"Forestry, Faculty of"@en . "DSpace"@en . "UBCV"@en . "Khan, Amer Ijaz"@en . "2010-04-30T14:44:17Z"@en . "2010"@en . "Master of Science - MSc"@en . "University of British Columbia"@en . "I explored effects of fertilization on soil N\u00E2\u0082\u0082O fluxes and underlying soil nutrients using short-term (up to 7 mo.) simulated operational fertilization with urea-nitrogen or nitrogen, phosphorus, potassium, and micronutrients (a N + micronutrients mix) in lodgepole pine, western hemlock, and Douglas-fir forests in British Columbia. The effect on the structure of ammonia- oxidizing bacterial (AOB) communities in the three forest ecosystems was also studied using polymerase chain reaction coupled with denaturing gradient gel electrophoresis (PCR-DGGE). \n Urea appeared to be rapidly mineralized to ammonium, and nitrification (relative to controls) was only observed in the lodgepole pine site and represented only 0.5% of added nitrogen. Across all sites and treatments, soils were as likely to consume as emit nitrous oxide, and among treatment replicates, rates were never significantly different from zero, with the exception of one efflux of 1.5 \u00CE\u00BCg m-\u00C2\u00B2 hr-\u00C2\u00B9 on the warmest day in the study. \n I conclude from this pilot study that in acidic, unpolluted (with regard to nitrogen deposition) upland conifer forest soils in western Canada fertilized once or infrequently with urea or ammonium or a combination of nutrients, soil greenhouse-gas flux dynamics are generally not altered over the short-term, with soils remaining neutral with regards to flux of nitrous oxide."@en . "https://circle.library.ubc.ca/rest/handle/2429/24250?expand=metadata"@en . "NITROUS OXIDE EMISSIONS, NUTRIENT DYNAMICS AND NITRIFIER COMMUNITIES FOLLOWING FERTILIZATION OF WESTERN HEMLOCK, LODGEPOLE PINE AND DOUGLAS-FIR FORESTS by Amer Ijaz Khan B.Sc. (Hons.), University of Agriculture, Faisalabad, Pakistan, 1993 M.Sc. (Hons.), University of Agriculture, Faisalabad, Pakistan, 1995 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in The Faculty of Graduate Studies (Forestry) THE UNIVERSITY OF BRITISH COLUMBIA (VANCOUVER) APRIL 2010 \u00C2\u00A9 Amer Ijaz Khan, 2010 ii ABSTRACT I explored effects of fertilization on soil N2O fluxes and underlying soil nutrients using short-term (up to 7 mo.) simulated operational fertilization with urea-nitrogen or nitrogen, phosphorus, potassium, and micronutrients (a N + micronutrients mix) in lodgepole pine, western hemlock, and Douglas-fir forests in British Columbia. The effect on the structure of ammonia- oxidizing bacterial (AOB) communities in the three forest ecosystems was also studied using polymerase chain reaction coupled with denaturing gradient gel electrophoresis (PCR-DGGE). Urea appeared to be rapidly mineralized to ammonium, and nitrification (relative to controls) was only observed in the lodgepole pine site and represented only 0.5% of added nitrogen. Across all sites and treatments, soils were as likely to consume as emit nitrous oxide, and among treatment replicates, rates were never significantly different from zero, with the exception of one efflux of 1.5 \u00CE\u00BCg m-2 hr-1 on the warmest day in the study. I conclude from this pilot study that in acidic, unpolluted (with regard to nitrogen deposition) upland conifer forest soils in western Canada fertilized once or infrequently with urea or ammonium or a combination of nutrients, soil greenhouse-gas flux dynamics are generally not altered over the short-term, with soils remaining neutral with regards to flux of nitrous oxide. iii TABLE OF CONTENTS ABSTRACT....................................................................................................................... ii TABLE OF CONTENTS ..................................................................................................iii LIST OF TABLES .............................................................................................................vi LIST OF FIGURES.......................................................................................................... vii ACKNOWLEDGEMENTS............................................................................................. viii DEDICATION................................................................................................................... ix 1. INTRODUCTION............................................................................................... 1 2. LITERATURE REVIEW..................................................................................... 4 2.1 Forest Fertilization ......................................................................................4 2.2 Effect of Fertilization on N2O Emissions................................................... 6 2.3 Nitrification................................................................................................ 7 2.3.1 Autotrophic Nitrification............................................................. 8 2.3.2 Archaeal Nitrification ................................................................11 2.3.3 Heterotrophic Nitrification ........................................................12 2.3.4 Importance of the Distinction Between Autotrophic and Heterotrophic Nitrification......................................................... 12 2.4 Denitrification........................................................................................... 14 2.4.1 Coupled Nitrification-Denitrification....................................... 14 2.4.2 Nitrifier Denitrification..............................................................18 2.4.3 Contribution of Denitrifiers and Nitrifiers to N2O Production..21 2.5 Rationale....................................................................................................23 2.6 Hypotheses..................................................................................................24 iv 3. MATERIALS AND METHODS ........................................................................25 3.1 Study Sites................................................................................................ 25 3.2 Site Fertilization ........................................................................................27 3.3 N2O Gas Flux Measurements.................................................................... 28 3.4 N2O Gas Analysis..................................................................................... 28 3.5 Soil Sampling for Nutrient Dynamics....................................................... 30 3.6 Soil Nutrient Analysis............................................................................... 30 3.7 Soil Sampling for DNA Extractions......................................................... 32 3.8 DNA Extractions...................................................................................... 33 3.9 PCR Amplification of DNA Samples .......................................................33 3.10 PCR Conditions.........................................................................................37 3.11 DGGE Conditions......................................................................................37 3.12 Statistical Analysis.................................................................................... 37 4. RESULTS............................................................................................................... 39 4.1 Soil Temperatures and Moisture Content................................................. 39 4.2 N2O Gas Flux............................................................................................ 41 4.3 Soil NH4 + and NO3 - Chemistry .................................................................43 4.4 Nitrifier Communities ...............................................................................46 4.5 Limits of the Study.................................................................................... 57 5. DISCUSSION......................................................................................................... 59 5.1 Greenhouse Gas Emission and Soil Nutrients.......................................... 59 5.2 Ammonia-oxidizing Communities............................................................ 63 5.3 General Limitations.................................................................................. 66 v 6. CONCLUSIONS ........................................................................................................68 BIBLIOGRAPHY .......................................................................................................69 APPENDICES ............................................................................................................85 1. DGGE profiles of bacterial 16 S rRNA PCR products amplified from soil under western hemlock 7 days following fertilization......................... 85 2. DGGE profiles of bacterial 16 S rRNA PCR products amplified from soil under western hemlock 50 days following fertilization........................ 86 3. DGGE profiles of bacterial 16 S rRNA PCR products amplified from soil under lodgepole pine 7 days following fertilization............................ 87 4. DGGE profiles of bacterial 16 S rRNA PCR products amplified from soil under lodgepole pine 210 days following fertilization ........................ 88 5. DGGE profiles of bacterial 16 S rRNA PCR products amplified from soil under Douglas-fir 7 days following fertilization.................................. 89 6. DGGE profiles of bacterial 16 S rRNA PCR products amplified from soil under Douglas-fir 60 days following fertilization............................... 90 7. Bands observed within each sample lane for western hemlock.................. 91 8. Bands observed within each sample lane for lodgepole pine...................... 92 9. Bands observed within each sample lane for Douglas-fir........................... 93 10. Matrix showing samples and the bands showing within each sample......... 94 vi LIST OF TABLE Table 1. Forward and Reverse primers used in this study................................................ 34 Table 2. Extractable inorganic and organic N, microbial biomass N and pH in 0-5 and 5-10 cm soil depths from lodgepole pine, western hemlock and coastal Douglas-fir sites ............................................................................................................................................45 Table 3. Percent of total added N recovered in all measured pools in 0-5 and 5-10 cm soil depth segments in N and complete fertilized plots in the lodgepole pine, western hemlock and coastal Douglas-fir site sampled 210, 50 and 60 days respectively following fertilization calculated as the difference between the averages of treatments and controls ............................................................................................................................................46 Table 4. A single-factor ANOVA for complete treatment (day 7 and day 60) in Douglas-fir stand ...............................................................................................................53 vii LIST OF FIGURES Figure 1.Transformations of mineral N in soil.................................................................. 6 Figure 2. Outline of the pathway and the enzymes involved in nitrification .....................8 Figure 3. Denitrification: outline of the pathway and enzymes involved .........................15 Figure 4. Nitrifier denitrification: hypothetical pathway and probable enzymes..............19 Figure 5. Gravimetric soil moisture and air and soil temperature at each site (across all treatment plots) and gas flux sampling date ....................................................40 Figure 6. Soil N2O fluxes at the lodgepole pine, western hemlock and Douglas-fir sites following fertilization............................................................................ 42 Figure 7. Extractable NH4+ - N, NO2- + NO3- -N in 0-5 and 5-10 cm soil depth segments following fertilization at the lodgepole pine site............................................... 44 Figure 8. NMS ordination for western hemlock stand 50 days after fertilization............ 47 Figure 9. Comparison of richness index for N and control treatments for western hemlock 50 days after fertilization...................................................................... 48 Figure 10. NMS ordination for lodgepole pine stand 7 days after fertilization................ 49 Figure 11. NMS ordination for lodgepole pine stand 210 days after fertilization............ 50 Figure 12. Comparison of richness index for N, control and complete treatments for lodgepole pine 210 days after fertilization.................................................................. 51 Figure 13. Comparison of richness index for control and complete treatments for Douglas-fir 7 days after fertilization................................................................................. 52 Figure 14. Comparison of richness index for complete treatment for Douglas-fir 7 and 60 days after fertilization............................................................................................ 53 Figure 15. Cluster analysis of composite matrix............................................................... 54 Figure 16. Cluster analysis of DGGE band patterns of all samples ..................................56 viii ACKNOWLEDGEMENTS I would like to acknowledge the generous help of many people on this journey. My deepest gratitude goes to my supervisory committee, Dr Sue J Grayston, Dr Cindy E Prescott, and Dr William Mohn. They gave me the opportunity to undertake the study, provided me with excellent guidance, and were always available in times of need. Funding for this research was made possible through the award of an NSERC strategic grant to Dr Grayston. All the past and present members of the Belowground Ecosystem Group (BEG) also deserve a special mention. Without their help and companionship, the task at hand would have been much arduous. A special thanks to Kate Del Bel for being helpful in the laboratory and being very patient with me. Lastly, I am extremely grateful to my family, including my parents and sister, my wife and kids, for always being there for me. All of this would not have been possible without their understanding, support, patience and innocent smiles. ix DEDICATION To my beloved family. 