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Enzyme activities and nitrogen transformations following fertilization of a Douglas-fir forest in coastal… Adams, Seth Daniel 2009

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ENZYME ACTIVITIES AND NITROGEN TRANSFORMATIONS FOLLOWING FERTILIZATION OF A DOUGLAS-FIR FOREST IN COASTAL BRITISH COLUMBIA by Seth Daniel Adams  B.Sc. University of Alaska Fairbanks, 2005  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) December 2009  © Seth Daniel Adams, 2009  ii  ABSTRACT Forest fertilization has long been used to enhance tree growth and timber yield. More recently, fertilization has become the focus of increased interest as a potential method for increasing soil C uptake, vis-à-vis suppression of microbial enzymes that decompose recalcitrant soil organic matter (SOM). However, fertilization is also associated with increased emission of the potent greenhouse gas N2O. In this study I evaluate the effect of N amendment on activities of soil enzymes and on N ammonification and nitrification rates in a chronosequence of Douglas-fir stands on Vancouver Island, British Columbia. Ammonification and nitrification rates were also compared between two different fertilizers, urea and slow-release urea, which is urea with a polymer coating to decrease the rate of N release. Fertilization significantly decreased the activity of the ligninases, phenol oxidase and peroxidase in the mineral soil layer of all stand ages. However, the effect appeared to be temporary, as there was no difference between treatment and control 63 days after fertilization. Activity rates of three enzymes that degrade labile SOM - cellobiohydrolase, betaglucosidase and NAGase - were also measured, and there was a small decrease in activity rates of these enzymes in the forest floor. Urea amendment increased net rates of ammonification and nitrification. Addition of slow-release urea resulted in lower rates of ammonification and nitrification compared to urea, but the rates remained elevated longer. Nitrification rates were increased the most in the clearcut stand (7 years old), and less so in the two older stands (18 and 57 years old). Ammonification and nitrification rates were approximately an order of magnitude higher in the forest floor than in the mineral soil, and the response to fertilization was also greatest in the forest floor. Nitrification was increased by fertilization, but this effect was only significant in the clearcut stand. Nitrification at all sites increased more with urea addition than with slowrelease urea. Further research is recommended to determine if there is a minimum threshold of available N necessary to cause the suppression of microbial enzyme activities, and if it could be reached through operational applications of slow-release urea fertilizer.  iii  TABLE OF CONTENTS ABSTRACT ................................................................................................................... ii TABLE OF CONTENTS ............................................................................................... iii LIST OF TABLES .......................................................................................................... v LIST OF FIGURES ....................................................................................................... vi LIST OF ILLUSTRATIONS ........................................................................................ viii LIST OF ABBREVIATIONS.......................................................................................... ix ACKNOWLEDGEMENTS ............................................................................................. x 1 INTRODUCTION .......................................................................................................1 1.1 SOIL CARBON ....................................................................................................1 1.2 WHY FERTILIZE FORESTS? .............................................................................2 1.3 N AMENDMENT SUPPRESSION OF DECOMPOSITION ................................2 1.4 DECOMPOSITION OF RECALCITRANT SOM ..................................................3 1.5 DECOMPOSITION OF LABILE SOM .................................................................5 1.6 EFFECTS OF N AMENDMENT ON SOIL BIOTA ..............................................5 1.7 FATE OF ADDED N ............................................................................................6 1.8 OBJECTIVES ......................................................................................................7 1.9 HYPOTHESES ....................................................................................................7 2 METHODS AND MATERIALS ..................................................................................8 2.1 SITE DESCRIPTION ...........................................................................................8 2.2 STUDY DESIGN ..................................................................................................9 2.3 SOIL SAMPLING AND PREPARATION .............................................................9 2.4 N IMMOBILIZATION, AMMONIFCATION AND NITRIFICATION ......................9 2.5 ENZYME ANALYSES........................................................................................10 2.6 STATISTICAL ANALYSIS .................................................................................11 3 RESULTS ................................................................................................................13 3.1 ENZYMES .........................................................................................................13 3.2 NITROGEN TRANSFORMATIONS ..................................................................14  iv 4 DISCUSSION ..........................................................................................................40 4.1 ENZYME RESPONSES ....................................................................................40 4.2 NITROGEN TRANSFORMATIONS ..................................................................42 4.3 MANAGEMENT IMPLICATIONS ......................................................................42 4.4 LIMITATIONS ....................................................................................................43 4.5 RECOMMENDATIONS .....................................................................................44 5 CONCLUSIONS ......................................................................................................45 6 APPENDICES .........................................................................................................46 APPENDIX A - ANOVA TABLES ............................................................................46 APPENDIX B – PHOTOS OF FIELD SITES ...........................................................49 APPENDIX C – SELECTED MEAN VALUES .........................................................50 APPENDIX D – CORRELATION MATRICES FOR ENZYME DATA .....................51 APPENDIX E – CORRELATION MATRICES FOR NITROGEN DATA .................52 7 WORKS CITED .......................................................................................................55  v  LIST OF TABLES Table 1 Selected soil characteristics of the study sites…………………………………. 11 Table 2 Mean concentrations of ammonium, nitrate, microbial N, and dissolved organic nitrogen compared between the three stand ages………………………………..……… 17 Table 3 Comparison of mean net nitrification rates between the three stand ages and two soil layers……………………………………………………………………………………… 17  vi  LIST OF FIGURES Figure 1 Compared activity rates of cellobiohydrolase and NAGase………………...... 18 Figure 2 Compared activity rates of betaglucosidase and cellobiohydrolase……...…. 19 Figure 3 Compared activity rates of NAGase and betaglucosidase…………………… 20 Figure 4 Compared activity rates of phenol oxidase and peroxidase……………...….. 21 Figure 5 Cellobiohydrolase activity in the forest floor of control and urea-fertilized plots immediately prior to and 2, 14 and 63 days following fertilization…………………….… 22 Figure 6 Betaglucosidase activity in the forest floor of control and urea-fertilized plots immediately prior to and 2, 14 and 63 days following fertilization…………………….… 23 Figure 7 NAGase activity in the forest floor of control and urea-fertilized plots immediately prior to and 2, 14 and 63 days following fertilization……………………………………… 24 Figure 8 Cellobiohydrolase activity in the mineral soil of control and urea-fertilized plots immediately prior to and 2, 14 and 63 days following fertilization………………………. 25 Figure 9 Betaglucosidase activity in the mineral soil of control and urea-fertilized plots immediately prior to and 2, 14 and 63 days following fertilization…………………….… 26 Figure 10 NAGase activity in the mineral soil of control and urea-fertilized plots immediately prior to and 2, 14 and 63 days following fertilization…………………….……………..