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Some ecological effects of operations used to convert densely stocked lodgepole pine stands into young… Blackwell, Bruce Alan 1989

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SOME ECOLOGICAL EFFECTS OF OPERATIONS USED TO CONVERT DENSELY STOCKED LODGEPOLE PINE STANDS INTO YOUNG PINE PLANTATIONS IN WEST CENTRAL BRITISH COLUMBIA by BRUCE ALAN BLACKWELL Bachelor of Science, University of British Columbia, 1984 A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES (Department of Forestry) We accept this thesis as conforming to the required standard THE UNIVERSITY OF BRITISH COLUMBIA September, 1989 © BRUCE ALAN BLACKWELL , 1989 0 In presenting this thesis in partial fulfilment of the requirements for an advanced degree at the University of British Columbia, I agree that the Library shall make it freely available for reference and study. I further agree that permission for extensive copying of this thesis for scholarly purposes may be granted by the head of my department or by his or her representatives. It is understood that copying or publication of this thesis for financial gain shall not be allowed without my written permission. Department of ^S^TTZ^ The University of British Columbia Vancouver, Canada Date ^ h = ^ ^ £ ^ /<?,/??9 DE-6 (2/88) i i ABSTRACT Large areas of the interior of B.C. are covered with densely stocked lodgepole pine {Pinus contorta) forests, 40-60 years old. These forests are growing very slowly and some are not considered to be capable of contributing to future timber supplies. When stands have densities around 20,000 stems/ha or greater they are unlikely to produce merchantable trees within a reasonable period of time without treatment. To bring the more repressed stands back into timber production it is necessary to clear them and regenerate new ones with a more desirable stocking level (rehabilitation). A study of the ecological effects of rehabilitation treatments on such stands in the Sub-Boreal Spruce Zone in the Lakes Forest District, west central B.C. was begun in July, 1985. This study quantified the effects of treatments on fuels, ecosystem nutrient status, associated vegetation, mineral soil and planted lodgepole pine seedlings to help assess the most economically and ecologically desirable method of treatment. The study investigated the effects of two treatments - mechanical knocking down of trees followed by broadcast slashburning and mechanical knocking down followed by windrowing then burning - and 4 sets of burning conditions designed to give 4 different types of burning severities based on fuel consumption. Each treatment/burning severity was replicated 2-3 times on plots approximately 1 ha in size. The knocking down commenced in late 1985 and 3 of 4 sets of burns were carried out during spring and summer 1986. The remaining set of burns was carried out during spring, 1987. It was found that over the range of burning conditions used, windrow burns consumed similar amounts of slash fuels, unlike broadcast burns which consumed greater amounts of i i i slash fuel as the fuel moisture codes of the Canadian FWI system increased. Forest floor consumption was generally only a small proportion of the total fuel consumption. Total nutrient losses decreased in the order N > S > P > Mg > Ca > K > Na. For the windrow burns, generally > 90% of all nutrients present in organic matter were lost during the burning. Nutrient quantities lost from windrow burns were significantly greater than quantities lost from broadcast burns. Windrow burn nutrient losses were generally greater than those lost from operational broadcast slashburns and were more similar to reported losses from whole tree harvesting operations. Some increases and some decreases in nutrient quantities were observed in the surface mineral soil in both the treatments. The greatest changes in soil nutrients were generally observed for Ca and N . Fire severity significantly influenced the loss of both total and mineralizable N , while both site preparation treatment and fire severity influenced the loss of S. Relatively large increases in mineral soil nutrient quantities were observed beneath windrows. The mineral soil inter-windrow areas, however were found not to be greatly affected by the treatment. The large increases beneath windrows were attributed to the burning of large fuel accumulations. Lodgepole pine seedling survival after two years was highest on areas between windrows and lowest on areas beneath windrows. The better survival in areas between windrows was attributed to improved soil temperature, while poorer survival in windrows was attributed to moisture stress caused by the creation of a hydrophobic layer or seedlings being planted in ash rather than mineral soil. Total height, height increment and basal diameter of lodgepole pine seedlings were greater on areas between windrows and least on broadcast burned areas. iv Biomass of understory vegetation during the first two post-treatment growing seasons decreased in the order: herbs > shrubs > mosses. Neither site preparation treatment nor fire severity appeared to have a significant effect on herb, shrub, or moss biomass during the first two post-treatment growing seasons. For individual species, biomass decreased in the order: Epilobium > Cornus > Spirea > Rosa > Linnaea. V TABLE OF CONTENTS Page ABSTRACT ii LIST OF TABLES viii LIST OF FIGURES xi A C K N O W L E D G E M E N T S xii C H A P T E R 1: INTRODUCTION TO T H E STUDY 1 Introduction 2 Study Objectives 5 Study Area , 6 Methods 10 C H A P T E R 2: EFFECTS OF TREATMENTS ON FOREST FUELS 15 Introduction 16 Literature Review: Slashburning effects with specific reference to lodgepole pine 17 Methods 25 Results and Discussion 35 C H A P T E R 3: EFFECTS OF TREATMENTS ON NUTRIENTS 53 Introduction 54 Literature Review: Effects of slashburning on chemistry and nutrients 55 Methods 66 Results and Discussion 74 vi Page CHAPTER 4: EFFECTS OF TREATMENTS ON PLANTED L O D G E P O L E PINE SEEDLINGS A N D ASSOCIATED V E G E T A T I O N 118 Introduction 119 Literature Review: Effects of treatments on lodgepole