1 1. INTRODUCTION Soils contain great biodiversity (Torsvik et al., 1996), a great deal of which has not been described (Torsvik and Ovreas, 2002). This is due to the fact that only a small fraction of the microorganisms are actually cultivable (Pace, 1997). The recent increase in microbial diversity studies and the data available now has been possible due to (a) improvement in culture-independent, molecular techniques, in particular the Polymerase Chain Reaction (PCR) technique, as well as (b) extraction of deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) from environmental samples (Giovannoni et al., 1990). This newly acquired knowledge is now helping us understand distribution controls of these microorganisms and their community structure and activity impact on the ecosystem. Compared to other habitats, forests have soils with very high prokaryotic diversity (Torsvik et al., 2002), but, it is unclear how this diversity relates to the functioning of the forest ecosystems (Leckie, 2005). The inherent nature of soil complexity results in the isolation of organisms in the soil environment, due to availability of resources at different depths of soils (Treves et al., 2003). Northern temperate forests are usually N limited (Vitousek and Howarth, 1991) and N fertilization has been shown to have a substantial positive effect on tree and stand growth (Weetman et al., 1988; Brockley 1992, 1996; Berch et al., 2006). Typically, one fertilizer application produces a temporary increase in tree and stand growth lasting 6\u00E2\u0080\u00939 years. Fertilization studies with Pinus and Picea species in boreal forest regions have suggested that sustained growth responses, and large reductions in rotation length, are achievable by repeatedly fertilizing young stands (Tamm, 1991; Malkonen and Kukkola, 1991; Bergh et al., 1999). Bergh et al., (2005) calculated that the growth of Norway spruce (Picea abies 2 L.) in northern Sweden could potentially be tripled by frequent applications of balanced fertilizers, thus shortening rotation lengths by as much as 40\u00E2\u0080\u009360 years, based on results from long-term fertilization experiments. In British Columbia, a number of maximum productivity trials were initiated in the 1990\u00E2\u0080\u0099s to demonstrate that N and P fertilization of plantation forests can also increase growth and stand volume but also economically viable (Brockley and Simpson, 2004). When N is supplied through fertilization, deficiencies of other nutrients may limit the growth response (Brockley and Sanborn, 2009). Growth responses may be enhanced if sulphur (S) and/or boron (B) is combined with N in fertilizer prescriptions (Brockley and Simpson, 2004). All the autotrophic ammonia - oxidizing bacteria (AOB) strains from terrestrial and freshwater environments belong to a single (monophyletic) group within the \u00CE\u00B2 \u00E2\u0080\u0093 proteobacteria (Head et al., 1993) comprising of two genera, Nitrosomonas and Nitrosospira (Stephen et al., 1996). Once fertilized, the AOB are involved in the oxidation of ammonium ion (NH4 + ) or ammonia (NH3) to nitrate (NO3 - ) via nitrite (NO2 - ), a process known as nitrification. These reactions are carried out by two groups of organisms: the first part (up to NO2 - ) is conducted by the so-called NH3 oxidizers or primary nitrifiers, whereas the second step is carried out by NO2 - oxidizers or secondary nitrifiers (Bock et al., 1986). Nitrification reduces the likelihood of NH3 emissions, but increases the chances that more oxidized forms are converted via denitrification to nitrous oxide (N2O) or dinitrogen gas (Jarvis et al., 2009). Nitrous oxide (N2O) is a potent greenhouse gas, which contributes to global climate change, having a global warming potential (GWP) (a function of enhanced radiative forcing and atmospheric residence 3 time) 310 times that of carbon dioxide (CO2) on a mole per mole basis (IPCC, 1996). The atmospheric N2O concentration is presently 314 ppb which is increasing at a rate of 0.25% per year (Houghton et al., 2001). The question at this juncture is whether such additions of fertilizer are exacerbating greenhouse-gas emissions, in particular nitrous oxide (N2O) emissions, into our environment. One approach in trying to understand the effect of fertilizers on N2O emissions is to target the nitrifiers, the AOB, which are a more constrained microbial group, phylogenetically (Enwall et al., 2007). 4 2. LITERATURE REVIEW 2.1 Forest Fertilization Fertilization is important in forestry because it increases C stocks in tree biomass (Canary et al., 2001; Nohrstedt et al., 1989), reduces rotation times, and may also increase C stocks in the forest floor (Prietzel et al., 2006). Fertilization increases plant productivity and plant biomass, which increases litterfall inputs, and thus soil C (Johnson, 1992). One potential drawback of forest fertilization is that it may result in increased N2O release through microbial nitrification and denitrification. However, evidence for such an effect is complex and contradictory, because N2O emissions from forest soil occur as a result of microbial production and consumption processes, which are linked to microbial N turnover processes of nitrification and denitrification (Conrad, 1996; 2002). These processes are highly variable both spatially and temporally, being influenced by environmental factors such as climate, meteorological conditions, soil and vegetation properties and human management (Kesik et al., 2005). Hence, emissions of N trace gases from forest soils show considerable variations between seasons, years and measuring sites (Butterbach-Bahl et al., 2002). Determination of the effects of fertilization on emissions of N2O is critical to ensure that the benefit of increased C sequestration is not offset by increased GHG emissions. Despite their importance in nutrient cycling processes and their role in greenhouse gas production, few studies have characterized microbial communities, especially in forest ecosystems. Soil microbes, including bacteria and fungi, play pivotal roles in various biogeochemical cycles (Molin and Molin, 1997; Wall and Virginia, 1999) and are responsible for the cycling of organic and inorganic compounds. Soil micro-organisms 5 also influence above-ground ecosystems by contributing to plant nutrition (Timonen et al., 1996), plant health (Smith and Goodman, 1999), soil structure, mycorrhizal fungi (Dodd et al., 2000) and soil fertility (O\u00E2\u0080\u0099Donnell et al., 2001). Our knowledge of soil microbial diversity and functionality is limited because of the limitations in the methods used for studying them. In particular, there is great uncertainty about the organisms that contribute to the global N-cycle in natural ecosystems, because most prokaryotes cannot be cultivated in the laboratory (Pace, 1997; Hugenholtz et al., 1998). Recent advances in molecular techniques, based on Polymerase Chain Reaction (PCR) are finally allowing us to study the micro-organisms, especially nitrifying and denitrifying bacteria, at the molecular level to understand their response to nitrogen fertilization, although these methods have their own limitations (Kirk et al., 2004). Novel genes for nitrite reductases (nirS, nirK) and ammonia monooxygenase (amoA) encoding key enzymes of denitrification and nitrification, respectively, have been amplified from environmental samples (Braker et al., 1998; Braker et al., 2000; Purkhold et al., 2000; Avrahami et al., 2002; Nogales et al., 2002; Webster et al., 2002). Denitrification and nitrification are believed to be the main processes producing nitrous oxide (N2O) in soils. Low rainfall and coarse soil texture generally promote nitrification, whereas high rainfall, fine soil texture and high C content promote denitrification, although both processes may occur simultaneously within soils (Davidson, 1991). Of the two, denitrification is considered to be the major source of N2O under most situations, while nitrification is reported to make a substantial contribution to the N2O emissions only under aerobic conditions (Williams et al., 1998). 6 Figure 1. Transformations of mineral N in soil (Source Wrage et. al. 2001) 2.2 Effect of Fertilization on N2O Emissions There are contradictory reports of the effect of mineral N fertilization on N2O emission. It has been shown that both NO3 - and NH4 + -based fertilizers can lead to greater N2O emissions among different soil systems (Azam et al., 2002; Linzmeier et al., 2001). In a study of the emissions of N2O from boreal agricultural clay and loamy sand soils, N2O flux did not vary as a function of applied N and were better estimated from soil physical properties, such as soil porosity (Syvasalo et al., 2004). A fine soil texture, restricted drainage and neutral to slightly acidic soil reaction are generally thought to favor N2O emission (Bouwman et al., 2002). In addition to soil conditions, N2O emissions are also affected by the timing of fertilizer application. Fertilizer application timing and mode influence NH3 volatilization and the efficiency of plant uptake, hence availability of N for nitrification and denitrification. Timing and matching the N application with plant needs is important, because prolonging the period in which NH4 + -based fertilizer can undergo nitrification or NH3 NH2OH NO2 - NO N2O N2 Pathway: Nitrifier Denitrification Nitrification N2O NO3 - NO2 - NO N2O N2 Denitrification 7 NO3-based fertilizers can be denitrified, without competition from plant uptake, is likely to increase emissions of NO and N2O (Ortiz-Monasterio et al., 1996; Smith et al., 1997; Chantigny et al., 1998;). Linzmeier et al., (2001) found that the application of fertilizer in the spring and under dry conditions resulted in a significant reduction in N2O emissions in soil under wheat cultivation. The processes of denitrification and nitrification can also occur simultaneously (Kuenen and Robertson, 1994). The availability of ammonium (NH4 + ) and oxygen (O2) are the most important factors controlling soil nitrification (Firestone and Davidson, 1989). The major controls on biological denitrification include the availability of carbon (C), NO3 - (and other N oxides) and O2 (Tiedje, 1988). However, it is not easy to ascertain the real contribution of either process to observed N2O fluxes (Arah, 1997). 2.3 Nitrification Nitrification can be divided into two processes: autotrophic nitrification and heterotrophic nitrification. 8 Figure 2. Outline of the pathway and the enzymes involved in nitrification (Source Wrage et al. 2001) 2.3.1 Autotrophic Nitrification Nitrification is the oxidation of ammonium ion (NH4 + ) or ammonia (NH3) to nitrate (NO3 - ) via nitrite (NO2 - ). These reactions are carried out by two groups of organisms: the first part is conducted by the so-called NH3-oxidizers or primary nitrifiers, whereas the second step is carried out by NO2 - -oxidizers or secondary nitrifiers (Bock et al., 1986). The oxidation of NH3 to NO3 - is due to two kinds of nitrifiers: the ammonia oxidizers (belonging to the genus Nitrosomonas), which oxidize NH3 to NO2 - in two steps (Hooper, 1986; Prosser, 1989; Muller et al., 1995): 1: NH3 + O2 + 2H + + 2e - \u00EF\u0083\u00A0 NH2OH + H2O (ammonia mono-oxygenase) 2: NH2OH + H2O \u00EF\u0083\u00A0 NO2 - +5H + + 4e - (hydroxylamine oxidoreductase) 3: 0.5O2 + 2H + + 2e - \u00EF\u0083\u00A0 H2O Total: NH3 + 1.5 O2 \u00EF\u0083\u00A0 NO2 - + H + + H2O NH3 NH2OH NO2 - NO3 - Ammonia monooxygenase Hydroxylamine oxidoreductase Nitrite oxidoreductase N2O ? N2O Ammonia oxidation Nitrite oxidation O2 + 2H + 2e - H2O 9 Nitrite oxidizers (belonging to genus Nitrobacter) are responsible for the oxidation of NO2 - to NO3 - (Hooper, 1986; Prosser, 1989; Muller et al., 1995): 1: H + + NO2 + H2O \u00EF\u0083\u00A0 H + + NO3 + 2H + + 2e - (nitrite oxidoreductase) 2: 0.5O2 + 2H + + 2e - \u00EF\u0083\u00A0 H2O Total: H + + NO2 + 0.5O2 \u00EF\u0083\u00A0 H + + NO3 Autotrophic ammonia-oxidizing bacteria use the essential enzyme ammonia mono- oxygenase to transform ammonia to hydroxylamine. The amo operon consists of at least three genes, amoC, amoA and amoB. The amoA gene encodes the subunit containing the putative enzyme active site (Norton et al., 2002). In particular amoA, the gene that encodes the first subunit of ammonia monooxygenase, is frequently used to study genetic diversity of ammonia-oxidizing bacteria (AOB). The amoA primer set is highly specific for ammonia-oxidizers and is suitable for assessing community shifts (Nicolaisen and Ramsing, 2002). Due to its higher diversity compared with 16S rRNA genes, it allows a greater resolution for the study of genetic differences in natural populations of AOB (Purkhold et al., 2000). Compton et al., (2004) studied the response of AOB community composition to chronic nitrogen additions in a hardwood forest and found that the ammonia monooxygenase gene (amoA) was more prevalent in high N-treated soils compared to untreated soils. A study utilizing amoA gene fragments amplified from a nitrogen-saturated forest soil suggested that environmental heterogeneity affects ammonia oxidizer numbers and activity, but not ammonia oxidizer community structure (Laverman et al., 2001). Analysis of environmental sequences by PCR amplification of 16S rRNA genes provided evidence for the sub-division of ammonia-oxidizers into two genera 10 (Nitrosospira and Nitrosomonas), and also indicated the existence of at least seven sub- clusters, four within Nitrosospira and three within Nitrosomonas (Stephen et al., 1996). A more recent extensive study compared phylogenetic analysis of 16S rRNA gene with that of a key functional gene amoA, encoding ammonia monooxygenase (Purkhold et al., 2000). The two phylogenies indicate similar evolutionary relationships and suggested that additional subgroups/clusters exist beyond those defined by Stephen et al., (1996). These two groups together belong to the family Nitrobacteriaceae (Buchanan, 1917). Nitrosomonas europaea is, perhaps, the best studied autotrophic NH3 oxidizer, but it is not the most common primary nitrifier in most soils (Macdonald, 1986; Klemedtsson et al., 1999). The Nitrobacteriaceae are aerobes and many are obligate autotrophs. Explanations for how autotrophic nitrification could occur in acid soils include growth and/or activity on surfaces (Allison and Prosser, 1993) and ureolytic activity (Allison and Prosser, 1991) as urea hydrolysis occurs at low pH values, enabling oxidation of ammonia produced intra-cellularly (Burton and Prosser, 2001). One study demonstrated the ability of ureolytic autotrophic ammonia oxidizers to contribute to nitrification at pH values as