… 27 Figure 11 Peroxidase activity in the forest floor of control and urea-fertilized plots immediately prior to and 2, 14 and 63 days following fertilization…………………….… 28 Figure 12 Phenol oxidase activity in the forest floor of control and urea-fertilized plots immediately prior to and 2, 14 and 63 days following fertilization…………………….… 29 Figure 13 Peroxidase activity in the mineral soil of control and urea-fertilized plots immediately prior to and 2, 14 and 63 days following fertilization…………………….… 30 Figure 14 Phenol oxidase activity in the mineral soil of control and urea-fertilized plots immediately prior to and 2, 14 and 63 days following fertilization…………………….… 31 Figure 15 Activity rates of cellobiohydrolase, betaglucosidase and NAGase compared between the three different stand ages…………………………………………………….. 32 Figure 16 Concentrations of ammonium, nitrate, microbial nitrogen, and dissolved organic nitrogen compared between the three fertilizer treatments and two soil layers...…….. 33 Figure 17 Comparison of ammonium concentrations in the forest floor between the three fertilizer treatments over time……………………………………………………………….. 34 Figure 18 Comparison of ammonium concentrations in the mineral soil between the three fertilizer treatments over time……………………………………………………………….. 35  vii Figure 19 Comparison of net-ammonification rates between the three stand ages, three fertilizer treatments, and two soil layers..........…………………………………………….. 36 Figure 20 Comparison of net-nitrification rates between the three stand ages, three fertilizer treatments, and two soil layers..…………………………………………………………..… 37 Figure 21 Comparison of net ammonification rates in the forest floor between the three fertilizer treatments over time……………………………………………………………….. 38 Figure 22 Net change in ammonium, nitrate, microbial nitrogen and dissolved organic nitrogen compared between the three fertilizer treatments and two soil layers……….. 39  viii  LIST OF ILLUSTRATIONS Plate 1 Map of the study area on Vancouver Island……………………………….…….. 11  ix  LIST OF ABBREVIATIONS °C α µg µL µM µm BC betaglucosidase C cm CO2 DON g h H202 ha K2SO4 kg km LAI LOM M m mg mM mL mm N N n NAGase NaOH nm nmol N2 N2O NH4+ NO2NO3NOX pH PLFA ROM SIN SOC SOM TOC-TN  Temperature in degrees Celsius Type I error Microgram Microliter Micromolar Micrometer British Columbia β-1,4-Glucosidase Carbon Centimeter Carbon dioxide Dissolved organic nitrogen Gram Hour Hydroxide Hectare Potassium sulfate Kilogram Kilometer Leaf area index Labile organic matter Molar concentration Meter Milligram millimolar Milliliter Millimeter Nitrogen Normality Size of the statistical sample β-1,4-N-Acetylglucosaminidase Sodium hydroxide Nanometer Nanomole Nitrogen gas Nitrous oxide Ammonium Nitrite Nitrate Nitrogen oxide Acidity in water Phospholipid fatty acid Recalcitrant organic matter Soluble inorganic nitrogen Soil organic carbon Soil organic matter Total organic carbon, total nitrogen  x  ACKNOWLEDGEMENTS I gratefully acknowledge the help of the many people who have helped me in the pursuit of this degree. First and foremost, I thank my committee members, Drs. Sue Grayston, Cindy Prescott and Andy Black, and my external examiner, Dr. Art Bomke, who made it all possible. I could not thank Dr. Val LeMay enough for her unending patience and help with the statistical analysis. She is certainly destined for sainthood. I would like to acknowledge the funders of this research, NSERC, through an NSERC strategic grant awarded to T.A. Black and S. J. Grayston and the NSERC discovery grant of S.J. Grayston. My never-ending lab work would have truly been so if not for the dedication of three people, Josi Cueni, Eveline Xia, and Barry Jonat. They took an interest in doing top-notch work that I found personally touching, and they managed to be fun to be around in the process. I would also like to give special acknowledgment to Dr. Paul Jassal for kindness, encouragement, long conversations thinking through „what it all means‟, and for spreading the fertilizer. My mom and dad would like to thank Andrew Hum for collecting some of my incubated bags, making it possible for me to go home for a visit. For my own part, I would like to thank him for being an all-around good guy. And the rest of the BIOMET group, who always managed to be helpful with field work and fun at conferences. Kazuyuki Ishimaru, Meiliana Dewi and I started together and rode out the bumps together. They are great friends and everything would have been harder without them. Kate Del Bel has my gratitude for always being sympathetic and accommodating when the Dodge broke down, and for being patient with my clumsiness in the lab. I would not like to thank the Dodge. And thanks to the countless other students in the Belowground Group who tolerated me regularly popping into their office to ask “hey, listen, do you know….?” And, of course, Susie, for being uniquely capable of putting up with me.  1  1 INTRODUCTION Soils are the single largest pool of carbon on the planet, including atmospheric CO2. Accordingly, there has been increased interest in recent years in management applications that increase soil carbon storage. A meta-analysis performed by Johnson and Curtis (2001) showed increased forest carbon (C) storage following nitrogen (N) fertilization. Fertilization is known to increase tree growth (e.g. Hanley, 1996), but below-ground C storage may also be increased by N fertilization due to suppressed decomposition of recalcitrant soil organic matter (Fog, 1988, Waldrop et al., 2004). However, N fertilization may also result in increased emissions of the potent greenhouse gas N2O, potentially offsetting the benefits of increased C storage (Jassal et al., 2008). This study does not measure N2O emissions or soil C content directly, but instead measures activity of foundational processes: activity rates of soil enzymes catalyzing decomposition, and transformation of the organic and inorganic N forms that precede conversion to N2O gas. 1.1 SOIL CARBON Three times more carbon is stored in Earth's soils than in the vegetation it supports (Post and Kwon, 2000). Soil organic carbon (SOC) takes two primary forms: light fraction (mostly cellulose, which is generally more labile, but also includes lignins and phenols, which are generally more recalcitrant to decomposition) and heavy fraction (SOC that has been modified by bacteria and incorporated into organo-mineral complexes which are highly resistant to decomposition) (Post and Kwon, 2000). Heavy-fraction organic carbon represents the majority of SOC on a global scale due to its long residence times in soil, with turnover times on the order of decades (Post and Kwon, 2000). This study focuses on lightfraction organic carbon in its two primary forms: cellulose, and lignins and phenols. Hereafter these two soil organic matter (SOM) categories are referred to as labile organic matter (LOM) and recalcitrant organic matter (ROM), respectively. Cellulose is the largest component of leaf structure and the second material to be decomposed after litter fall: first are the water-soluble components, then cellulose, then lignins and phenols. Since lignins and phenols play a considerable role in the formation of humus – SOM with a decay rate that is nearly zero - their decomposition may have a significant long-term effect on SOC (Berg and Matzner, 1997, Prescott, 2005). Although lignin makes up a smaller mass fraction of leaf structure than readilydecomposed cellulose, it provides a framework for the leaf and frequently a large fraction of the cellulose is integrated into the lignin structures (Berg and Matzner, 1997). Since lignin is more recalcitrant than cellulose, the cellulose bonded within the lignin cannot be accessed  2 until after the lignin is decomposed. Therefore, the decomposition rate of much of the cellulose in litter is tied to the decomposition of lignin (Berg and Matzner, 1997). Decomposition of cellulose is catalyzed by a wide variety of enzymes, collectively called cellulases, which are produced by a wide variety of bacteria and fungi. Although cellulose is generally rapidly decomposed, frequent additions of plant litter prevent soil from becoming depleted in LOM. In temperate ecosystems decomposition is retarded by cool weather, causing a buildup of LOM in the active layer (Post and Kwon, 2000). Labile organic matter is integral to forest function because it represents the fastest input and mineralization of important nutrients (Post and Kwon, 2000). Due to its longer residence times in soil, ROM is of considerable interest in studies addressing long-term soil C fluxes (e.g., Hofmann et al., 2009). Unlike cellulose, there are few enzymes capable of completely decomposing lignins; the main ones are phenol oxidase and peroxidase. These two enzymes are mainly thought to be produced by a group of fungi known as white rot fungi, which are primarily basidiomycetes. Further constraining decomposition, all organisms known to decompose lignin are aerobic (Berg and Matzner, 1997). 1.2 WHY FERTILIZE FORESTS? The productivity of coastal forests of the Pacific Northwest is commonly highly Nlimited (see review by Edmonds et al., 1989). A single addition of N can increase growth in most coastal Douglas-fir stands for up to 10 years, and lead to growth increases of up to 20% (Hanley et al., 1996). Tree-growth increases may last longer in poor-quality soils (Edmonds et al., 1989). Additionally, recent reports of increased soil C storage following atmospheric N deposition have led to interest in using fertilization to also potentially increase C storage belowground (see review by Johnson and Curtis, 2001). The mechanism of the enhanced soil C storage with N deposition is thought to be related to increased litter deposition resulting from enhanced tree growth, coupled with direct suppression of microbial community activity and the enzymes responsible for decomposition. Increased timber yields, shorter rotation times, and potential long-term increases in soil C storage have stimulated interest in large-scale forest fertilization by the British Columbia government and timber companies. 1.3 N AMENDMENT SUPPRESSION OF DECOMPOSITION The carbon to nitrogen (C:N) ratio of a particular substrate is commonly thought of as an index of its decomposability; wherein a high C:N ratio implies N limitation and therefore lower decomposability. For this reason it was long assumed that addition of N to soil would  3 increase decomposition of SOM. However, Fog (1988) linked a variety of “anomalous” results, mostly of decreased mass loss rates or decreased CO2 evolution following N amendment, into a coherent explanation of a previously-unknown phenomenon of N suppression of decomposition. He showed it to be unlikely that the effect of N on decomposition is as simple as it being a limiting factor to decomposition. Recently there has been a flurry of new studies investigating the possibility of increased carbon storage in forest soils following N amendment - vis-à-vis accumulating SOM – through either increases in soil C or decreases in heterotrophic respiration, and most studies have shown the potential for increases in soil C storage. Notably, the focus of many recent studies is the effect of chronic nitrogen deposition resulting from human activities on C storage (for details, see Waldrop et al., 2004), and so the studies were conducted in continuously N-saturated conditions. Other long-term studies have largely measured mass loss, and have recorded reduced mass loss for up to 5 years following fertilization (Fog, 1988). However, the duration of these Naddition effects on enzyme activities once N-limitation has returned has not been well studied. 1.4 DECOMPOSITION OF RECALCITRANT SOM Nitrogen amendment is thought to retard the decomposition of lignin (Fog, 1988, Berg and Matzner, 1997). The type of N fertilizer applied does not seem to be critical (Fog, 1988). In most studies to date N amendment has resulted in decreased phenol oxidase activity (Carreiro et al. 2000, Saiya-Cork et al., 2002, Sinsabaugh et al., 2002, DeForest et al., 2004, Gallo et al., 2004, Sinsabaugh et al., 2004, Hofmockel et al., 2007, Kunito et al., 2009), sometimes accompanied by a decrease in peroxidase activity (Sinsabaugh et al., 2004). However, increased phenol oxidase activity following N amendment has been found in high-quality, low-lignin litters (Carreiro et al., 2000, Gallo et al., 2004). Similarly, other studies have found phenol oxidase activity to be suppressed in humus layers but stimulated in litter, indicating that the effect of N amendment on phenol oxidase activity depends on the chemistry of the organic substrate (Carreiro et al., 2000, Saiya-Cork et al., 2002, Sinsabaugh et al., 2002), although this is controversial (Keeler et al., 2009). Enowashu et al. (2009) excluded atmospheric deposition in a central European forest by filtering rain, creating conditions opposite of most other N studies: a high-N control and a low-N treatment. Their results provided mixed support of the most common findings to date; under low-N conditions decreased cellulase activity, as expected, but not increased ligninase activity (however, phenol oxidase was not measured). Few studies directly compare soil enzyme suppression in differing soil layers; Deforest et al. (2004) compared forest floor and mineral soil layers  4 and found that they responded similarly, but with larger magnitude of suppression in the forest floor. A leading hypothesis for the mechanism of the decrease in decomposition of recalcitrant materials following N addition is the “nitrogen-mining hypothesis” put forth by Craine et al. (2007). They suggest that N-limited microbes decompose large amounts of recalcitrant C in order to access N contained within the molecules. There are two possible mechanisms for the resulting decrease in decomposition under the N-mining hypothesis: 1) a decrease in the production of extracellular enzymes to extract N from recalcitrant substances (Waldrop et al., 2004, Sinsabaugh et al. 2005 and Craine et al., 2007), and 2) increased availability of N increases the demand for labile C, which reduces availability to those microbes responsible for the decomposition of recalcitrant organic matter (Craine et al., 2007). Regardless of which mechanism is operating, suppressed decomposition of recalcitrant C has significant implications for our understanding of nutrient cycling: high availability of labile C may cause N-limited microbes to decompose recalcitrant C in order to meet N demands for growth (Craine et al., 2007). In other words, the two C pools are not cycled independently of one another. The N-mining hypothesis may only pertain to recalcitrant substrates. This is supported by a finding by Waldrop et al. (2004) in which losses of soil carbon in the three years following N amendment were found in forests with high-quality litters, whereas gains were detected in a forest stand with low-quality litter. A review by Prescott (2005) cites an additional six studies showing either increased decomposition of low-lignin litters after N amendment or decreased decomposition of high-lignin litters following N amendment. Increased soil C storage or reduced decomposition of SOM following N amendment has been shown in a variety of ecosystem types (with the exception of peat bogs, owing to anaerobic conditions combined with unique low-lignin, high-phenol litters peculiar to Sphagnum (see Freeman et al. (2001) and Bragazza et al. (2006)). Several recent papers have shown decreased decomposition of SOM with N amendment irrespective of enzyme activities (Keeler et al., 2008, Hobbie, 2008). These authors allow that similar enzyme suppression could have gone undetected due to temporal heterogeneity of enzyme activity, or that decomposition was simply catalyzed by enzymes not measured in their study. But they also suggest that previously reported reductions in enzyme activity may be ecosystemspecific or part of a suite of changes, including microbial community composition changes, inhibition of decomposition by phenolic compounds, production of new, highly-recalcitrant compounds due to abiotic interactions between soluble inorganic nitrogen (SIN) and phenols, or any combination of these.  5 1.5 DECOMPOSITION OF LABILE SOM N amendment has been shown in many studies to increase decomposition of cellulose (see reviews by Fog (1988) and Berg and Matzner (1997)), and therefore decomposition of cellulose is generally thought to be an N-limited process. More recent studies have confirmed increased cellulase activity under N amendment (Carreiro et al., 2000, Saiya-Cork et al., 2002, Sinsabaugh et al., 2002, Gallo et al., 2004, Sinsabaugh et al., 2004, Keeler et al., 2008). Only one study has reported a decrease in cellulase activity with N addition, which they attributed to an increase in soluble phenolic compounds, which, in turn, suppressed the cellulases (DeForest et al., 2004). 1.6 EFFECTS OF N AMENDMENT ON SOIL BIOTA Nitrogen added to decomposing organic matter often has no effect or a negative long-term effect on microbial activity, as reviewed by Fog (1988) and by Berg and Matzner (1997). Soil microbial activity, measured as rates of mass loss, soil respiration and extracellular enzyme activity, has shown consistent responses to N amendment. Soil respiration commonly decreases following N amendment (Olsson et al., 2005, Demoling et al., 2008). Olsson et al. (2005) found decreases in autotrophic and heterotrophic respiration following N amendment, despite a 3-fold increase in above-ground growth. They attribute the decreased autotrophic respiration to decreased energy allocation by trees to roots and mycorrhizal fungi (Olsson et. al, 2005 and references therein). Demoling et al. (2008) found a significant reduction in microbial carbon, bacterial growth rate, total fungal biomass and proportion of fungal to bacterial biomass, indicating a significant decrease in soil fungi. DeForest et al., (2004) found a decrease in microbial biomass following N amendment, but without a shift in relative composition of soil microbes. Carreiro et al. (2000), DeForest et al. (2004), Gallo et al. (2004) and Sinsabaugh et al. (2004) found no change in relative community structure of soil microbes after N amendment, based on phospholipid fatty acid (PLFA) data. Although analysis of PLFAs is of insufficient resolution to assess a detailed shift in the microbial community composition, it can indicate broad-scale changes in microbial community structure, such as fungi:bacteria ratios. Using molecular techniques, Hofmockel et al. (2009) surveyed abundance of basidiomycete genes that code for laccase, and found no correlation between phenol oxidase activities and gene abundance, indicating that inhibition of phenoloxidase production may be at the level of gene expression rather than changes in community structure. Given the overall complexity of soil ecosystems and the effects of N amendment, we remain far from a predictive understanding of the interaction between N amendment and soil  6 biota (Sinsabaugh et al., 2002) and, consequently, the mechanism of increased C storage with fertilization. 