low as 4 when supplied with urea, without the requirement for surface growth or micro - environments of higher pH (Burton and Prosser, 2001). Autotrophic bacteria such as those belonging to the genus Nitrosomonas obtain their energy from the oxidation of N and their C from CO2 \u00E2\u0080\u0093\u00E2\u0080\u0093 both inorganic sources. Thus, the energy for the CO2 fixation originates from nitrification. N2O is formed during NH3 oxidation through chemical decomposition of intermediates between NH4 + and NO2 - such as hydroxylamine (NH2OH) or NO2 - itself. This is usually regarded as a special form of chemodenitrification (Chalk and Smith, 1983), which is closely linked with NH3 11 oxidation as the latter is the source of the substrates for chemodenitrification. There is also evidence that incomplete oxidation of NH2OH can lead to the development of N2O (Hooper and Terry, 1979). Thus, NH3 oxidation to NO2 - can be a source of N2O. 2.3.2 Archaeal Nitrification There is recent evidence that archaea possess amoA genes and that they may be the dominant nitrifiers, particularly in acid forest soils. There is much debate currently, as to whether these archaea are true autotrophs, heterotrophs or facultative. Nicol and Schleper (2006) have reported crenarchaeal sequences of kingdom Crenarchaeota domain Archaea from all major moderate environments including forest, agricultural, grassland and alpine soils (Bintrim et al., 1997; Jurgens et al., 1997; Buckley et al., 1998; Nicol et al., 2003 & 2005). With the development of cultivation-independent molecular analysis, their abundance is now being investigated. According to one estimate, at least 2.3 x 10 28 cells of the estimated 3.7 x 10 29 microbial cells in aquatic and soil environments might represent Crenarchaeota (i.e. ~ 6% of prokaryotes in these environments, if not more) (Whitman et al., 1998). Genes that potentially encode ammonia monooxygenase, a key enzyme in nitrification, have also been recently discovered in archaea (Venter et al., 2004; Ko\u00C2\u00A8nneke et al., 2005; Treusch et al., 2005; Schleper et al., 2005). Nicol and Schleper (2006) have suggested a role for marine and terrestrial Crenarchaeota in ammonia oxidation. Leininger et al., (2006) claimed that archaea were the dominant nitrifiers in 12 pristine and agricultural soils in three climatic zones. They used RT-PCR and complementary DNA analysis using novel cloning-independent pyrosequencing technology. The results suggested that archaeal amoA gene copies were up to 3,000-fold 12 more abundant than the bacterial amoA gene by working on Isoprenoid glycerol dialkyl glycerol tetraethers (GDGTs), which are unique membrane lipids of archaea and are often used as biomarkers to study their presence and distribution. It is quite possible that these archaeal communities are present, and may even dominate the nitrifier community in forest and acidic soils. 2.3.3 Heterotrophic Nitrification Heterotrophic nitrifiers use organic carbon (C) as a source of C and energy (Robertson and Kuenen, 1990; Castignetti, 1990). Heterotrophic nitrifiers can oxidize organic forms of N such as urea as well as NH3 (Papen et al., 1989). In the acid soils of Pasirmayang, N2O is produced mainly through nitrification by heterotrophic nitrifiers (Nakajima et al., 2005). Under aerobic condition, heterotrophic nitrifiers produce much more N2O per cell than autotrophic nitrifiers (Papen et al., 1989; Anderson et al., 1993). 2.3.4 Importance of the Distinction Between Autotrophic and Heterotrophic Nitrification Nitrification in soil is generally thought to be performed by a number of autotrophic soil bacteria and archaea. It has been shown that chemoautotrophic ammonium-oxidizing bacteria are the predominant source of NO and N2O produced during nitrification in soil (Tortoso and Hutchinson, 1990). The oxidation of NH3 to NO3 - is mainly due to the action of two groups of autotrophic organisms typified by the genera Nitrosomonas and Nitrobacter (Koops et al., 1991). Heterotrophic microorganisms are also known to produce NO3 - in vitro, although the significance of this process in N-cycling is largely 13 unknown (Killham, 1986). Since autotrophic nitrifying organisms seem to be sensitive to low pH, it has been suggested that heterotrophic nitrification might be dominant in acid forest soils (Ishaque and Cornfield, 1976; Adams, 1986; Stroo et al., 1986; Duggin et al., 1991). However, some studies suggest that acidophilic autotrophs are also involved in the production of NO3 - in acid forest soils (Duggin et al., 1991; Pennington and Elli, 1993). There is increasing evidence that archaea are present in a wide range of soils worldwide and that they may be the dominant nitrifiers in these soils (Leininger et al., 2006; Offre et al., 2009). One important method to discriminate autotrophic and heterotrophic nitrification is the acetylene (C2H2) inhibition test. C2H2 was first found to inhibit NH3 oxidation in pure cultures of N. europaea (Hynes and Knowles, 1978), and then established as a potent inhibitor of nitrification in soil (Bremner and Blackmer, 1979; Walter et al., 1979; Berg et al., 1982). C2H2 can be described as a mechanism-based inhibitor, a compound that will inhibit as a result of the normal catalytic cycle of the enzyme, producing an inhibitory product from the compound. Usually it involves irreversible inactivation of the enzyme through its covalent modification by the product of catalysis (McCarty, 1999). The ammonia monooxygenase from the heterotrophic nitrifier Pseudomonas denitrificans is not inhibited by acetylene (C2H2), which is how the two processes can be discriminated. However, it is not known whether archaeal gene (amoA) is inhibited by acetylene or not, though very recent evidence suggests archaea are inhibited by C2H2 (Offre et al., 2009). Therefore, in forests where heterotrophic nitrification was thought to dominate, it may actually be the archaea that are the dominant nitrifiers. Compared to the multi-haem enzyme found in the autotrophs, the heterotrophic hydroxylamine 14 oxidoreductase is a non-haem enzyme (Richardson et al., 1998). Unlike conventional denitrifiers, the heterotrophic nitrifiers are also sometimes able to denitrify under aerobic conditions (Robertson et al., 1989) and N2O is produced as an intermediate in the reduction of NO2 - to N2, as in denitrification (Anderson et al., 1993; Richardson et al., 1998). 2.4 Denitrification Denitrification can lead to loss of N from soil systems, and incomplete conversion of mineral N to N2 results in the formation of nitric oxide (NO), which can contribute to ozone formation, and nitrous oxide (N2O) (O\u00C2\u00A8quist et al., 2004; Zumft, 1999). During complete denitrification, nitrate is sequentially reduced to dinitrogen gas through the generation of the intermediates nitrite, nitric oxide (NO), and nitrous oxide (N2O) (Zumft, 1997). Each reductive step is catalyzed by a separate nitrogen oxide reductase. The concerted activity of the four nitrogen oxide reductases typically maintains a steady flow of intermediates (Goretski et al., 1990, Zumft, 1997). Until recently it was thought that anaerobic denitrifying bacteria were responsible for denitrification. However, recent evidence is showing the existence of nitrifier denitrification by both bacteria and archaea (Hayatsu et al., 2008) and fungal denitrification (Shoun et al., 1992). 2.4.1 Coupled Nitrification-Denitrification Coupled nitrification-denitrification is the process where denitrifiers reduce NO2 - or NO3 - that was produced by nitrifiers. 15 Nitrate Nitrite Nitric oxide Nitrous oxide reductase reductase reductase reductase Figure 3. Denitrification: outline of the pathway and enzymes involved (Source Wrage et al 2001) Denitrification consists of four reaction steps by which nitrate is reduced into dinitrogen gas through the action of metalloenzyme, nitrate reductases, nitrite reductases, nitric oxide reductases and nitrous oxide reductases. Nitrite reductase is the key enzyme of this respiratory process since it catalyzes the reduction of soluble nitrite into N2 gas. Two structurally different nitrite reductases, utilizing different prosthetic metals have been characterized: a copper nitrite reductase encoded by the nirK gene and a cytochrome cd1- nitrite reductase encoded by the nirS gene (Zumft, 1997). Several studies have used nirK and nirS as molecular markers to study the diversity of denitrifying bacteria in various environments (Prieme et al., 2002, Yoshie et al., 2004). However, it has recently been shown that nirK gene, thought to be necessary for production of NO and N2O by Nitrosomonas europaea was actually not essential, since nirK-deficient cells still produced nitric oxide (NO) and nitrous oxide (N2O) (Beaumont et al., 2002). Of the two nitrite reductase genes, the nirS gene is the more widely distributed than the nirK gene. Although structurally different, both types of enzyme are functionally and physiologically equivalent (Glockner et al., 1993; Zumft, 1997). However, the more widely distributed nirS gene is found in only 30% of the denitrifiers studied so far, while the nirK gene is found in a wider range of physiological groups (Coyne et al., 1989). The NO3 - NO2 - NO N2O N2 16 nirS gene has not been identified in nitrifying bacteria, but nirK is found in both nitrifying and denitrifying bacteria (Chain et al., 2003, Casciotti and Ward, 2001). The high diversity of nirK and its ambiguous association with nitrifiers and denitrifiers makes it an unsuitable marker for distinguishing the relative abundance or diversity of these functional groups (Casciotti and Ward, 2004). The enzyme that forms the N-N bond during denitrification is nitric oxide reductase. The enzyme comprises two subunits, the smaller subunit nor C and the larger subunit nor B. Nor C is a membrane anchored cytochrome c, and nor B contains protohemes (Berks et al., 1995). Braker and Tiedje (2003) explored the distribution of norB in cultured denitrifying strains and in environmental samples and demonstrated its promise as a functional gene marker for denitrification. N2O can be formed in soils by denitrification within anoxic microsites within soil aggregates (Renault and Stengel, 1994) or by aerobic denitrification (Robertson and Kuenen, 1984; Robertson et al., 1989). Anaerobic denitrification involves the reduction of nitrate via nitrite and nitric oxide (NO), to N2O and N2. The necessary conditions for the process occur when respiratory consumption of oxygen (O2) in the soil by plant roots and soil microorganisms exceeds the rate of replenishment by diffusion from the atmosphere. Denitrification, as an anaerobic metabolic process, is controlled by oxygen level, electron donors (organic carbon) and electron acceptors (nitrate) (Firestone and Davidson, 1989). The concentration of nitrate (or nitrite) in the soil is another important regulator and the third main controller is the amount of available organic carbon (Tiedje, 1988). Denitrifiers are widely distributed across the bacterial taxa and include species of 17 Pseudomonas, Bacillus, Thiobacillus, Propionibacterium and others (Firestone, 1982). These predominantly heterotrophic microorganisms are facultative anaerobes that are able to use NO3 - in place of oxygen as an electron acceptor in respiration to cope with low-oxygen or anaerobic conditions. At high O2 concentrations, the aerobic metabolism of denitrifiers is promoted so that the reduction of NO3 - does not take place. Although denitrification is generally thought of as an anaerobic process, there have been many reports of aerobic denitrification (Lloyd et al., 1987; Robertson et al., 1989; Bell et al., 1990; Zart and Bock, 1998; Chen et al., 2003). Because of the interest in sub-boreal forests as a potential sink for atmospheric CO2, previous work examining the fate of excess N as environmental deposition comes from northern mid-latitude forests (Dise and Wright, 1992; Seely and Lajtha, 1997; Nadelhoffer, 2001). Higher N2O emissions are often reported from fertilized compared to unfertilized soils, rates of emission being greatest following application of NH4 + or NH4 + - forming fertilizers (Breitenbeck et al., 1980; Flessa et al., 1996; Smart et al., 1999). Since N2O is an intermediate of denitrification, which can be released in high quantities in low- oxygen environments with sufficient NO3 - and metabolizable organic carbon, release of N2O from soils could be increased by the increased availability of soil N caused by forest fertilization. Ammonia - oxidizers are capable of reversing their natural reaction process by reducing NO2 - in the presence of O2 (Hooper, 1986). There are reports that autotrophic nitrifiers are able to reduce NO2 - to NO, N2O, or N2 under oxygen limitation (Poth, 1986; Remde and Conrad, 1990). This process is known as aerobic denitrification with the end product of the reaction being dependent on the organisms and the presence of a suitable 18 electron acceptor (Poth, 1986; Remde and Conrad, 1990). Autotrophic ammonia-oxidizer isolates with the ability of aerobic denitrification have been put into the genus Nitrosomonas (Poth, 1986; Remde and Conrad, 1990). The denitrifying capacity of nitrite oxidizers has been studied less extensively and a number of Nitrobacter isolates have been found incapable of denitrification under oxic conditions (Hynes and Knowles, 1984; Freitag et al., 1987; Bock et al., 1995). Lloyd et al., (1987), using simultaneous mass spectrometric monitoring of dissolved N2, NOx and O2, found that under laboratory conditions a number of different bacteria can denitrify, even when O2 concentrations approach or even exceed air saturation values. Robertson et al., (1989) studied various heterotrophic nitrifiers in a chemostat environment and found that some of them were also aerobic denitrifiers. The mechanism for the production of N2O and NO are unclear so far. There are two possible hypotheses for aerobic denitrification. First, NO and N2O are produced as the result of biological activity by ammonia-oxidizers (Hooper and Terry, 1979; Hynes and Knowles, 1984). Second, NO and N2O are produced as a result of chemical reactions involving unstable nitrification intermediates (Hynes and Knowles, 1984; St\u00C3\u00BCven et al., 1992). Most of the evidence reported so far appears to support the first hypothesis (Remde and Conrad, 1990; Anderson et al., 1993; Bock et al., 1995). 2.4.2 Nitrifier Denitrification Nitrifier denitrification is the process where ammonia is oxidized to nitrite, followed by reduction of nitrite to nitric oxide, nitrous oxide and nitrogen gas. The process is carried out by autotrophic nitrifying bacteria and archaea. 19 Figure 4. Nitrifier denitrification: hypothetical pathway and probable enzymes (Source Wrage et al 2001) The two processes of nitrification and denitrification are involved in the conversion of NH3 to N2 gas in the nitrogen cycle (Colliver and Stephenson, 2000). Nitrification is the oxic oxidation of NH3 + to NO3 - via NO2 - using O2 as the terminal electron acceptor. On the other hand, denitrification is the anoxic process in which N-oxides are used as the terminal electron acceptor in place of O2 (Payen, 1981). Nitrification and denitrification inhibitors and artificial electron donors were used to establish the route of NO and N2O production by Remde and Conrad (1990). They showed that both NO and N2O were actually produced during reduction of NO2 - , rather than oxidation of NH3. Remde and Conrad (1990) found that despite adding formaldehyde as a growth inhibitor to oxic cultures of Nitrosomonas and Nitrosovibrio, 15% NO was still being produced as compared to control, although no N2O was produced. This was suggested to be due to chemical decomposition. According to Chalk and Smith (1983) N2O is formed during NH3 oxidation through chemical decomposition of intermediates between NH4 + and NO2 - such as NH2OH and NH3 NH2OH NO2 - NO N2O N2 Ammonia monooxygenase Hydroxylamine oxidoreductase Nitrite reductase Nitric oxide reductase Nitrous oxide reductase Nitrification Denitrification 20 NO2 - itself. Chalk and Smith (1983) have given the possible routes for this chemodenitrification as follows: 1: 3HNO2 \u00E2\u0086\u0094 HNO3 + 2NO + H2O 2: 2 HNO2 \u00E2\u0086\u0094 NO + NO2 + H2O 3: HNO2 + HNO3 \u00E2\u0086\u0094 2NO2 + H2O 4: NH2OH + HNO2 \u00E2\u0086\u0094 N2O + 2 H2O 5: HNO2 + NH4 + \u00E2\u0086\u0094 N2 + 2 H2O + H + Work by Anderson et al., (1993) also found that by growing N. europaea in the presence of a number of artificial electron donors and electron acceptors, both NO and N2O are produced during the reduction of NO2 - rather than from oxidation of NH3 or NH2OH. According to Jetten et al., (1997); 1: NO2 - + e - + 2H + \u00EF\u0083\u00A0 NO + H2O 2: NO + e - + H + \u00EF\u0083\u00A0 1/2N2O + 1/2 H2O Total: NO2 - + 2e - + 3H + \u00EF\u0083\u00A0 1/2N2O + 1 1/2 H2O On the other hand, Hooper and Terry (1979) have pointed out the evidence that incomplete oxidation of NH2OH can lead to the development of N2O. Ammonium oxidation by ammonium oxidizing bacteria under low O2 concentration leads to production of NO, N2O and N2 from nitrite reduction (Shrestha et al., 2002). Tallec et al (2006) have reported that the N2:N2O emission percentage varies with the oxygen condition, but N2 remains the major product, never less than 93% and 94% of total gaseous nitrogen removal for nitrifier denitrification and denitrification respectively in a batch-reactor experiment. 21 2.4.3 Contribution of Denitrifiers and Nitrifiers to N2O Production There are different indicators which can determine the source of N2O from the soil. One of them is acetylene (C2H2). Being one of many substrates that ammonia monooxygenase can use for its catalytic oxidations, C2H2 can inhibit nitrification by converting quickly into an epoxide which inhibits ammonia monooxygenase by covalently binding to it (McCarty (1999), Wrage et al., (2001)). Berg et al. (1982) reported that acetylene inhibits ammonia oxidation by autotrophic nitrifiers at low (10 Pa) partial pressure of C2H2, and inhibits N2O reductase during denitrification at high (10 kPa) pressure. Its application has provided evidence that both processes may proceed simultaneously in soil (Garrido et al., 2002). Daum et al., (1998) found that acetylene did not inhibit the oxidation of NH4 + by heterotrophic nitrifiers at the low concentrations used to inhibit autotrophs. Recent advances in stable-isotope techniques allowing direct measurement of 15 N-N2O provide a more accurate determination of the source of N2O where several processes are contributing to emissions (Baggs et al., 2003). This can be coupled with C2H2 (10 Pa; 0.01% v/v) inhibition to determine the respective contributions of denitrification, autotrophic nitrification and heterotrophic nitrification (Bateman and Baggs, 2005). Menyailo et al. (2003), based on their stable-isotope experiments, have suggested that denitrification produces much more N2O than nitrification. The last stage of the denitrification process can reduce N2O, already produced during the process, to molecular nitrogen (N2). Thus, the N2O emission may depend on the ratio between the N2O produced by denitrification and N2O being consumed by denitrification. If the ratio is higher, it is expected that the N2O emission from the soil will be higher. 22 Two other factors that might be of importance to N2O emission are water content and temperature. At high water content, where the diffusion rates of O2 and NO in soil are slow, NO produced is reduced to N2O before being emitted from soil (Davidson,1992). Davidson (1992) also suggested that biological consumption of N2O probably requires more severe reducing conditions than does the consumption of NO. The high water content (i.e. high water-filled pore space (WFPS)) increases the anaerobic conditions in soil and favors denitrification (Wall and Heiskanen, 1998). Freezing of soil destroys microbial cells and liberates the organic compounds of cells which are good substrates for heterotrophic microbes (Skogland et al., 1988; Christensen and Tiedje, 1990; Papen and Butterbach-Bahl, 1999). Koponen and Martikainen (2004) have suggested that denitrifiers benefit more than heterotrophs from the extra substrates liberated in soil at low temperature. The ice in the pores of soil acts as a diffusion barrier, enabling the reduction of NO in denitrification. At temperatures below zero, limited oxygen diffusion resulting from the ice barrier can enhance N2O production (Teepe et al., 2000). The N2O and NO production and consumption rates could thus cause differences in the ratio of NO:N2O in the emissions. This would explain the low NO emission rates at temperatures below 0 o C. An important factor in the release of N2O from soils is pH. It influences the three most important processes that generate nitrous oxide and nitrogen: nitrification, denitrification and dissimilatory NO3 - reduction to NH4 + (Stevens et al. 1998). It has been suggested that the N2O:N2 ratio of denitrification increases at low pH values due to the pH sensitivity of N2O reductase (Ottow et al., 1985; Thomsen et al., 1994). However there are reports of 23 low pH inhibiting the denitrification process as well (Christensen (1985), Nagele and Conrad (1990 a, b), Blosl and Conrad (1992)). 2.5 Rationale This study formed part of a larger project of which the aim was to assess the potential of forest fertilization to increase C sequestration in aboveground biomass and soil in three forest types in B.C. that are commonly fertilized and also to ascertain that addition of fertilizers was not going to exacerbate the problem of greenhouse-gas emissions through release of N2O or inhibition of CH4 oxidation. As soil microorganisms are responsible for these greenhouse gas fluxes another important aspect of the project was to characterize the underlying microbial communities in these soils that are involved in the processes of CH4 oxidation, nitrification and denitrification. My specific aims in this project were to determine if fertilization of these forests alters N2O emissions from soil and to characterize the microbial communities which are responsible for nitrification and may be responsible for denitrification in these soils. I explore the short-term (up to 7 months) effects of simulated operational fertilization on soil N2O fluxes and on underlying soil nutrient and microbial biomass dynamics in three economically important conifer plantation forests in British Columbia. Transformations of added N forms were characterized to explore the specific mechanisms of potentially altered N2O fluxes. I also characterized some of the microbial communities (nitrifiers) which may be responsible for nitrification and N2O production in these soils. Primers for specific gene sequences associated with nitrifier populations were used to amplify DNA extracted from 24 these soils and DGGE was used to fingerprint the microbial communities. Fumigation- extraction procedures were also used to determine dynamics of microbial and organic C and N, and inorganic N (NO3 - and NH4 + ). This information was used to assess the effects of fertilization on microbial biomass, microbial physiological adaptations (illustrated through C: N ratios) as well as biologically available (i.e. K2SO4 extractable) inorganic N. 2.6 Hypotheses 1. A single addition of N will lead to a short-term enhanced N2O efflux through stimulated nitrification and denitrification. I also predict that N2O emissions will be substantially lower than in agricultural systems owing to constrained nitrification in acidic soils. 2. N2O emissions will be higher in the Douglas-fir stand than the western hemlock and lodgepole pine stands, as a consequence of differences in soil pH and other soil chemical characteristics and environmental factors (temperature, moisture) that affect the microbial community. 3. Differences in nitrification rates and N2O emissions following fertilization of the three stands will be associated with differences in the nitrifier communities in these soils. 25 3. MATERIALS AND METHODS 3.1 Study Sites The tree species selected for the study are commonly fertilized by the forest industry in Western Canada. These are western hemlock (Tsuga heterophylla Raf. Sarge), lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) and coastal Douglas-fir (Pseudotsuga menziesii Mirb.Franco). Three forest types in different biogeoclimatic (BEC) zones were chosen because of their proximity to long-term research installations set up to monitor the effects of fertilization on stand dynamics. The first site, a lodgepole pine forest was located approximately 100 km east of Prince George, British Columbia (53\u00C2\u00B0 55' N 122\u00C2\u00B0 46' W) near Kenneth Creek in the Sub-Boreal Spruce zone and near long-term research sites established by the British Columbia Ministry of Forests and Range. The site was planted in the spring of 1983 following clear-cutting and broadcast burning. The site was situated at an elevation of approximately 1000 m above sea level. The nearby city of Prince George has an average temperature of -9 \u00C2\u00B0C and 15 \u00C2\u00B0C for the months of January and August respectively and receives between 600-700 mm of rain per year (Weather Network A). The understory consisted mainly of grasses and shrubs, and the soil generally belonged to the Eluviated Dystric Brunisol sub-group (Soil Classification Working Group 1998) with between 2 and 8 cm of the surface horizon and a distinct eluviated (Ae) layer varying from 3 to 10 cm throughout the site. However in certain areas, a Bf horizon greater than 10 cm in thickness existed, thus meeting the diagnostic criterion for the podzolic order (Soil Classification Working Group 1998). 26 The second site was a western hemlock forest close to Port McNeill, British Columbia in the very wet hyper maritime Coastal Western Hemlock zone (Pojar et al., 1987) on northern Vancouver Island, British Columbia (50\u00C2\u00B0 43'N 127\u00C2\u00B0 30'W). The site was clearcut-harvested and slash-burned in early 1980\u00E2\u0080\u0099s. My plots were near the fertilization demonstration (DEMO) plots set up by Western Forest Products Inc. as part of the SCHIRP (Salal Cedar Hemlock Integrated Research Project). At the time of study, western redcedar (Thuja plicata Donn.) had vegetated naturally making it a mixed stand. The understory was made up of a very dense salal (Gaultheria shallon Pursh) shrub. Soils were previously characterized as Humo-Ferric Podzols (Blevins et al., 2006). Generally, the organic soil horizons at this site were greater than 40 cm deep, thus meeting the criterion for a deep Hemic Folisol (that is, an upland organic soil) (Soil Classification Working Group 1998). Average January temperatures in the nearby town of Port Hardy were 3 \u00C2\u00B0C with August temperatures reaching 15 \u00C2\u00B0C. Yearly precipitation was estimated to be nearly 1900 mm (Weather Network B). The third site, a coastal Douglas-fir forest, was located 20 km north of Nanaimo British Columbia on southwestern Vancouver Island (49 o 9\u00E2\u0080\u0099N 123o 55'W) and managed by Island Timberlands LP. The site appeared to have been burnt following clearcut harvesting and was re-planted in 1980. The site was close to a boundary between the Coastal Douglas-Fir and Coastal Western Hemlock zones, but was considerably drier and slightly warmer than the western hemlock site. The nearby city of Nanaimo had an average January temperature of 2 \u00C2\u00B0C and average August temperature of 18 \u00C2\u00B0C and on average received 1145 mm precipitation per year (Weather Network C). The site had a 27 very sparse understory and the soils appeared to belong to the Orthic Sombric Brunisol subgroup. Organic horizon depth varied between 1 and 3 cm at this site. 3.2 Site Fertilization Unfertilized forest bordering the long-term fertilization trials were used to study the immediate effects of fertilization on N2O emissions and nitrifiers. At each site, plots with rope borders were established measuring 0.058 hectares (western hemlock), 0.164 hectares (lodgepole pine) and 0.01 hectares (coastal Douglas\u00E2\u0080\u0093fir). At each of the forest sites, three sets of 5 plots were randomly assigned as (1) control plots that received no fertilizer, (2) N plots that received 11.4 g urea equivalent to 200 kg nitrogen (N) ha -1 and (3) complete plots that received N equivalent to 200 kg and 100 kg phosphorus (P), 100 kg potassium (K), 50 kg sulfur (S), 25 kg magnesium (Mg), and 1.5 kg boron (B) ha -1 . Nitrogen was mostly supplied in the form of urea, in the complete treatment; however 24 % of the total N was added as mono-ammonium phosphate (total N 11%, available phosphate 52%) which also served as a source of phosphorus. Potassium was delivered as potassium chloride and sulphate potash magnesia, which was also the source of sulfur and magnesium. Boron was added in the form of a granular borate (complete fertilizer mix was based on Brockley, 2007). Fertilizer was hand-spread evenly across each plot on September 15, 2005 in the lodgepole pine site, February 28, 2006 in the western hemlock site, and March 29, 2006 in the coastal Douglas-fir site, corresponding in rate with typical operational fertilization (R. Brockley, personal communication). The coastal Douglas-fir site only received the complete fertilizer treatment. 