1.7 FATE OF ADDED N Upon addition to a forest soil, urea pellets are rapidly hydrolyzed into ammonium (NH4+),which  may be taken up by vegetation or soil micro-biota, or nitrified into nitrite (NO2-)  and nitrate (NO3-) (the residence time of nitrite is sufficiently short that it is not normally detected in forest soils). Depending on the conditions, nitrate may then be denitrified to N2 gas. Denitrification is a heterotrophic process performed by facultative anaerobic bacteria, and in the presence of small amounts of oxygen or low pH the process may be incomplete, resulting in the release of N2O gas (see review by Wrage et al, 2001). N2O is a greenhouse gas 300 times more potent than CO2 with an atmospheric residence time of approximately 120 years (IPCC, 2007). NH4+ is preferentially taken up by most trees and soil microbial populations (e.g., Hart et al., 1994), and so the size of soil NO3- pools can be used as an index of N availability in the ecosystem. Therefore, NO3- leaching and denitrification can be indicative of ecosystem N-saturation (Wallenstein et al., 2006). Denitrification is constrained by N availability, and has been increased by fertilization in both lab and field experiments (Johansson, 1984, Binkley and Hart, 1989). Denitrification is not measured in this study. However, ammonification and nitrification are precursor steps to denitrification, and are considered in this study for their potential impact on denitrification. Nitrification and denitrification are often tightly coupled (Wrage et al., 2001), and the rates are sometimes correlated (Wallenstein et al., 2006). In a concurrent study, Jassal et al. (2008) found increased N2O emissions following fertilization; the urea treatment had higher initial rates of N2O release, which peaked sharply 2 months after fertilization. However, four months after fertilization the rate of release of N2O was higher from the slow-release plots, yielding approximately equal total N2O emissions and accounting for 5%of the total fertilizer N added. Ammonification and nitrification are stimulated by N fertilization in forest soils (e.g., Prescott et al., 1992, Forge and Simard, 2001, Wallenstein et al., 2006). Nitrification is also stimulated by clearcut harvesting (Prescott et al., 1992, Smolander et al., 1998, Forge and Simard, 2000). In recently clearcut stands the increase in nitrification following fertilization is notably fast (Forge and Simard, 2001), likely due to elevated populations of nitrifying bacteria prior to fertilizer application. In these cases nitrification can exceed ammonification and deplete soil ammonium pools (Smolander et al., 1998).  7 1.8 OBJECTIVES In this study I explore the possible mechanisms of increased soil carbon storage and the fate of the added nitrogen following fertilization in a chronosequence of Douglas-fir forests in south-west British Columbia (BC). It is part of a larger study which utilizes eddycovariance to measure the forest carbon budget following fertilization, including measuring N2O emissions resulting from fertilization. Specifically, I seek to explain the mechanism for any decrease in soil respiration following fertilization by measuring LOM and ROM enzyme activity in three Douglas-fir stands aged 8, 20 and 59 years for 63 days following fertilizer application. I also determine the fate of added N fertilizer by measuring rates of net ammonification, net nitrification and net increase in microbial biomass-N. I compare urea and slow-release urea fertilizers to determine if slow-release yields smaller pools of inorganic N following fertilization and lower rates of nitrification (and potentially denitrification). 1.9 HYPOTHESES Based on literature to date I hypothesize that: 1) N amendment will suppress activity of enzymes that degrade recalcitrant organic matter (phenol oxidase and peroxidase). 2) N amendment will increase activity of enzymes that degrade labile organic matter (NAGase, cellobiohydrolase and betaglucosidase). 3) N amendment will increase ammonification and nitrification rates. a. In the urea treatment there will be a „pulse‟ increase of these measures shortly after fertilization, and then return to background levels; in the slowrelease treatment ammonification and nitrification rates and will increase more gradually throughout the study period. b. N amendment will have the strongest effect on ammonification and nitrification rates in the forest floor as compared to the mineral soil. 4) Nitrification rates will be highest in the recently clearcut site, and this site will respond most strongly to fertilization. I will also address the following questions: 1) How long do the enzyme responses to fertilization last? 2) Do enzyme activities and responses to fertilization vary between soil layers? 3) Do enzyme activities and responses vary between stand ages?  8  2 METHODS AND MATERIALS 2.1 SITE DESCRIPTION This study was conducted on the east coast of Vancouver Island, British Columbia, Canada at research sites that are part of the Fluxnet Canada Research Network (http:www.fluxnet-canada.ca/; now Canadian Carbon Program) (Plate 1). The three sites comprise three stand ages of primarily Douglas-fir (Pseudotsuga menziesii), ages 58, 19, and 7 years in 2007. The sites are henceforth referred to as mature, young and clearcut, respectively. The mature stand is located approximately 10 km south-west of Campbell River at 49°52‟N, 125°20‟W, and 300 m elevation. The forest naturally regenerated in 1949 following logging and slash-burning. The dominant overstory is second-growth Douglas-fir (80%) with 17% western redcedar (Thuja plicata) and 3% western hemlock (Tsuga heterophylla). Stand density in 2007 was about 1100 stems per hectare, dominant tree height was about 33 m, mean tree diameter at 1.3-m height was 31 cm, and leaf area index (LAI) was 7.3 (Chen et al., 2006, in Jassal et al., 2009). The mean annual temperature and precipitation at the site are 8.6°C and 1470 mm, and the site is occasionally subjected to a soil water deficit in August, September and October (Jassal et al., 2008). The young stand is located approximately 70 km south-west of Campbell River at 49°31‟N, 124°54‟W, and 170 m elevation. It was logged in 1987 and broadcast burned and planted in 1988 with 75% Douglas-fir, 21% western redcedar and 4% grand fir (Abies grandis). The mean annual temperature and rainfall at the site are 8.8 °C and 1410 mm, (Jassal et al., 2009). The clearcut is located approximately 10 km south-west of Campbell River at 49°52‟N, 125°17‟W, and 175 m elevation. The original harvest took place in 1940, and it was harvested again in the winter of 1999/2000 and planted in early spring 2000 with 93% Douglas-fir and 7% western redcedar plug stock. Stumps from the original old-growth forest as well as the recent harvest are still evident. The mean annual temperature and rainfall at the site are 9.6 °C and 1610 mm (Jassal et al., 2009). The soils are humo-ferric podzols with similar N and C concentrations, although the depth of the organic layer varies between sites and is deepest at the young site (Humphreys et. al., 2006).  9 2.2 STUDY DESIGN At each site nine 100-m2 plots were laid out in a randomized complete block pattern to test each of three treatments, with three replicates of each. The three treatments I compared were the control (i.e. no fertilizer addition), urea, and polymer-coated, slowrelease urea (Environmentally Smart Nitrogen, Agrium Inc., Calgary, Alberta, Canada). Fertilizer was spread manually at 200 kg N ha-1 on April 11, 2007 at all three sites. 2.3 SOIL SAMPLING AND PREPARATION Samples were collected from each plot at each of the three sites immediately before treatment (day 0), and 1, 2, 7, 14, 21, 28 and 63 days after fertilization. Using a garden trowel, one (approximately fist-sized) sample of forest floor and a second of mineral soil were taken at each time and were placed in separate bags. Forest floor samples were a profile of the depth of the horizon (Table 1), mineral soil samples were collected from the top 5 to10 cm of the mineral soil layer. Samples were placed in a cooler and taken back to the lab where they were frozen until analysis. Concentration of available NH4+, available NO3-, total extractable N and total extractable C was measured in these samples. 