28 3.3 N2O Gas Flux Measurements PVC flux collars, 10 cm in diameter, were inserted approximately 3 cm into the soil to enable measurement of soil gas fluxes. On each sampling day, PVC flux sampling chambers approximately 25 cm in height with closed-cell foam at bottoms and silicone- filled rubber septa were fitted on to collars. Stopcocks were closed to prevent pressure buildup during routine installation. Then, 12 ml of headspace air was removed with a 20- ml syringe and 25-gauge needle and transferred to a pre-evacuated Exetainer (Labco, High Wycombe, Buckinghamshire, UK) vial at 0, 15, 30, 45, and 60 minutes following chamber placement. Gas samples were taken immediately before fertilizer was applied (day 0), and on days 1, 2, 4, 7, 21, and 210 following fertilization in the lodgepole pine site, on days 1, 3, 7, 21, and 50 following fertilization in the western hemlock site, and on days 1, 3, 7, 23, and 60 following fertilization in the coastal Douglas-fir site. Air temperature and soil temperature 5 and 10 cm below the surface within 10 cm of each collar were also measured at each sampling time. 3.4 N2O Gas Analysis Gas was analysed at the University of Victoria usually within 2-3 days and always within 1 week of sampling, on Varian 3800 gas chromatographs (Palo Alto, CA, USA) equipped with a packed column and flame ionization and an electron capture detector for N2O. Injected gas volumes were 1 ml for N2O. Gas concentrations were calculated from integrated areas on chromatograms using regressions calculated from three standard concentrations of N2O (0.3, 1.01 and 10.0 ppm). 29 The masses of N2O in flux chambers at each sampling time were calculated using the ideal gas law (number of moles of gas= pV/RT, where p and T are absolute pressure and temperature, V is the gas volume in the chamber, and R is the ideal gas constant or 0.08205746 L\u00C2\u00B7atm\u00C2\u00B7K \u00E2\u0088\u00921 \u00C2\u00B7mol \u00E2\u0088\u00921 ) and molecular weight of each gas using recorded temperature expressed in \u00C2\u00B0K and assuming 1 atmosphere of pressure. Gas fluxes were calculated as the linear slope of increasing or decreasing mass of each gas over time divided by the area encircled by the flux collar. Each linear regression was tested for statistical significance and a single datum point was removed if this reduced any P value from >0.05 to \u00E2\u0089\u00A40.05. This was occasionally necessary for N2O flux calculations. In cases where removal of multiple different single points resulted in a subsequently significant linear regression, the point resulting in the largest correlation coefficient was removed. When removal of a single datum would not reduce P values to \u00E2\u0089\u00A40.05, values were removed from further analyses except when slopes were \u00E2\u0089\u00A5 -0.1 and \u00E2\u0089\u00A4 0.1, in which case a flux rate of zero was assigned. This range of slope was chosen based on repeated N2O measurements in a sealed chamber (not over soil) on the GC over 1 h, ordered from both largest to smallest and smallest to largest, which in principle could produce these flux rates. Although a relationship with a slope of zero does not have statistical significance, lack of flux is meaningful in this study. This was done occasionally for N2O. Effects of fertilization on gas fluxes (all sites) and nutrients at each depth (lodgepole pine site) over time, including fertilization \u00EF\u0082\u00B4 time interactions, were evaluated with repeated measures analyses of variance (ANOVA) where the repeated measurement of gas flux rate or nutrient concentration was the within-subjects factor. Single t-tests were used to determine if N2O fluxes in an individual treatment at one time were significantly different 30 from zero. Effects of fertilization treatment and site (or species) on nutrients and microbial biomass on the final measurement date were tested using ANOVA with Tukey post-hoc tests. Pearson\u00E2\u0080\u0099s correlation coefficients between soil, nutrient and microbial biomass factors and flux rates were determined among all sampling times when edaphic properties were measured for control plots in the lodgepole pine site alone and among all sites. In cases where Pearson correlations were significant, scatterplots with linear regressions were made and R 2 values calculated using Microsoft Excel 2000 (Redman, WA, USA). In any dataset where distribution of resulting residuals was not normal (that is, when skewness/standard error of skewness or kurtosis/standard error of kurtosis were not sufficiently near zero), data were log-transformed and reanalyzed, however for ease of interpretation, means and standard deviations of non-transformed data are presented. Statistically significant differences were assumed at P \u00E2\u0089\u00A4 0.05. 3.5 Soil Sampling for Nutrient Dynamics Soil was sampled from each plot on days 1, 4, 7, 21, and 210 in the lodgepole pine site, on days 1, 7, 23, and 50 in western hemlock, and on days 1, 7, 23 and 60 following fertilization in coastal Douglas-fir, using a 7-cm-diameter stainless-steel corer. Each soil core was divided into 2 depth segments, 0-5 cm and 5-10 cm beneath the forest floor surface, placed into plastic bags and kept on ice in a cooler. 3.6 Soil Nutrient Analysis For nutrient analysis, soil samples were thawed for 3 hr at 20 \u00EF\u0082\u00B0C, dried and weighed for bulk density measurements, removed from bags, sieved to 8 mm and then returned to the 31 bag where they were thoroughly mixed before analysis. A small portion (5 grams) of each soil was placed in a beaker, weighed, dried at 105 \u00EF\u0082\u00B0C, and reweighed to measure moisture content. Extractable organic and microbial C, N, and P and inorganic N and P were determined using chloroform (CHCl3) fumigation-extraction and alkaline persulfate oxidation techniques modified from Voroney et al., (1993) and Williams et al., (1995) following Basiliko et al., (2007) and Bengtson et al., (2007). From each soil sample, two 20 g sub-samples were removed from bags. One sample was fumigated in a vacuum desiccator for 24 h in the dark with ethanol free CHCl3 and subsequently evacuated 7 times for 10 minutes to remove residual CHCl3 and the other was set aside at 4\u00C2\u00B0C for the same time period. Following fumigation, both control and fumigated samples were sealed in containers with 70 ml of 0.5 M potassium sulfate and shaken at 200 RPM for 1 hr. Extracts were filtered to 0.45 \u00CE\u00BCm and analyzed for total organic C, total N as nitrate (NO3) after oxidation with alkaline potassium persulfate (K2SO4) in an autoclave, and inorganic N species were measured as NO3 - and NH4 + in the control extract only. The values for NO3 - -N also include nitrite (NO2 - ). Microbial biomass C, N, and P were calculated by subtracting the non-fumigated extractable DOC or total N or P from the fumigation-extraction DOC or total N or P respectively. This analysis yielded the following results: 1. The difference between fumigated and un-fumigated DOC indicated the microbial biomass carbon. It is known that this procedure does not recover all microbial biomass; however approximate factors to correct for the efficiency of extraction in organic soils have been previously calculated (Sparling et al., 1990). 32 2. The difference between total N in un-fumigated and fumigated sample extracts indicated microbial N. 3. Total N minus inorganic N yielded dissolved organic N. The advantage of this procedure is that it is quick and simple, and even under alkaline conditions, persulphate oxidizes organic N and NH4 to NO3. This is preferable to Kjeldahl digestion, which does not give quantitative recovery of NO3-N solution without pre-treatment to reduce NO3-N to ammonium-N (Pruden et al., 1986). The Kjeldahl digests must be neutralized or diluted for sulphuric acid prior to N analysis by continuous techniques and steam distillation which is slow (Williams et al., 1995). One disadvantage of the method is that very high Total Organic Carbon (TOC) in the extracts (> 330 mg C/m) can cause underestimation of total N in the sample. This can be corrected by diluting the extracts prior to oxidation. Another disadvantage is that it tells us little about the microbial community structure, structure or function. Soil nutrients and microbial biomass concentrations are expressed per g of dry soil. Increases in pools of N at each depth were calculated as the difference between average values in treatments minus controls as a percentage of total N added using calculated dry bulk densities for volumetric conversions. This additional N was termed \u00E2\u0080\u0095recovered\u00E2\u0080\u0096. Statistical analyses comparing the three fertilizer treatments were conducted using Systat 10 (SPSS Inc. Chicago, IL, USA). 3.7 Soil Sampling for DNA Extractions A total of 437 soil samples were used for DNA extractions. These were spread across sampling dates and all forest types (lodgepole pine, western hemlock and coastal 33 Douglas-fir) at both depths (organic (0-5 cm) and mineral (5-10 cm)). There were five replicates of each of the three treatments (control (no fertilization), N+B and complete) in lodgepole pine and western hemlock and five replicates for the two treatments (control (no fertilization) and complete) in coastal Douglas-fir. Of the 437 samples, 80 samples were selected to be further studied. These were all from the organic soil layer and included all fertilizer treatments. The sampling dates selected were day 7 and the final sampling dates (day 50 for western hemlock, day 60 for coastal Douglas-fir and day 210 for lodgepole pine). The objective was to capture microbial diversity at the start and at the end of the study period. 3.8 DNA Extractions The DNA was extracted using a PowerSoil DNA Isolation kit (MO BIO laboratories Inc., Carlsbad, California, USA). Following soil thawing at room temperature, 0.25 g of soil was used for the DNA extraction. The extracted DNA (100 \u00CE\u00BCl) was stored at - 20 o C to avoid any degradation. 3.9 PCR Amplification of DNA Samples A Polymerase Chain Reaction (PCR) and Denaturing Gradient Gel Electrophoresis (DGGE) approach was selected for characterizing the microbial diversity in this study. A portion of the 16S rRNA gene of the \u00CE\u00B2-Proteobacteria (common nitrifying bacteria) was amplified using a nested PCR approach based on Tourna et al., (2008) (Table 1). 34 Table 1. Forward and Reverse primers used in this study PCR 1 CTOf1 5\u00E2\u0080\u0099- AGA AAA GCA GGG GAT CG - 3\u00E2\u0080\u0099 CTOf2 5\u00E2\u0080\u0099- AGG AAA GTA GGG GAT CG - 3\u00E2\u0080\u0099 CTOf3 5\u00E2\u0080\u0099- AGG AAA GCA GGG GAT CG - 3\u00E2\u0080\u0099 CTOr1 5\u00E2\u0080\u0099- TAG CCT TGT AGT TTC AAA CGC - 3\u00E2\u0080\u0099 CTOr2 5\u00E2\u0080\u0099- TAG CTT TGT AGT TTC AAA CGC - 3\u00E2\u0080\u0099 PCR 2 Muyzer fGC 5\u00E2\u0080\u0099- TAC GGG AGG CAG CAG -3\u00E2\u0080\u0099 Muyzer r 5\u00E2\u0080\u0099- ATT ACC GCG GCT GCT GG -3\u00E2\u0080\u0099 A 42-base-pair GC clamp (CGC CCG CCG CGC GCG GCG GGC GGG GCG GGG GCA CGG GGG GCC) was added at the 5\u00E2\u0080\u0099- end of the Muyzer fGC forward primer to avoid total denaturing of the DNA during the electrophoresis process. A nested PCR approach uses two pairs of PCR primers, the first pair amplifying a wider length of the DNA molecule for a PCR product, and the second set of primers binds within the first PCR product to deliver a smaller, sharper PCR product. The logic behind such an approach is that if by mistake a slightly different area of the DNA was amplified, chances are very small that it would be again amplified by the second primer pair. DNA extractions and amplifications from all the samples were hampered by inhibition by humic acids, which caused difficulty in getting PCR products. To overcome the problem, two PCR approaches were utilized which differed in the sources from which the chemicals were obtained and also the addition of BSA in the second PCR approach. Furthermore, a strategy was implemented to process the DNA using different dilutions. One \u00CE\u00BCl of undiluted DNA was used for the first PCR in both the approaches. The PCR product from first PCR was then subjected to different dilutions, i.e. from an undiluted PCR 1 product to a 1/10 diluted PCR 1 product. Then all these dilutions were subjected to 35 the second PCR. The products of the second PCR were then visualized on a 1% agarose gel to determine the 16S rDNA products. Out of 80 samples selected for DGGE, not all gave a positive result with the primer set specific for the 16S rRNA gene of the \u00CE\u00B2- subclass of the Proteobacteria. Sixty three samples actually showed bands when visualized on an agarose gel, representing at least three replicates of each treatment for each forest type at each sampling time, and were further used in the DGGE study. The initial amplification was done using a composite forward primer (made up of 3 primers namely CTOf1,CTOf2 and CTOf3) and a composite reverse primer (made up of 2 primers namely CTOr1 and CTOr2) as used by Kowalchuk et al (1997). For the set of forward primers, a 100x solution was made for all the individual primers. Then 100 \u00CE\u00BCl from the three solutions was taken and pooled. A 10x stock solution was prepared by taking 10 \u00CE\u00BCl from the pooled solution and adding 90 \u00CE\u00BCl of distilled water. The same procedure was used for the reverse primers. The reaction mixture volume for the first PCR was 20 \u00CE\u00BCl which contained DNA (2.0 \u00CE\u00BCl), 10x ThermoPol buffer (New England Biolabs, Ipswich,MA,USA) (2.0 \u00CE\u00BCl), 2mM dNTP (New England Biolabs, Ipswich,MA,USA) (2.5 \u00CE\u00BCl), 50 mM MgCl2 (Biotools B&M S.A. made in Spain) (0.6 \u00CE\u00BCl), 100x (10mg/ml) Bovine Serum Albumin (BSA) (New England Biolabs, Ipswich,MA,USA ) (0.4 \u00CE\u00BCl), 10 \u00CE\u00BCM forward and reverse primers (0.4 \u00CE\u00BCl each), Taq polymerase (5U/ \u00CE\u00BCl) (Bioline,Taunton,MA,USA) (0.064 \u00CE\u00BCl) and PCR grade water (11.636 \u00CE\u00BCl). The second PCR reaction was done using the primers Muyzer fGC and Muyzer r as reported by Muyzer et al (1993). For both the primers, a 10x stock solution