2.4 N IMMOBILIZATION, AMMONIFCATION AND NITRIFICATION At the time of each sampling a second sample (equivalent to the one returned to the lab) was placed in a 15-µm-thick polyethylene bag which was sealed and re-buried in the same location and depth. Six weeks later these incubated bags were removed and analyzed for the same nutrients as the non-incubated bags (method described below). This method allows a snap-shot of nutrient transformations to be calculated at different dates following N amendment. The calculated transformations (per Jerabkova et al., 2006) are: net ammonification, net nitrification, and microbial biomass C and N. Net ammonification is calculated as NH4+ at the end minus NH4+ at the beginning, net nitrification is calculated as NO3- at the end minus NO3- at the beginning. Once in the lab, each sample was thawed and any remaining vegetation was removed. The forest-floor samples were blended in a household blender, and all samples were sieved through a 5-mm screen. All of the following measurements were made using sub-samples of each sample. A 5-g sample was dried for 24 hours at 65°C to determine moisture content based on wet and dry weight. To measure pH, 5.0 g of sample and 50 mL of H20 were placed in a plastic, closeable container and shaken for 15 minutes. The soil solution was allowed to settle before pH was measured with a HANNA instruments HI 9025 pH meter. Total extractable soil C and N concentrations were measured by extracting each soil sample (7-g wet mass) for one hour in a 50-mL 0.5-M K2SO4 solution, while being  10 agitated (Brookes et al., 1985). Samples were allowed to settle in the refrigerator, and then the supernatant was removed with a syringe and filtered through Whatman 42 filter paper (2.5-µm particle retention size). Total extractable C and N were measured at the University of Toronto (Mississauga) Ecohydrology Lab using a Lachat IL550 TOC-TN analyzer. Microbial biomass C and N was measured using the fumigation-extraction method as per Brooks et al. (1985). Samples (7-g wet mass) were fumigated by incubating them in the dark for 24 hours at room temperature in a vacuum chamber containing an open beaker with 30 mL of chloroform and boiling chips. Samples were then extracted and analyzed for C and N concentrations as described above. 2.5 ENZYME ANALYSES Enzyme activities were measured in the control (unfertilized) and urea-amended treatments in the three stands at time 0, prior to fertilization, and at day 2, 14 and 63 after fertilization. Enzyme activity rates were measured using a technique adapted from Sinsabaugh et al. (2003). The cellulases and chitinase were measured fluorimetrically, while phenol oxidase and peroxidase were measured colorimetrically. For the fluorimetric assay 0.1 g of thawed soil sample was placed in a 125-mL Nalgene container with 50 mL of pH-5.0 50-mM sodium acetate buffer and agitated for one hour with small glass beads for stirring. Another 50 mL of the sodium acetate buffer was added after agitation. 200-µL aliquots of sample were dispensed into 96-well microplates along with 50 µL of 200-µM enzyme substrate, with 16 replicates per sample. The two cellulases measured were β-1,4Glucosidase (betaglucosidase) and Cellobiohydrolase, and the chitinase measured was β1,4-N-Acetylglucosaminidase (NAGase). The corresponding three substrates used were: 4-MUB-N-acetyl-β-glucosaminide, 4-MUB-β-D-cellobioside, and 4-MUB-β-D-glucoside. The procedure for the colorimetric analysis was identical to that of the fluorimetric analysis, except that 0.5 g of sample was used instead of 0.1 g, and 25-mM L-3,4dihydroxyphenylalanine was used as the substrate for the reaction, with an additional 10 µL of 0.3% H202 for peroxidase. Substrate controls received 50 µL of the appropriate substrate plus 200 µL of acetate buffer, and quench standard wells received 50 µL of standard (10 µM 4-methylumbelliferone) plus 200 µL of acetate buffer. After addition of substrate, samples were incubated in the dark at room temperature. Incubation times were 3 hours for NAGase and betaglucosidase and 7 hours for cellobiohydrolase. After incubation a 20-µL aliquot of 0.5-N NaOH was added to each well to stop the reaction. Activity was then measured on a microplate fluorimeter running Cytofluor, with 360/40 excitation and 460/40 emission filters, gain set to 50 and mix time set to 5 seconds. Corrections were made for controls and quenches, and activities were expressed  11 in units of nmol / g / h. Peroxidase and phenol oxidase were incubated for 5 and 18 hours, respectively, then activity was measured using a microplate spectrophotometer that measured absorbance at 460 nm running Softmax Pro. Units are nmol / g / h. 2.6 STATISTICAL ANALYSIS The experimental design was a randomized complete block analyzed as a split-splitsplit plot, with fertilizer applied to the whole-plot, the three stand ages applied to the split plot, the two soil layers applied to the split-split plot, and time applied to the split-split-split plot. Data were analyzed using SAS Analytics 9.1.3 Service Pack 4 (©SAS Institute Inc., Cary, North Carolina, 2003-2003). The PROC GLM procedure was used to assess differences between stand ages, fertilizer treatments, soil layers, and time, with one level of each of those combined to form one split-split plot unit. Assumptions of analysis of variance were checked using residual plots to determine equal variance and normality tests to determine normality of the error terms. Transformations of variables were used when needed. Significance level was set at α=0.05; however, differences at α=0.1 were noted and referred to as marginally significant.  Table 1: Selected soil characteristics for the three study sites in 2002 (Humphreys et al., 2006). Site Surface organic layer  Mature  Young  Clearcut  thickness (cm)  0.9-19.3  1.9-11.5  0.6-17.2  pH  6.29  5.60  5.62  C (mg/g dry soil)  244–527  360–556  401–496  6.8–16.5  1.6–18.3  4.0–16.3  5.86 18–74 0.4–4.4  5.65 21–345 0.9–6.3  5.88 32–105 1.0–5.1  N (mg/g dry soil) Soil mineral fraction (0 to 15 cm) pH C (mg/g dry soil) N (mg/g dry soil)  12  Plate 1: Location of study sites, Vancouver Island, British Columbia, Canada (from Ferster, 2009).  13  3 RESULTS 3.1 ENZYMES Enzyme activity responses to the various treatments and covariates could largely be broken into two categories: those that degrade recalcitrant (ROM) and labile organic matter (LOM). When activity rates of the individual enzymes were compared to the other enzymes some interesting patterns emerged. Activity levels of the LOM enzymes (in this study, NAGase, cellobiohydrolase and betaglucosidase) were highly internally correlated (Figures 1, 2 and 3). None of the LOM enzymes ever existed independently of one another – ie, if cellobiohydrolase was active, betaglucosidase was too. Peroxidase and phenol oxidase were less closely correlated (Figure 4). Activity of rates of LOM and ROM enzymes were independent of one another, and none of these relationships were affected by fertilization. In the forest floor there was a trend, occasionally significant or marginally significant, towards reduced LOM enzyme activity in the fertilized plots compared to time 0 or compared to the control plots at the same time (Figures 5, 6 and 7). This effect appeared in the two later times measured, but was most pronounced at day 14, which may indicate that the effect was declining after 63 days. In the mineral soil, fertilization did not significantly affect activity levels of the LOM enzymes in any stand age, time or treatment (Figures 8, 9, 10). There was a trend toward higher LOM enzyme activities on days 2 and 14 in the control plots, but this was not significant for any enzyme. Activity rates of peroxidase and phenol oxidase in the control plots were significantly higher in the mineral soil than in the forest floor, so fertilization responses of the two soil layers are considered independently. In the forest floor, peroxidase activity was significantly lower in the fertilized plots compared to time 0, but not compared to the control at the same time after time 0 (Figure 11). Phenol oxidase activity was unaffected (Figure12). In the mineral soil, activities of both enzymes were suppressed by fertilization on day 14 (Figures 13 and 14), compared to the same time in the control plots. In the control plots there was a significant time effect, seen as an increase in activity of the ROM enzymes at day 14 compared to the other times. This effect was seen in both enzymes, although the increase was less abrupt in phenol oxidase. In the fertilized plots there was no effect of time on these two enzyme activities, which is interesting because there was no difference between enzyme activities before and after fertilization. Therefore, for mineral soils it is more accurate to think of fertilization as preventing a natural increase in enzyme activity rather than as suppressing ROM enzyme activity below the activity level before fertilizer application (Figures 13 and 14).  