was prepared by taking 10 \u00CE\u00BCl of the 100x solution and adding 90 \u00CE\u00BCl of distilled water. For the second 36 PCR, 10x TP Buffer (New England Biolabs, Ipswich, MA, USA) (5.00 \u00CE\u00BCl), dNTP containing 10mM of each dNTP (New England Biolabs, Ipswich,MA,USA) (6.25 \u00CE\u00BCl), MgCl2 (50 mM) (Biotools B&M S.A. made in Spain) (1.50 \u00CE\u00BCl), forward and reverse primers (1.00 ul), TAQ polymerase (Bioline, Taunton, MA, USA) (0.16 \u00CE\u00BCl), PCR 1 product (1.00 \u00CE\u00BCl) and PCR grade water (34.09 \u00CE\u00BCl) was used to produce a final volume of 50 \u00CE\u00BCl. For a few of the samples, a different PCR amplification approach was needed to obtain products. These samples were Day 7 lodgepole pine complete, Day 7 lodgepole pine N+B, and Day 50 western hemlock complete (1 of 5 samples). The procedure for this second PCR approach was as follows: The volume for the first PCR reaction was 20 \u00CE\u00BCl which contained DNA (2.0 \u00CE\u00BCl), 10x NH4 buffer (Bioline,Taunton,MA,USA) (2.0 \u00CE\u00BCl), 2 mM dNTP (New England Biolabs, Ipswich,MA,USA) containing 10 mM of each dNTP (2.5 \u00CE\u00BCl), 50 mM MgCl2 (Bioline,Taunton,MA,USA) (0.6 \u00CE\u00BCl), 100x (20 mg/ ml) Bovine Serum Albumin (BSA) (Roche Applied Science, Laval, Canada) (0.2 \u00CE\u00BCl), 10 \u00CE\u00BCM forward and reverse primers (0.4 \u00CE\u00BCl each), Taq polymerase (5U/ul) (Bioline,Taunton,MA,USA) (0.064 \u00CE\u00BCl) and PCR-grade water (11.836 \u00CE\u00BCl). For the second PCR, 10x NH4 Buffer (Bioline, Taunton, MA, USA) (5.00 \u00CE\u00BCl), dNTP containing 10 Mm of each dNTP (New England Biolabs, Ipswich,MA,USA) (6.25 \u00CE\u00BCl), MgCl2 (50 mM) (Bioline, Taunton, MA, USA) (1.50 \u00CE\u00BCl), forward and reverse primers (1.00 \u00CE\u00BCl), TAQ polymerase (Bioline, Taunton, MA, USA) (0.16 \u00CE\u00BCl), PCR 1 product (1.00 \u00CE\u00BCl), 100x (20 mg/ ml) Bovine Serum Albumin (BSA) (Roche Applied Science, Laval, Canada) (0.8 \u00CE\u00BCl) and PCR-grade water (33.29 \u00CE\u00BCl) was used to produce a final volume of 50 \u00CE\u00BCl. 37 3.10 PCR Conditions PCR conditions used in this experiment were based on Tourna et al., (2008): 95 o C for 5 minutes; followed by 10 cycles of 94 o C for 30 seconds, 55 o C for 30 seconds, 72 o C for 1 minute; followed by 25 cycles of 92 o C for 30 seconds, 55 o C for 30 seconds, 72 o C for 1 minute; followed by 72 o C at 10 minutes. The same protocol was followed for both PCR approaches. 3.11 DGGE Conditions DGGE was performed by using an 8% (w/v) acrylamide gel with a 30 - 70% denaturant gradient and run in a 1\u00C3\u0097 TAE (Tris\u00E2\u0080\u0093acetate\u00E2\u0080\u0093EDTA) buffer for 16 h under conditions of 60 \u00C2\u00B0C and 75 V. DGGE gels were stained with SYBR Green I nucleic acid gel stain (Molecular Probes, Eugene, OR) at a 1:10,000 dilution for 30 minutes and were scanned with a Typhoon 9400 imager (Amersham Biosciences, Piscataway, NJ). 3.12 Statistical Analysis DGGE fingerprints were compared using Gel Compar II (Applied Maths, Belgium). Gel images were normalized using standards run in the outside and middle lanes. Fingerprint patterns were analyzed using Pearson's correlations, providing pairwise percent similarity values for all fingerprint densitometric curves. An unweighted pair group method with arithmetic mean (UPGMA) dendrogram was created from this similarity matrix. The data matrix provided by the Gel Compar was used to run the Nonmetric Multidimensional Scaling (NMS), which is useful when the underlying relationships between objects are not easily observable, but a distance matrix is available. With 38 nonmetric scaling, all that is required is the data distances. Multi-Response Permutation Procedure (MRPP) was also done to test whether there were significant differences between two groups of sampling units. The objective of using a Principal Component Analysis (PCA) is to describe the variation in the data set so that only a few of the indices account for most of the variability thus reducing the number of variables. All of the above were done using the statistical software PC-ORD for Windows (Version 5.14), MjM software, Gleneden Beach, Oregon, U.S.A. 39 4. RESULTS 4.1 Soil Temperatures and Moisture Content Average soil temperatures for the sampling dates 5 cm beneath the surface across flux measurement times were 6.6 \u00C2\u00B0C at the lodgepole pine, 4.5 \u00C2\u00B0C at the western hemlock, and 7.8 \u00C2\u00B0C at the coastal Douglas-fir sites, while average moisture contents in the 0-5cm soil horizons were 80%, 409%, and 40% respectively on a dry soil basis (Figure 5). 40 Figure 5. Gravimetric soil moisture and air and soil temperature at each site (across all treatment plots) and gas flux sampling date. Values are means and error bars are standard deviations of 15 measurements. 41 4.2 N2O Gas Flux The range of N2O fluxes at individual collars for all the treatments across all sites ranged from \u00E2\u0080\u009312.4 to 10.8 \u00CE\u00BCg N2O m -2 hr -1 . Average rates across all treatments and times were - 0.05, - 0.31, and 0.02 \u00CE\u00BCg N2O m -2 hr -1 at the lodgepole pine, western hemlock, and coastal Douglas-fir sites. Although lodgepole pine showed a significant fertilization treatment \u00C3\u0097 time interaction (Figure 6 A) and there was a significant fertilization treatment effect in western hemlock, as indicated by repeated measures ANOVA (Figure 6 B), only the complete treatment plots on day 60 following fertilization at the coastal Douglas-fir site showed an average flux that, among replicates, was significantly different from zero (Figure 6 C, circled) with an efflux rate of 1.5 \u00CE\u00BCg N2O m -2 hr -1 . On the whole, there was large temporal and spatial variability in flux rates resulting in few or no apparent patterns in fertilization effects, leading to no net emissions across sites or treatments. A. lodgepole pine -5 0 5 lodgepole pine (Ref. Basiliko et al. 2009) control complete N So il N 2O fl ux (u g N 2O m -2 h- 1 ) Day 1 Day 2 Day 4 Day 21 Day 210 Treatment: p=0.06, time:p=0.76, treatment x time: p=0.03 Day 7 42 B. western hemlock -5 0 5 western hemlock (Ref. Basiliko et al. 2009) control complete N So il N 2O fl ux (u g N 2O m -2 h- 1 ) Day 1 Day 3 Day 7 Day 21 Day 50 Treatment: p=0.02, time:p=0.38, treatment x time: p=0.11 C. Douglas-fir -5 0 5 Douglas-fir flux Treatment: p=0.21, time:p=0.42, treatment x time: p=0.68 Day 1 Day 3 Day 7 Day 23 Day 60 control complete (Ref. Basiliko et al. 2009) So il N 2O f lu x (u g N 2O m -2 h- 1 ) Figure 6. Soil N2O fluxes (ug N2O m -2 hr -1 ) at the lodgepole pine, western hemlock and Douglas-fir sites following fertilization. For lodgepole pine, the first measurement was done immediately before fertilization. For the rest, it was a day after fertilization. 43 4.3 Soil NH4 + and NO3 - Chemistry Soil NH4 + concentration increased immediately following fertilization in the 5-cm surface horizon in both the N and complete plots at the lodgepole pine site which gradually decreased over time. NH4 + concentration was about 20 times less in the lower soil horizon than in the surface horizon (Figure 7 A & B). In the surface soil horizon of all sites, the NH 4 + concentrations were significantly elevated in N and complete fertilized plots as compared to the control plots, and represented the largest concentrations of N species measured by the time the study ended (Table 2). NH 4 + concentrations in complete plot were significantly larger than controls in the lower horizon at the coastal Douglas-fir site, with no significantly larger values observed in the same treatments at the other two sites (Table 2). The N species which dominated additional N was always NH 4 + (Table 3). Despite the fact that the largest NH 4 + concentrations were measured in the fertilized treatments at the western hemlock site (Table 2), there was a lower calculated recovery of added N owing to low bulk density of the organic soil relative to the lodgepole pine and coastal Douglas-fir sites (Table 3). 44 0 1200 2400 A - NH4 + (0-5 cm)N Complete Control Day 2 Day 4 Day 7 Day 21 Day 210 Treatment P=0.00, time P=0.00, treatment x time P=0.03 0 60 120 B - NH4 + (5-10 cm)N Complete Control Day 2 Day 4 Day 7 Day 21 Day 210 treatment P=0.01, time P=0.65, treatment x time P=0.21 0 4 8 C \u00E2\u0080\u0093 NO2 - and NO3 - (0-5 cm)N Complete Control Day 2 Day 4 Day 7 Day 21 Day 210 treatment P=0.00, time P=0.01, treatment x time P=0.00 0 0.5 1.0 D \u00E2\u0080\u0093 NO2 - and NO3 - (5-10 cm)N Complete Control Day 2 Day 4 Day 7 Day 21 Day 210 treatment P=0.00, time P=0.00, treatment x time P=0.01 Figure 7. Extractable NH4 + -N, NO2 - + NO3 - -N in 0-5 to 5-10 cm soil depth segments following fertilization at the lodgepole pine site. NO3 - concentration gradually increased in the surface soil horizon of the complete plots until day 7 following fertilization and subsequently decreased. Additional NO3 - was found in the soil horizon of N plots compared to the control plots only on day 210 following fertilization (Figure 7 C). Concentrations in the lower horizon were higher in N and complete plots (< 0.5 \u00CE\u00BCg N g -1 soil) as compared to the control plots, except on day 210 (Figure 7 D). In the lodgepole pine site, over 90% of the amount of added N was 45 \u00E2\u0080\u0095recovered\u00E2\u0080\u0096 in measured pools, while the other two sites had considerably lower recovery at the end of the study period. Table 2. Extractable inorganic and organic N, microbial biomass N and pH in 0-5 and 5-10 cm soil depths from lodgepole pine, western hemlock and coastal Douglas-fir. Values are averages of samples collected 210,50 and 60 days respectively. Depth (cm) lodgepole pine western hemlock Douglas-fir control N complete control N complete control complete NH4 + - N (\u00CE\u00BCg g-1 soil) 0-5 cm 13.9a 488b 127b 6.33a 903b 728b 28.2a 384b (9.0) (402) (61.8) (5.11) (599) (1185) (26.7) (235) 5-10 cm 2.87a 39.5a 16.9a 41.9a 108a 222a 8.20a 71.1b (1.51) (43.3) (6.86) (38.1) (183) (340) (2.69) (56.7) NO3 - - N (\u00CE\u00BCg g-1 soil) 0-5 cm 0.79a 3.34a 0.66a 2.02a 3.37a 3.10a 1.02a 3.64a (0.53) (2.72) (0.14) (1.30) (1.69) (1.66) (0.59) (4.11) 5-10 cm 0.57a 0.55a 0.46a 1.63a 5.00a 1.47a 0.49a 0.74a (0.11) (0.08) (0.03) (0.50) (7.52) (0.41) (0.05) (0.52) Organic - N (\u00CE\u00BCg g-1 soil) 0-5 cm 21.2a 52.9a 21.6a 114a 428a 284a 47.5a 104.7a (3.72) (77.2) (5.06) (67.1) (478) (118) (33.7) (153) 5-10 cm 16.9a 35.2b 19.8 a,b 74.3a 147 a,b 279b 24.5a 55.0a (3.10) (12.1) (8.96) (16.0) (69.0) (122) (7.10) (41.7) Microbial - N (\u00CE\u00BCg g-1 soil) 0-5 cm 35.9a 266b 52.6 a,b 319a 536a 309a 61.6a 51.7a (21.3) (203) (42.2) (64.4) (237) (151) (35.8) (39.8) 5-10 cm 8.93a 8.95a 8.11a 161a 96.9a 79.2a 5.49a 10.2a (4.82) (3.37) (4.42) (49.6) (102) (70.3) (3.75) (8.88) pH (in K2SO4) 0-5 cm 3.8 a 4.3a 6.6b 3.3a 3.8a 6.1b 5.1a 6.6b (0.5) (0.4) (0.6) (0.2) (0.6) (0.5) (0.5) (1.3) 5-10 cm 4.3a 4.4a 6.7b 3.1a 3.4a 6.9b 4.9a 6.1b (0.6) (0.5) (0.4) (0.2) (0.2) (0.3) (0.7) (0.9) 46 Table 3. Percent of total added N recovered in all measured pools in 0-5 and 5-10 cm soil depth segments in N and complete fertilized plots in lodgepole pine, western hemlock and coastal Douglas- fir site sampled 210, 50 and 60 days respectively. Depth (cm) lodgepole pine western hemlock Douglas-fir NH4 + - N 0-5 cm 52.2 17.9 26.4 5-10 cm 7.8 2.0 9.9 NO3 - - N 0-5 cm 0.3 0.0 0.0 5-10 cm 0.3 0.1 0.0 Extractable organic N 0-5 cm 3.5 6.3 -0.4 5-10 cm 3.9 2.2 0.8 Microbial N 0-5 cm 25.4 4.3 -1.4 5-10 cm 0.0 -1.9 1.1 Total N 93.4% 30.9% 36.4% 4.4 Nitrifier Communities In the western hemlock stand, 7 days after fertilization, the DGGE fingerprints of the 16S rRNA revealed that soils receiving the N treatment had the most ammonia-oxidizing bacterial diversity followed by the control (unfertilized soils) and soils from the complete fertilizer treatment had least diversity ( Appendix 1). Nonmetric Multidimensional Scaling (NMS) of the samples was not successful due to weak structure of the data. This might be due to presence of outliers or the single variable having drastically greater weight than the other variables. Multi-Response Permutation 47 Procedure (MRPP) was not possible because two of the three treatments had only one representative. Fifty days following fertilization of the western hemlock stand, soil from the control (unfertilized) stands had the greatest AOB diversity and soils from the stands receiving the complete fertilizer treatment the least (Appendix 2). NMS analysis was not successful due to the stability criterion not being met. But the software recommended a 3-dimensional solution and then ran the best ordination with it (Figure 8). Figure 8. NMS ordination showing bacterial communities from the western hemlock stand 50 days after fertilization based on DGGE profiles, where treatment 1: complete, treatment 2: control, and treatment 3: N. MRPP analysis of the bands observed in the DGGE gel yielded a p value of 0.921, suggesting that there were no significant differences between the treatments. A graphical representation of the richness index of bands for the N and control treatments shows that there is not much difference between the two treatments and the single factor ANOVA also did not give a significant difference between the two treatments (Figure 9). S11 S12 S169 S170 S171 S172 S3 S4 S5 Axis 1 Treatment 1 2 3 Axis 2 48 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 N control A v e ra g e # o f b a n d s p e r g e l Figure 9. Comparison of richness index for N and control treatments for western hemlock 50 days after fertilization. In the lodgepole pine stands 7 days after fertilization, soils in the unfertilized stands had more nitrifier diversity, compared to soils in the stands receiving both the N and complete fertilizer treatments (Appendix 3). NMS analysis of the gel was not successful due to the stability criteria not being met, which was overcome by the PCORD software running the best possible ordination in 3-dimensions (Figure 10). MRPP analysis gave a p value of 0.421 suggesting no significant differences between the treatments. 