14 Enzyme activity showed only minor changes with forest age. Activity levels of LOM enzymes were highest in the young stand, followed by the clearcut then the mature forest (Figure 15). Only the difference between the young stand and the mature forest was significant. Neither peroxidase nor phenol oxidase showed any difference in activity levels across stand ages (the effect of site, with all other factors averaged, was p=0.59 and p=0.57, respectively, data not shown). 3.2 NITROGEN TRANSFORMATIONS Ammonium was the largest and most consistent pool of extractable N at all sites (Table 2), particularly in the forest floor and in fertilized plots (Figure 16). Concentrations of all N forms except nitrate were higher in the forest floor than in the mineral soil. Fertilization substantially increased the availability of ammonium in the forest floor (Figure 17) and mineral soil (Figure 18), but levels returned to approximately background levels by Day 63 in the mineral soil. Ammonium concentration in the forest floor appeared to have „peaked‟ and began to decline by the end of the experiment, particularly in the urea treatment (Figure 17). Dissolved organic nitrogen (DON) concentrations were substantial in all treatments, but DON was occasionally absent in the forest floor layer of the fertilized plots. Nitrate was frequently absent or present only in trace quantities in all sites and treatments. Microbial biomass C and microbial biomass N concentrations were significantly higher in the forest floor than in the mineral soil. DON, ammonium and nitrate concentrations included occasional outliers, indicating high local variability due to natural variability or uneven fertilizer application, or both. The magnitude of the variation was larger in the fertilized plots (data not shown), indicating that much of the variation likely resulted from uneven fertilizer application, although natural variation in uptake and use may also be important. Ammonification (Figure 19) and nitrification (Figure 20) rates were roughly an order of magnitude higher in forest floor than mineral soil samples in all treatments and sites, although the values were sometimes negative. At the model level, there was not a significant effect of soil layer or an interaction between fertilizer and soil layer, but when the soil layers were analyzed independently activity rates in response to fertilization were very different between the two soil layers. The magnitude of ammonification was much larger than nitrification in all treatments. Ammonification rates were generally increased by slow-release fertilizer, and reduced or unchanged by urea (Figure 19). This pattern was true in both soil layers. A notable exception to this rule was in the forest floor of the clearcut site, where both fertilizers caused large (but non-significant, probably due to variation) reductions in ammonification  15 rate. Net ammonification rates did not differ between stand ages or times, although the high variability makes elucidation of an effect difficult (Figure 21). Nitrification was usually increased by fertilization, although the effect was rarely significant due to the high variability. In both forest floor and mineral soil, nitrification was lowest in the control, higher in the slow-release and highest in the urea-treated plots (Figure 20). Nitrification did not significantly differ amongst stand ages in either soil layer in the control plots (Table 3). Under the slow-release urea nitrification in the clearcut was stimulated significantly in the mineral soil and substantially, though non-significantly in the forest floor. In the urea-treated plots forest-floor nitrification was stimulated significantly in clearcut and young stands; in the mineral soil nitrification was stimulated significantly in the clearcut and the mature stands. The absolute quantities of nitrate present were very small relative to the other N forms measured (Table 2), and close to the lower detection limits of the equipment used for the analysis. As such, nitrate levels and transformation rates that are statistically different may not be ecologically important. Nitrification rates between replicate plots in the mineral soil differed significantly (p=0.0003) within each stand age. This could indicate high microsite variability of nitrification rates in mineral soil, but the quantities detected are probably too small to matter ecologically. The clearcut site had the highest nitrification rate, followed by the mature stand and the young stand. Additionally, within each stand the urea plots had the highest nitrification rate, followed by the slow-release, then the control (Figure 20). Nitrification rate did not clearly vary with time, although there were occasional pulses of activity (data not shown). These pulses did not show a clear time pattern, and are as likely to reflect variation in microsites as they are to reflect a time effect on nitrification activity. An interesting result was the occasionally negative or more-negative ammonification rates in urea-treated forest-floor plots in the mature stand and clearcut. Net-ammonification rates were calculated by subtracting ammonium after incubation from ammonium before, so negative rates indicate that less ammonium was present after incubation than before. The missing ammonium may have gone to one of a number of possible sinks, including chemical immobilization, nitrification, denitrification, microbial uptake, and volatilization. Leaching and plant uptake would not occur from buried bags. The increases in microbial N, DON and nitrate during incubation indicated that microbial uptake, chemical immobilization and nitrification accounted for most, but not all, of the missing NH4+ in the urea-treated forest-  16 floor plots (Figure 22). The remaining missing N may have been lost through denitrification, which may be coupled to nitrification in high-nitrate conditions, such as occurring after urea addition. Microsite variability (resulting in variation between the paired soil samples) might also be partly responsible for this result.  17  Table 2: Mean concentrations of various forms of N in three stands of differing ages (µg / g dry soil). Each value is the mean of 3 samples from 3 different fertilizer treatments, 2 soil layers and 8 sampling times (n=144). Values of each nutrient type with the same letter are not significantly different (α = 0.1). Ammonium  Nitrate  Microbial N  DON  Clearcut  176 a  1.3 a  41.3 a  40.0 a  Young  234 a  0.3b  85.1ab  33.5 a  Mature  513 b  0.7 ab  89.7 b  142.1 a  Table 3: Mean nitrification rates in two soil layers under three fertilizer treatments, with three different stand ages directly compared (µg / g dry soil / period). The incubation period was 42 days. Each value is the mean of 3 samples collected on each of 8 days (n=24). Mean nutrient values within soil types and fertilizer treatments with the same letter are not significantly different (α = 0.1). Control  Slow  Urea  Clearcut  3.7 a  28.4 a  45.1b  Young  1.1 a  2.5a  11.1 b  Mature  0.5 a  4.6 a  7.4 a  -0.06 a  10.3 b  18.1 b  0.04 a  0.2 a  0. 9 a  1.1 a  13.9 b  Forest Floor  Mineral Soil Clearcut Young Mature  -1.0 a  18  19  20  21  22  23  24  25  26  27  28  29  30  31  32  33  34  35  36  37  38  39  40  4 DISCUSSION 4.1 ENZYME RESPONSES Central to this study was the hypothesis that N amendment will suppress activity of enzymes that degrade recalcitrant organic matter (ROM - phenol oxidase and peroxidase). This would reduce decomposition of SOM, which may then increase soil C storage. This hypothesis was partly supported in this study. In the forest floor phenol oxidase was not affected by fertilization. Peroxidase activity in the forest floor was significantly reduced by fertilization when compared to time 0 in the urea-fertilized plots, which may indicate a suppression of activity. However, it is also possible that the time-0 value in the urea treatment was anomalously high, resulting from high spatial or temporal variability. It is not possible to eliminate either of these possible explanations, so it remains unclear if peroxidase activity in the forest floor was suppressed by N addition. In the mineral soil both peroxidase and phenol oxidase activities were reduced 14 days following fertilization with urea. My findings are consistent with much of the literature, with the exception of the longevity of the result – I found ROM enzyme activity was reduced by fertilization, but the effect in the mineral soil appeared temporary. This is in contrast to a study by Sinsabaugh et al. (2004) who deemed the effect „permanent‟, citing decreased ROM enzyme activity in the mineral soil during the first year of the study and increased DOC during the second year of the study, which they attribute to decreased ROM enzyme activity. Their study was performed in a hardwood forest in the north-eastern United States under high-lignin litters. Studies in hardwood forests in northern Michigan lasting for an entire growing season (generally, May to October) have consistently supported their results (e.g. Carreiro et al. 2000, Gallo et al., 2004). In a larch plantation in Japan, Kunito et al. (2009) found suppression of phenol oxidase following N fertilization, but they sampled for only 30 days following fertilization. In contrast, DeForest et al. (2004), found a suppressive effect of fertilization on peroxidase and phenol oxidase in the forest floor (and peroxidase only in the mineral soil), but enzyme activities rebounded within 5 months of the initial fertilization. An important distinction between these previous studies and mine is the nature of the fertilization regime. The above studies were intended to simulate nitrogen deposition resulting from human activities (for details, see Waldrop et al., 2004), whereas the purpose of my study was to investigate large-scale fertilization as a forest management practice. My plots received a large one-time application of urea pellets; most of the above studies received smaller and more frequent applications of nitrate-containing fertilizers.  