49 Figure 10. NMS ordination showing bacterial communities from the lodgepole pine stand 7 days after fertilization based on DGGE profiles. The lower diversity of nitrifiers in the soils of both of the fertilized lodgepole pine stands, compared to the unfertilized stands remained 210 days following fertilization (Appendix 4). NMS analysis was not successful as the stability criterion was not met. However, the software did provide a 1-dimension solution and then ran the best ordination for the purpose of running the analysis (Figure 11). S201 S239 S241 S279 S280 S281 S282 Axis 1 Treatment complete control N Axis 2 50 Figure 11. NMS ordination showing bacterial communities from the lodgepole stand 210 days after fertilization based on DGGE profiles. The MRPP analysis gave a p value of 0.002, suggesting statistically significant differences between the bands. A comparison of the richness index of bands for all the three treatments 210 days after fertilization showed that there were no significant differences as was also suggested by the single factor ANOVA with a non significant p value (Figure 12). S211 S212 S219 S220 S221 S222 S229 S230 S232 S233 Axis 1 Treatment complete plete control N Axis 2 51 0 1 2 3 4 5 6 7 N control complete A v e ra g e # o f b a n d s p e r g e l Figure 12. Comparison of richness index for N, control and complete treatments for lodgepole pine 210 days after fertilization. In the coastal Douglas-fir stands 7 days following fertilization, soils from the unfertilized (control) treatment had a greater diversity of nitrifiers than in the complete treatment (Appendix 5). NMS analysis was not successful due to the stability criterion not being met. MRPP was not possible due to the small number of samples involved. 52 There were few differences between the two treatments in richness index as is evident from the graph below (Figure 13). Single factor ANOVA gave no significant results. 0 0.2 0.4 0.6 0.8 1 1.2 1.4 control complete A v e ra g e # o f b a n d s p e r g e l Figure 13. Richness index for control and complete fertilizer treatments for Douglas-fir 7 days after fertilization. However, 60 days after fertilization, although the total band numbers were much less than at day 7, the soils in the coastal Douglas-fir stands receiving complete fertilizer still had a greater number of bands than the unfertilized (control) stands at day 7, unfortunately no fingerprints were obtained from soil samples taken from the unfertilized (control) treatment 60 days after fertilization (Appendix 6). If a comparison was made between the richness indexes for the complete treatments from both day 7 and day 60, they do show a significant difference (Figure 14) as is also evident from the single factor ANOVA which gave a p-value of 0.002 (Table 4). 53 -2 0 2 4 6 8 10 12 14 16 complete(7) complete(60) A v e ra g e # o f b a n d s p e r g e l Figure 14. Richness index for complete fertilizer treatment for Douglas-fir 7 and 60 days after fertilization. Summary Groups Count Sum Average Variance Column1 2 2 1 0 Column2 5 61 12.2 6.7 ANOVA Source of Variation SS df MS F p-value F crit Between Groups 179.2 1 179.2 33.43 0.002 6.61 Within Groups 26.8 5 5.36 Total 206 6 Table 4. A single-factor ANOVA for richness indices of complete treatment (day 7 and day 60) in Douglas-fir stand. 54 NMS analysis for the samples was not successful due to the weak structure of the data. MRPP analysis was not possible due to the small number of samples used. A cluster analysis (Figure 15) was conducted on the phylogenetic data from all the samples that were used in the gels. These were DNA samples from the organic layer soil. Figure 15. Cluster analysis of composite matrix, where pine day 7; hemlock day 7; D.fir day 7; and pine day 210; hemlock day 50; D.fir day 60. There was a distinct separation of the forest stands between the different sampling times. The samples from the same forest type were clustered in the same general space i.e. pine high on axis 2 and hemlock low on axis 2. Time was the discriminating factor on axis 1, the day 7 samples for all the forest stands have a low score on axis 1, with the only outlier being a sample (# 391) from the coastal Douglas-fir stand treated with complete fertilizer. S401 S390 S391 S201 S283 S282 S200 S241 S203 S281 S372 S374 S373 S371 S370 S21 S91 S41 S93 S4 S170 S12 S172 S169 S5 S171 S1 S3 S222 S229 S223 S219 S221 S220 S232 S230 S211 S212 S233 Axis 1 Axis 2 55 The individual graphs did not show treatment effects clearly, however, on composite analysis for the treatments 1 (complete) versus 2 (control) and 1 versus 3 (N + B) there were significant differences. Microbial communities from the different treatments in the Douglas-fir stand on day 7 after fertilization and from the different treatments in the pine stands on day 210 after fertilization were discriminated. Running the MRPP with \u00E2\u0080\u0095Treatment\u00E2\u0080\u0096 as the defining factor gave a p value of 0.056. Taking \u00E2\u0080\u0095Site\u00E2\u0080\u0096 as the defining factor, MRPP gave a p value of 0.000 which is very highly significant. NMS analysis did not run through because the stability criterion was not met for the data. Appendix 10 shows the PCA coordinates and axis for the composite matrix. This suggests that the forest stands had the most effect on the microbial community composition associated with them. 56 All the samples from all the DGGE gels were then combined into a single composite matrix as follows (Figure 16): 39 38 37 36 35 34 33 32 31 30 29 28 27 26 25 24 23 22 21 20 19 18 17 16 15 14 13 12 11 10 9 8 7 6 5 4 3 2 1 Figure 16. Dendrogram illustrating cluster analysis results for DGGE profiles of bacterial communities from Douglas-fir, lodgepole pine and western hemlock stands from all sampling dates, with the following description. 1 Fc7-1 D.Fir control Day7 21 H+50-1 Hemlock complete day 50 2 F+7-1 D.Fir complete day 7 22 Hc50-1 Hemlock control day 50 3 F+7-2 D.Fir complete day 7 23 Hn+b50-2 Hemlock N+B day 50 4 Pn+b7-1 Pine N+B day 7 24 Hn+b50-3 Hemlock N+B day 50 5 Pc7-1 Pine control day 7 25 Hn+b50-4 Hemlock N+B day 50 6 Pn+b7-2 Pine N+B day 7 26 Hc50-2 Hemlock control day 50 7 Pc7-2 Pine control day 7 27 Hc50-3 Hemlock control day 50 8 P+7-1 Pine complete day 7 28 Hc50-4 Hemlock control day 50 9 Pn+b7-3 Pine N+B day 7 29 P+210-1 Pine complete day 210 10 Pc7-3 Pine control day 7 30 Pc210-1 Pine control day 210 11 F+60-1 D.Fir complete day 60 31 P+210-2 Pine complete day 210 12 F+60-2 D.Fir complete day 60 32 P+210-3 Pine complete day 210 13 F+60-3 D.Fir complete day 60 33 P+210-4 Pine complete day 210 14 F+60-4 D.Fir complete day 60 34 P+210-5 Pine complete day 210 15 F+60-5 D.Fir complete day 60 35 Pc210-2 Pine control day 210 16 Hn+b7-1 Hemlock N+B day 7 36 Pc210-3 Pine control day 210 17 Hc7-1 Hemlock control day 7 37 Pn+b210-1 Pine N+B day 210 18 H+7-1 Hemlock complete day 7 38 Pc210-4 Pine control day 210 19 Hc7-2 Hemlock control day 7 39 Pn+b210-2 Pine N+B day 210 20 Hn+b50-1 Hemlock N+B day 50 Distance (Objective Function) Information Remaining (%) 0100 2E+0075 4.1E+0050 6.1E+0025 8.1E+000 57 It is evident from the dendrogram that there are 5 major groups into which the samples have been divided. In the matrix showing samples and the bands showing within each sample (Appendix 10), all the bands found seem unique to each forest type and time as there was no observable similarity across forest type or time. It seems that the largest effect over time is with sites and the time since fertilization. It is important to note that more bands suggest greater evenness of the population, i.e. less dominance by one or a few phylotypes. Overall, these analyses show that for the lodgepole pine site, there was a consistency in the trend of Control plots having greater diversity among the three treatments. For western hemlock, the N treatment had more diversity at the start of the study period, whereas by the end of the study period, the Control treatment was showing more diversity. For the coastal Douglas-fir site, with only two treatments to compare, i.e., Control and Complete, there was more diversity among the samples from Control treatment at the start of the study period, while at the end of the study, complete treatment ended up being more diverse than the Control treatment. A summary of bands observed within each sample lane for each of the forest stands, i.e., western hemlock, lodgepole pine and coastal Douglas-fir can be found in Appendix 7, 8 and 9 respectively. 4.5 Limits of the Study These results should be judged according to the circumstances around the study. First of all, the ladder used in the DGGE gels does not appear to be consistent among the different gels. The fact that there seems to be different ammonia oxidizers in the samples 58 might be an artifact of the gel differences. The ladders did not give the same pattern in all of the gels. This made it difficult to compare band positions between the gels. The lack of consistency in the replications between the samples also accounted for some weakness of the results obtained. In order to be able to compare the treatments, it is preferable to have the same number of replicates between the treatments which was not the case. This would mean that we cannot assign the same weight to all the treatments. Limited sampling dates were also one of the areas which affected the study. A large pool of samples would have given more weightage to the results. 59 5. DISCUSSION 5.1 Greenhouse Gas Emission and Soil Nutrients Within the first days following fertilizer application, most urea was apparently mineralized to CO2 and NH4 + . Although this was only directly observed in the lodgepole pine and western hemlock sites, it is presumed to have occurred in the coastal Douglas-fir site between application and first measurement, as the urea pellets dissolved within the first few hours during a moderate rain shower, which did not occur at the lodgepole pine and western hemlock sites; the coastal Douglas-fir site was also warmer, potentially supporting faster urease activity (Tscherko et al., 2001). By the end of the study there may have been small traces of urea remaining in the lower soil horizon in the lodgepole pine and western hemlock site as extractable organic N and C were significantly elevated in the N-treated plots at these sites but not in the unfertilized controls. This was not observed in the coastal Douglas-fir site, and corroborates complete and rapid mineralization of urea. In laboratory incubations with coastal Douglas-fir soil from southern British Columbia, Aarnio et al., (1996) reported that urea additions were rapidly mineralized to NH4 + and large concentrations of this ion persisted over the 54-week study. The majority of the added N was detected in the organic horizon of the lodgepole pine site, with the next largest pool being the microbial biomass, indicating microbial immobilization of added N. By the time the study ended, there was near complete recovery of N in the measured pools overall. This was in contrast with the western hemlock and coastal Douglas-fir sites where only approximately 1/3 of the added N was recovered in measured pools and little to no additional N was detected in the microbial 60 biomass. This is probably because the western hemlock and coastal Douglas-fir sites were fertilized during their growing seasons, with presumably the vegetation assimilating additional N, in contrast to the lodgepole pine site, which was fertilized at the end of the growing season. Nitrogen uptake by the vegetation appears to be most likely sink for the added N. This is supported by a lack of evidence of leaching of added N, as only up to 12 % of the amount of added N was detected in the lower 5-10 cm soil horizon, little to no N2O efflux losses were detected, and little to no net nitrification that could have led to subsequent losses of NO and N2 were measured. It may have been possible for leaching to have occurred between fertilization and soil sampling, although this is not likely. Additional NO3 - , probably arising from nitrification, detected at the lodgepole pine site represented less than 0.5 % of added N. With the understanding that autotrophic nitrification is limited by acidic conditions (Prosser, 1989), net nitrification was not observed in the least acidic coastal Douglas-fir soil, and nitrification was not even stimulated by the complete fertilization treatment that raised soil pH and increased NH4 + concentrations. Because the temporal dynamics of nutrients were not measured at this site, we can only speculate about net transformations based on treatments compared to unfertilized controls over a 2-month period. At the lodgepole pine site, net nitrification was observed initially (albeit minor) following fertilization in the complete, but not in the N-fertilization treatment and was probably due to elevated pH. The coastal Douglas-fir site was the only location where a significant efflux of N2O was detected 60 days after fertilization. The presence of limited or no N2O efflux in unfertilized controls, and following fertilization both confirm and conflict, with other findings. Lack of N2O emissions may only apply to acidic, unpolluted (with regard to N 61 deposition) upland conifer forest soils fertilized once or infrequently with urea or NH4 + . In a study on N2O emissions from BC Douglas-fir soils incubated in vitro using 15 N-urea tracers, Pang and Cho (1984) reported negligible N2O emissions, however they observed that they could stimulate denitrification measured as 15 N2 and 15 N2O with Ca 15 NO3 additions, indicating that nitrification was an important step limiting N2O efflux. Ullah et al., (2008) were not able to stimulate N2O efflux in upland eastern Canadian boreal forest soils following NH4NO3 additions in laboratory incubations. Similarly, in a field study, Bowden et al., (2000) did not detect any N2O efflux following NH4NO3 fertilization in an eastern United States temperate hardwood forest. Also N addition to Finnish boreal forest soils did not lead to N2O efflux (Maljanen et al., 2006), probably due to rapid immobilization by plants and microorganisms. However, in the same study, lab incubations of the soil with N fertilizer additions resulted in significant N2O release. Sitaula et al. (2001) reported that fertilization with NH4NO3 increased N2O efflux by up to 8-fold in a Norwegian pine forest. Jassal et al. (2008) reported emissions of N2O accounting for 5% of the added urea-N following fertilization of a 58-year-old coastal Douglas-fir stand on Vancouver Island. The N2O emissions began one month after and peaked three months after fertilization, so in our study we may have missed the peak in N2O emissions. However, additional factors which have to be considered in comparison of our study and that of Jassal et al. (2008) is the different age of the coastal Douglas-fir stands in our study (26 years) and the Jassal et al. (2008) study (58 