41 The rebound of ROM enzyme activity by the end of the 60-day sampling period in this study may be a consequence of ammonium and nitrate returning to pre-fertilization levels in the fertilized plots by the end of the study period. The repeated fertilizer applications in other studies may have prevented the resumption of microbial enzyme activities by maintaining N availability. After Day 14 ammonium concentrations in the mineral soil (where the suppression of the ROM enzymes was seen) declined to nearly background levels, indicating that N may have again become limiting. My other hypothesis related to the effects of fertilization on C turnover was that N amendment will increase the activity of enzymes that degrade labile organic matter (LOMNAGase, cellobiohydrolase and betaglucosidase). This hypothesis was not supported by this study, indeed in the forest floor the activities of the three LOM enzymes were reduced by fertilization, and in the mineral soil there was no effect of fertilization on the activities of these enzymes. LOM enzyme activities in the urea-treated forest floor plots followed a similar pattern to ROM, with the lowest activity rate at Day 14. NAGase is a chitinase, whose activity has been shown to be reduced by high N availability (Bragazza et al., 2006). This probably indicates that at Day 14 nitrogen availability was highest, which is also when the suppression of the ROM enzymes was strongest. In contrast, the activities of betaglucosidase and cellobiohydrolase are widely believed to be N-limited (Fog, 1988). The activity rates of the three LOM enzymes were highly correlated to one another, so it is possible that the other two enzymes were lowered as a by-product of suppression of NAGase. Another plausible explanation is that decreased activity of peroxidase (this study, DeForest et al., 2004, Colman et al., 2007) resulted in increased presence of soluble phenols in the soil. Phenols interfere with the activity of LOM enzymes (DeForest et al., 2004, Hobbie, 2008). Soluble phenol concentrations may be further increased by NH4+ being complexed into organic materials to form soluble phenols, and formation of these compounds may also co-opt available C, causing labile C to become limiting to soil microbes (Fox, 2004). Activity of LOM enzymes in both soil layers was highest in the young stand, followed by the clearcut and then the mature forest. This may be attributable to the young stand having more understory vegetation than the mature forest, and it being composed of herbaceous plants, while woody shrubs and ferns dominated the mature forest. Herbaceous plant litters have higher cellulose content than needle litter (Prescott, 2005), which would stimulate activity of LOM enzymes. The intermediate activity in the clearcut may reflect it having smaller quantities of litter input, especially from the young trees.  42 4.2 NITROGEN TRANSFORMATIONS Net ammonification results were erratic, probably as a result of high microsite variability. When the time series was averaged together, net ammonification was reduced or unchanged by urea application. If ammonium pools are depleted due to rapid nitrification (Forge and Simard, 2001) the net ammonification rate will be negative. Ammonification rates were negative in both fertilizer treatments in the clearcut, and in the urea-treated soils in the mature forest. If high nitrification is the cause of negative ammonification rates, this supports the hypothesis that increases in nitrification rate will be largest (and fastest) in the clearcut, and that nitrification will be increased most by the urea treatment. However, measured net nitrification rates were much smaller than net ammonification, so it is unlikely that nitrification (and subsequently denitrification) accounted for all of the „missing‟ ammonium. Other ammonium sinks that could make up some of the difference include microbial uptake, chemical immobilization, and volatilization. Microbial uptake, DON and nitrification did account for most of the missing ammonium. The importance of abiotic chemical immobilization of NH4+ is uncertain, but Johnson et al. (2000) suggest that the relative importance is positively correlated to N concentration, so this may have been the fate of some of the added N. Chemical immobilization of nitrate is unlikely to be an important N sink (Colman et al., 2007). The importance of volatilization is uncertain; it may have occurred in the first days following urea application due to high ammonium concentration and increased pH (data not shown) due to urea addition (Vitousek and Melillo, 1979). However, volatilization is inhibited by moisture, and the days following fertilization were rainy and the soils were wet, so volatilization losses of NH4+ were probably small. As predicted, nitrification was increased by fertilization, but this effect was only significant in the clearcut site. This supports the hypothesis that the clearcut would respond most strongly to fertilization. As also predicted, nitrification in all sites was increased more with urea than with slow-release urea. Jassal et al. (2008) found that the total amount of N2O released accounted for 5% of the fertilizer applied in both the urea and slow release urea treatments. Therefore, denitrification may also account for some of the missing N in this study. 4.3 MANAGEMENT IMPLICATIONS Fixation of atmospheric N to make the commercial fertilizer used in large- scale fertilization requires the consumption of large amounts of fossil fuels, with potentially large global warming potential. To sell or trade carbon credits under future carbon regulatory treaties the “carbon equivalents” of greenhouse gases released as a result of fertilization such as NOx from incomplete denitrification and CO2 from manufacture, transport and  43 spreading of fertilizer – must not exceed forest carbon gains. This study addresses the question of whether or not N-fertilization of coastal Douglas-fir forests would result in increased soil C storage through the suppression of microbial enzymes that degrade organic matter. The results provide some evidence in support of this hypothesis; ROM enzymes appeared to be suppressed by fertilization, however, the effect appeared to be short-lived by the end of the 60-day study period enzyme activity levels in the control and fertilized plots were not significantly different. The peculiar pattern of suppression – a spike in activity levels in the control plots in the middle of the study period – also makes it difficult to predict the longevity of the fertilization effect. Therefore, whether or not N fertilization is a useful management technique for increasing soil carbon storage in these forests requires further study. The N dynamics measured following fertilization in this chronosequence study provide some insights into the optimal fertilization regime for coastal Douglas-fir forests. A forest manager seeking to enhance tree growth should seek to reduce N limitation without saturating the system, as saturation increases nitrate leaching and denitrification (Wallenstein et al., 2006), and may increase the proportion of N that is complexed into recalcitrant inorganic compounds (Johnson et al., 2000) where it is not readily available to trees. Fertilization of the clearcut stand would appear to be the least efficient application of fertilizer tested here; high nitrification under both fertilizer treatments in both soil layers indicates that the clearcut was quickly N saturated. Additionally, in a study of a forest in interior BC, Forge and Simard (2001) observed that fertilization in clearcuts appeared to benefit weeds the most. In the two older stands, the urea treatment resulted in a nonsignificant increase in nitrification in the forest floor, and the mature stand showed a small increase in nitrification in the mineral soil due to percolation to the mineral soil. Both stands had a much smaller increase in nitrification following application of slow-release urea, indicating a lower degree of saturation. This suggests that the best option for forest fertilization is to fertilize either young (in this case, 18 years old) or mature (57 years old) stands using the slow-release fertilizer. 