years) and the timing of fertilization. Our fertilizer was applied in late March, as compared to fertilizer addition in the Jassal et al. (2008) study in mid-April. Some European studies have reported simulated chronic atmospheric N deposition leading to increased N2O efflux, ranging 62 from 0.2% in well-drained Swedish forest sites (Klemedtsson et al., 1997) to 1.5 to 5 times faster in German sites receiving more atmospheric wet N deposition than a corresponding Irish site (Butterbach-Bahl et al., 1998). There were no apparent negative effects of fertilization on greenhouse gas emissions over the length of the study period. Over longer time periods, fertilization in ecosystems with high lignin-containing litters results in increased soil C and altered soil respiration (Johnson and Curtis, 2001) which could be due to decreased ectomycorrhizal fungal and rhizosphere activity, reduction in belowground to aboveground biomass allocation ratios, increased litter production and input to soil, and suppression of microbial enzymes (Agren et al., 2001; Magill and Aber, 1998; Hammel, 1997; Johnson, 1992). The time span of many of these potential effects would be longer than the time scale for the present study, although in an eastern United States temperate forest, N fertilization with NH4NO3 suppressed soil respiration over the scale of months (Bowden et al., 2000). Positive correlations, particularly observed between soil respiration and pH and temperature, have been routinely reported. Only the lodgepole pine site apparently displayed a correlation between extractable organic N and soil respiration. The same site also had the smallest concentrations of measured N species of the 3 sites, which perhaps points to N limitation of soil microbial or plant root activity. It had been reported earlier (Brumme et al., 1999) that while forest ecosystems may exhibit \u00E2\u0080\u0095background\u00E2\u0080\u0096 emissions of N2O, \u00E2\u0080\u0095event based\u00E2\u0080\u0096 emissions following rewetting and freezing and thawing can also represent large effluxes. Although any temperature or moisture linkages to N2O fluxes was not observed, this study only included 2 dates undergoing thawing in 2 sites, soil moisture did not vary a great deal in any sites over the 63 study period, and the only significant treatment effect on N2O efflux was observed on the warmest measurement day, but warm days overall were not well represented. It is not impossible then, that rapid, event-based, N2O efflux or that summer N2O efflux could occur in these sites and that efflux may have been greater in fertilized sites. So our experimental design with a very limited number of sampling dates and spanning different time periods for each site permitted the possibility that we did not measure some of the fertilization effects that occurred. 5.2 Ammonia-oxidizing Communities The plant-soil microbial community\u00E2\u0080\u0099s relationship is not straightforward, with the aboveground and belowground components of a terrestrial ecosystem being dependent on each other (Gomoryova et al., 2009). Studies show that different decomposer communities colonize residues and roots of different plant species (Wardle et al., (1999) and (2006), Miethling et al., (2000), Kowalchuk et al., (2002)). In forests, different tree species influence forest humus formation, nutrient content, base status, and mineralization rates of C, N and P, nitrification and denitrification differently (Binkley and Valentine (1991), Gower and Son (1992), Fyles and Cote (1994), Priha and Smolander (1999), Thomas and Prescott (2000)). Nugroho et al., (2005) reported that environmental factors like C/N ratio of the F layer and atmospheric N deposition affect the presence of ammonia-oxidizing bacteria (AOB), which may explain differences in N transformation rates between different forest soils. A number of studies have indicated the presence of ammonia-oxidizing bacteria in acidic forest soils (Laverman et al., (2001), Mintie et al., (2003), Compton et al., (2004), Nugroho et al., (2005) and (2006)). 64 The results of our study suggest that the fertilizer treatments had an effect on the bacterial (AOB) diversity within the different tree stands, at least in the short term, although the largest apparent difference in AOB community structure was between the different forest types. However, as was noted previously, these findings could be due to the differences between gels. Fertilization only resulted in minor nitrification at the lodgepole pine site, while in the coastal Douglas-fir and western hemlock sites, it was insignificant. However, nitrification rates were not indicative of denitrification rates. N2O efflux from the lodgepole site was insignificant. The only significant N2O flux event was actually 62 days following fertilization in the coastal Douglas-fir site. We can only deduce that these sites are harboring different microbial populations, including nitrifiers and denitrifiers (because of the differences in process rates), because we did not cut out bands from the DGGE gels and re-amplify them to determine the identity of the microbial populations from the three sites. That aspect should become the focus of future studies. Researchers have investigated the effect of forest fertilization on microbial community structure (e.g. Nohrstedt et al., (1989), Ohtonen et al., (1992), Forge and Simard (2001)), with the impact on shifts in microbial communities being the focus of a few of these studies. For example, Sun et al (2004) reported a sharp increase in bacterial ribotypes in a century-old manure treated soil compared to a control soil. Some studies have suggested that increases in bacterial diversity due to the fertilizer treatments (simple and amended) were due to the increase in bacterial richness (detected bands and observed OTU\u00E2\u0080\u0099s) and biodiversity (Ge et al., 2008), although such a trend in our study was not observed. Nitrogen fertilization of forests has been shown to have variable effects on soil microbial biomass in the short term (Prescott et al., (1992), Soderstrom et al., (1983), 65 Hart and Stark (1997)), but in the long term, often fertilization results in decreased microbial biomass and activity (Smolander et al., (1994), Perie and Munson (2000)). The nature of these shifts varies amongst ecosystems and over time, often in unpredictable ways (Frey et al., (2004), Fransson et al., (2000) and Aber and Magill (2004)). Such shifts in microbial community composition could potentially lead to unpredictable alterations in critical ecosystem processes (Schimel (1995), Balser et al., (2002)). Monitoring changes in the total microbial community can be one approach to study the effects of fertilization on soil microorganisms. Such studies have already been done in agricultural systems which looked at changes in total bacterial community composition in soil amended with N fertilizers (Peacock et al., (2001), Enwall et al., (2005)). Grassland ecosystems have also been studied to investigate the possible links between AOB composition, diversity and nitrification kinetics by Webster et al., (2005). Studies in agricultural ecosystems, using a PCR-DGGE approach and targeting 16S rRNA genes, have found that there are significant differences between fertilized and unfertilized treatments, with AOB generally more abundant in fertilized soils as compared to control soils (Innerebner et al., (2006), Nyberg et al., (2006), Enwall et al., (2007), Ge et al., (2008)). Ros et al., (2006) investigating the microbial community structure following long-term amendments of different composts on an agricultural soil, found bacterial diversity to be significantly higher in compost-treated soil compared to control soil at 0\u00E2\u0080\u009320 cm. The diversity of ammonia oxidizers in compost-treated soils, however, was reported to decrease with depth, which was not the case for the control soil. In another study by Cookson et al., (2006), the influence of season, agricultural management and soil 66 properties on gross N transformations and bacterial community structures was assessed. It was found that bacterial community structure was correlated to soil textural classes, gross N fluxes and C and N pools. In studies done on the effect of different fertilization regimes in forest ecosystems, again using PCR-DGGE analysis on 16S rRNA genes, Schmidt et al., (2007) found AOB to be a minor component of the total bacterial community, even at higher N-deposition levels. Laverman et al., (2005) found a highly diverse bacterial community in a pine- forest top soil (0-8 cm) where the number of strongly dominant species was very small with few nitrifiers. Agnelli et al., (2004) found more complex banding patterns in upper soil horizons than in the deeper horizons, while studying distribution of microbial communities in a forest soil profile. Backman et al., (2003) found a shift in bacterial population from one Nitrosospira cluster to another, when comparing limed vs. non- limed coniferous forest soils. High diversity of Nitrosospira-like sequences was found in the limed soil profiles, whereas no AOB-like sequences were detected in the control soil at any depth. Another liming study in two forest types done by Carnol et al., (2002) suggested the abundance of Nitrosomonas europaea-like sequences was independent of the soil horizon, tree type or the liming treatment, with Nitrosospira-like sequences in the minority. 5.3 General Limitations The DGGE is a powerful molecular fingerprinting tool of medium resolution used in achieving quick analysis of a large number of samples. But there are limitations to this technique. The extraction efficiency of the DNA is very important. Then, the method is 67 dependent on PCR amplification, which in itself has its limitations and is flawed due to a number of factors, thus adding bias. Also, there is the issue of gel to gel variation, dependent on how the gels are prepared. This can make the comparison between gels difficult. Also, there is limitation to the resolution of the method. It can assess sequences which are 0.1-1% more intense than the total intensity of the sample. Due to the presence of highly diverse soil microbial population, sometimes very complex fingerprint patterns are possible. This will give many bands with equal intensity, thus sometimes masking the underlying diversity. 68 6. CONCLUSIONS In conclusion, fertilization with urea N or a complete fertilizer mix with urea and NH4 + -N and other macro and micronutrients did not lead to substantial increases in N2O fluxes in the short-term, even in reasonably wet sites that may support anoxic conditions and denitrification, except that there was an initial loss of CO2 as urea was apparently mineralized. The lodgepole pine site was the only site with significant net nitrification yet did not have significant N2O efflux or uptake, while at the coastal Douglas-fir site, on one measurement day, a small, but significant, N2O efflux was observed in N-fertilized plots on the warmest measurement day of the study. Although longer studies with greater measurement frequency are needed (particularly for N2O), this study indicates that emissions of N2O following single application of fertilization in unpolluted, acidic, conifer-plantation soils in western Canada do not outweigh potential benefits of enhanced C storage over discrete periods of time with regards to global warming potential. Our results, based on 16S rDNA diversity, suggest that the forest soils studied sustain distinct microbial populations. There is also the added element of time, as with the passage of time these populations tended to change from their original composition at the start of the study. Again, by the end of the study period, these populations were also different among each other. However, the diversity of the ammonia oxidizers observed in our samples might be an artifact of differences between the gels and further studies are needed. 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In: Dworkin M, Falkow S, Rosenberg E, Schleifer KH and Stackebrandt E (Eds.), The prokaryotes: an evolving electronic resource for the microbiological community, 3rd ed., release 3.0 [online], Springer, New York, www.prokaryotes.com. 85 APPENDIX 1 DGGE profiles of bacterial 16 S rRNA PCR products amplified from soil under western hemlock 7 days following fertilization with 200Kg N ha-1 urea or 200Kg N ha-1 plus 100Kg P ha-1 plus micronutrients (where S21-23: N, S89-93:Control, and S41-44: Complete). ladder S23 S22 S21 S93 S92 S91 S90 S89 S44 S43 S42 S41 ladder 86 APPENDIX 2 ladder S5 S4 S3 S1 S172 S171 S170 S169 S12 S11 ladder DGGE profiles of bacterial 16 S rRNA PCR products amplified from soil under western hemlock 50 days following fertilization with 200Kg N ha-1 urea or 200Kg N ha-1 plus 100Kg P ha-1 plus micronutrients (where S1-5: N, S169-172: Control, and S11-12: Complete). 87 APPENDIX 3 ladder S203 S202 S201 S200 S283 S282 S281 S280 S279 S241 S240 S239 ladder DGGE profiles of bacterial 16 S rRNA PCR products amplified from soil under lodgepole pine 7 days following fertilization with 200Kg N ha-1 urea or 200Kg N ha-1 plus 100Kg P ha-1 plus micronutrients (where S200-203: N, S279-283: Control, and S239-241: Complete) 88 APPENDIX 4 ladder S212 S211 S233 S232 S230 S229 S223 S222 S221 S220 S219 ladder DGGE profiles of bacterial 16 S rRNA PCR products amplified from soil under lodgepole pine 210 days following fertilization with 200Kg N ha-1 urea or 200Kg N ha-1 plus 100Kg P ha-1 plus micronutrients (where S211-212: N, S229-233: Control, and S219-223: Complete) 89 APPENDIX 5 ladder S404 S403 S402 S401 S400 S394 S392 S391 S390 ladder DGGE profiles of bacterial 16 S rRNA PCR products amplified from soil under coastal Douglas-fir 7 days following fertilization with 200Kg N ha-1 plus 100Kg P ha-1 plus micronutrients (where S400-404: Control, and S390-394: Complete) 90 APPENDIX 6 ladder S363 S362 S361 S360 S374 S373 S372 S371 S370 ladder DGGE profiles of bacterial 16 S rRNA PCR products amplified from soil under coastal Douglas-fir 60 days following fertilization with 200Kg N ha-1 plus 100Kg P ha-1 plus micronutrients (here S360-363: Control, and S370-374: Complete) 91 HEMLOCK day7 N+B day7 control day7 complete day7 control day50 N+B day50 control day50 complete day50 control day50 control day50 N+B day50 control day50 N+B day50 N+B S21 S91 S41 S93 S4 S170 S12 S172 S169 S5 S171 S1 S3 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 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