4.4 LIMITATIONS This study has a few limitations; some are inherent to the experimental design and a few are a result of how the experiment was carried out. Inherent to the design, many of the measurements made in this study are proxy measures for the actual interest of the study. For example, decomposition and carbon budgets are a primary interest, but enzyme activities are measured as a proxy for decomposition potential. Enzyme measures are commonly used in this way to address larger scale questions (Sinsabaugh, 1994). Actual C  44 flux and denitrification are measured in a related, concurrent study using soil CO2 efflux chambers and eddy covariance (e.g. Jassal et al., 2008). A persistent complication during data analysis was high microsite variability. The high microsite variability detected may have been exacerbated by uneven fertilization fertilization was done by hand, and, indeed, uneven application of fertilizer is the bane of many forest studies, with no simple solution. Fortunately, many of the analyses done in this study had very high n. For example, an analysis comparing fertilizers and soil layers had an n of 72 when the time series, stand ages, and replicates were averaged. However, some comparisons, such as between fertilizers at a given time in a given stand, were impractical due to low n. This was particularly true in measures plagued by high variability, such as net ammonification and net nitrification, which were measured by pairing samples. Variability between these two samples would be recorded as being the result of either ammonification or nitrification. The negative effects of microsite variability on experimentation could be minimized by mixing soil from multiple samples to make a single composite sample. For measurements using paired samples each sample could simply be „split‟, and re-incubate half of it, minimizing variation between pairs. 4.5 RECOMMENDATIONS It would be useful to determine whether or not there is a minimum threshold of available N to cause the suppression of microbial enzyme activities, and if there is a critical threshold of N-availability, what level of fertilization with slow-release urea would be required to achieve it. This would provide a useful target, if N-fertilization is being considered as a means of sequestering additional C in soils.  45  5 CONCLUSIONS Which fertilizer is best? The results of this study suggest:   Slow-release is recommended over urea for broad-scale application due to lower potential for leaching and denitrification.    Fertilizer should be applied to older stands, not clearcuts, because older stands have lower nitrification rates and decreased likelihood of leaching..  Will N amendment increase forest soil C storage through the mechanism of inhibiting enzymes involved in decomposition of recalcitrant organic matter?   Ligninases were suppressed, but the effect appeared to be temporary.    Therefore, the results of this study do not suggest that N amendment will substantially increase forest soil C storage by this mechanism.    Future studies will assess other possible mechanisms of increased soil C storage following fertilization.  46  6 APPENDICES APPENDIX A - ANOVA TABLES  ANOVA TABLES Ammonification Source  DF  Type III SS  Mean Square  F Value  P Value  SITE  2  5.39080946  2.69540473  12.45  0.0073  FERT  2  11.20372865  5.60186432  9.79  0.0030  SOIL_TYPE  1  0.02160294  0.02160294  0.04  0.8479  SITE*FERT  4  6.85566503  1.71391626  3.00  0.0628  SITE*SOIL_TYPE  2  7.86160123  3.93080061  7.05  0.0123  FERT*SOIL_TYPE  2  2.47601266  1.23800633  2.22  0.1593  Source  DF  Type III SS  Mean Square  F Value  P Value  SITE  2  0.00352374  0.00176187  2.73  0.1433  FERT  2  0.00391026  0.00195513  2.69  0.1083  SOIL_TYPE  1  0.00123371  0.00123371  2.85  0.1224  SITE*FERT  4  0.00250548  0.00062637  0.86  0.5139  FERT*SOIL_TYPE  2  0.00075182  0.00037591  0.87  0.4492  Nitrification  47 NAGase Source  DF  Type III SS  Mean Square  F Value  P Value  SITE  2  7004569  3502284  2.10  0.2030  FERT  1  2575181  2575181  1.64  0.2474  SOIL_TYPE  1  6752342  6752342  3.23  0.1324  SITE*FERT  2  3287051  1643525  1.05  0.4071  FERT*SOIL_TYPE  1  186757  186757  0.09  0.7771  Source  DF  Type III SS  Mean Square  F Value  P Value  SITE  2  1408661  704330  2.85  0.1351  FERT  1  324629  324629  1.26  0.3045  SOIL_TYPE  1  1367657  1367657  2.57  0.1696  SITE*FERT  2  870993  435496  1.69  0.2616  FERT*SOIL_TYPE  1  11624  11624  0.02  0.8882  Source  DF  Type III SS  Mean Square  F Value  P Value  SITE  2  16349373  8174686  3.90  0.0822  FERT  1  4607893  4607893  1.88  0.2190  SOIL_TYPE  1  18702522  18702522  3.86  0.1068  SITE*FERT  2  3849240  1924620  0.79  0.4972  FERT*SOIL_TYPE  1  43590  43590  0.01  0.9281  Cellobiohydrolase  Betaglucosidase  48 Peroxidase Source  DF  Type III SS  Mean Square  F Value  P Value  SITE  2  203151343  101575671  0.64  0.5580  FERT  1  15838310  15838310  0.16  0.7030  SOIL_TYPE  1  2731524726  2731524726  31.93  0.0024  SITE*FERT  2  30802725  15401362  0.16  0.8592  FERT*SOIL_TYPE  1  449913575  449913575  5.26  0.0704  Source  DF  Type III SS  Mean Square  F Value  P Value  SITE  2  10646518  5323259  1.75  0.2526  FERT  1  563566  563566  0.07  0.7963  SITE*FERT  2  2796861  1398430  0.18  0.8391  SOIL_TYPE  1  52219979  52219979  29.39  0.0029  FERT*SOIL_TYPE  1  45624619  45624619  25.68  0.0039  Phenol Oxidase  49 APPENDIX B – PHOTOS OF FIELD SITES  Clearcut  Young  Mature  50 APPENDIX C – SELECTED MEAN VALUES Source  DF  Type III SS  Mean Square F Value  P Value  SITE  2  1.28079929  0.64039964  0.1327  2.88  The following values are means of stand age and replicate samples.  FERT  SOIL  TIME  pH  CONTROL  FF  1  6.43  CONTROL  FF  7  5.195  CONTROL  FF  28  5.26875  UREA  FF  0  5.93  UREA  FF  1  6.864  UREA  FF  7  5.98  UREA  FF  14  6.35  UREA  FF  28  6.015  CONTROL  MS  1  5.6944444  CONTROL  MS  7  5.438  CONTROL  MS  28  5.5333333  UREA  MS  0  5.7  UREA  MS  1  5.98625  UREA  MS  7  6.37  UREA  MS  28  5.8775  51  APPENDIX D – CORRELATION MATRICES FOR ENZYME DATA The SAS System The CORR Procedure 5 Variables:  Cellobioside  Nagase  Glucoside  Phenox  Perox  Simple Statistics Variable  N  Mean  Std Dev  Sum  Min  Max  Cellobioside  131  583  516  76388  0  2492  Nagase  131  1485  1225  194540  24  6670  Glucoside  131  1777  1449  232826  0  6913  Phenox  131  1099  1985  144014  0  10401  Perox  131  11283  11192  1478065  0  65763  Pearson Correlation Coefficients, N = 131 Prob > |r| under H0: Rho=0  Cellobioside  Cellobioside  1.00000  Nagase  0.94880  Nagase  Glucoside  Phenox  Perox  1.00000  <.0001  Glucoside  Phenox  Perox  0.95857  0.94604  1.00000  <.0001  <.0001  0.03981  0.04957  -0.01814  0.6516  0.5740  0.8371  0.17974  0.23344  0.12041  0.5034  0.0400  0.0073  0.1707  <.0001  1.00000  1.00000  52  APPENDIX E – CORRELATION MATRICES FOR NITROGEN DATA The SAS System The CORR Procedure  8 Variables:  Ammonia  Nitrate  Ammonification  Nitrification  MicroNup  Microbial_N  DON  DON_change  Simple Statistics Variable  N  Mean  Std Dev  Min  Max  Ammonia  188  0.37337  0.86095  0.00136  6.22383  Nitrate  188 0.00080  0.00388  0  0.04561  Ammonification 181 -0.03565  0.50738  -3.00319  2.41869  Nitrification  181 0.00582  0.02918  -0.00865  0.33786  MicroNup  189 0.04465  0.56365  -2.26049  5.62306  Microbial_N  146 0.07500  0.18481  0  1.21500  DON  106 14.03242  21.95473  0  65.00000  DON_change  41  25.83178  -1.37056  65.00000  23.39677  53 Pearson Correlation Coefficients Prob > |r| under H0: Rho=0 Number of Observations  Ammonia  Ammonia  1.00000  Nitrate  -0.01469  Nitrate  Ammonification Nitrification  1.00000  0.8414  Ammonification- 0.56022  Nitrification  MicroNup  Microbial_N  DON  DON_change  -0.00856  1.00000  <.0001  0.9090  0.14238  0.17650  -0.09851  0.0559  0.0175  0.1870  0.32535  -0.03344  -0.13791  0.17872  <.0001  0.6531  0.0672  0.0173  0.19201  0.08445  -0.08979  -0.04589  0.0230  0.3212  0.3040  0.5999  -0.12294  0.03918  0.08611  -0.09363  0.2093  0.6901  0.3967  0.3566  -0.07796  -0.07458  0.07270  0.11898  0.6280  0.6431  0.6515  0.4587  1.00000  54 Pearson Correlation Coefficients Prob > |r| under H0: Rho=0 Number of Observations  MicroNup MicroNup  1.00000  Microbial_N  -0.38533  Microbial_N  DON  DON_ change  1.00000  <.0001  DON  DON_change  -0.03300  -0.05271  1.00000  0.7420  0.6917  0.25508  -0.26346  0.24786  0.1171  0.1005  0.1182  1.00000  55  7 WORKS CITED Berg, B. and E. 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