pine regeneration 120 Methods 122 Results and Discussion 125 C H A P T E R 5: R E S E A R C H S U M M A R Y A N D OPERATIONAL RECOMMENDATIONS 137 Treatment effects on fuels 138 Treatment effects on nutrients 139 Treatment effects on lodgepole pine seedlings and associated vegetation 142 Implementation of study results 144 Research Recommendations 146 BIBLIOGRAPHY 147 Appendix 2-1 Assessment of costs of conducting the site preparation, burning and mop-up operations in the experimental treatments 157 Appendix 2-2 Pretreatment lodgepole pine, understory vegetation, and forest floor biomass in the experimental plots 163 Appendix 2-3 Fuel consumption, pre and postburn slash fuel loads, in the experimental plots 168 Appendix 3-1 Pretreatment nutrient concentrations in lodgepole pine components, understory vegetation and dead woody materials 172 Appendix 3-2 Pre- and postburn nutrient concentrations in forest floor and slash 176 Appendix 3-3 Pretreatment nutrient quantities in lodgepole pine biomass components 182 vii Page Appendix 3-4 Pretreatment biomass and nutrient quantities in understory vegetation in the experimental plots 191 Appendix 3-5 Pretreatment biomass and nutrient quantities in forest floor and dead woody material in the experimental plots 196 Appendix 3-6 Postbura biomass and nutrient quantities in forest floor and dead woody materials in the experimental plots 203 Appendix 3-7 Pre and postbura nutrient quantity summary for the experimental plots 211 Appendix 3-8 Prebura and one year postbura nutrient concentrations in the surface 15 cm of mineral soil in the experimental plots 221 Appendix 3-9 Prebura and one year postbura mineral soil mass of the < 2 mm fraction and nutrient quantities of the surface 15 cm of mineral soil in the experimental plots 226 Appendix 3-10 Analysis of variance to test the significance of the effects of treatment type (windrow burn vs knockdown and broadcast burn) and fire severity on nutrient changes both absolute and relative, in slash, forest floor and slash and forest floor combined 231 Appendix 3-11 Tukey's test of significance of the effects of treatment type (windrow burn vs knockdown and broadcast burn) and fire severity on nutrient changes, both absolute and relative, in slash, forest floor and slash and forest floor combined 256 Appendix 4-1 Two-way analysis of variance results for seedling responses 262 Appendix 4-2 Two-way analysis of variance for 1988 vegetation biomass 265 Appendix 4-3 Two-way analysis of variance results for 1988 herb, shrub, moss and total biomass 269 Appendix 4-4 The average height, height increment, basal diameter and survival of lodgepole pine seedlings planted in the experimental plots at the end of the first and second growing season 272 Appendix 4-5 Summary of the biomass and percent cover of the most important understory species during the first and second growing seasons in each of the experimental plots 275 Appendix 4-6 List of pre and postbura plant species present in the experimental plots 281 Appendix 4-7 Layout of tree seedling assessment plots within the study area 283 LIST OF TABLES Page 1-1. Tree density in the treatment plots in the study area 9 1- 2. Canadian Fire Weather Index System codes and indices for each burning period,together with prevailing weather conditions and severity prescriptions 14 2- 1. Biomass regression equations used to estimate tree component biomass 28 2-2. Relative densities for lodgepole pine dead woody materials in the study plots 30 2-3. Preburn and postburn fuel loads (kg/m2) for the experimental plots 36 2-4. Pretreatment mass of surface dead woody materials in the study plots 37 2-5. Average mass of lodgepole pine stemwood, stembark, needles, branches, dead branches and roots in each of the 3 experimental blocks 3_8 2-6. Average preburn, postburn mass and consumption of forest floor in the experimental plots 40 2-7. Average understory vegetation mass, by component in each of the experimental blocks 41 2-8. Summary of fuel consumption during the burns in the experimental plots 42 2-9. Average preburn, and postburn mass of slash fuels in the experimental plots 44 2-10. A N O V A table for the influence of fire severity and site preparation (TRT) on total fuel consumption 45 2-11. Correlations between slash consumption and initial slash load by slash diameter 47 2-12. Forest floor depth, depth-of -burn and postburn mineral soil exposure for the broadcast burns in the experimental plots 48 2-13. Correlations between forest floor depth-of-burn and slash consumption and initial forest floor depth for the broadcast burn plots 50 ix Page 3-1. Pretreatment nutrient quantities (kg/ha) and mass of lodgepole pine, understory vegetation, dead woody materials, forest floor and mineral soil averaged over all experimental plots 75 3-2. Estimated nutrient changes (kg/ha) in the forest floor following the burns in the experimental plots 78 3-3. Estimated relative nutrient changes (%) in the forest floor following the burns in the experimental plots 80 3-4. Correlations between nutrient changes in forest floor and fuel consumption variables in broadcast burn plots 91 3-5. Immediate and one year postburn estimated nutrient changes (kg/ha) in the forest floor caused by broadcast burn treatments 93 3-6. Estimated nutrient losses (kg/ha) from slash during the burns in the experimental plots 96 3-7. Estimated relative nutrient losses (%) from slash during the burns in the experimental plots "97 3-8. Correlations between nutrient losses in slash and fuel consumption variables for broadcast burn plots 99 3-9. Correlations between nutrient losses in slash and fuel consumption variables for windrow burn plots 101 3-10. Correlations between nutrient losses in slash and fuel consumption variables for windrow and broadcast burn plots combined 102 3-11. Estimated total nutrient losses (kg/ha) during the burns in the experimental plots 105 3-12. Estimated percentage nutrient losses from organic matter during the burns in the experimental plots 106 3-13. Correlation coefficients for total and relative nutrient losses and fuel consumption variables for broadcast burn plots 108 3-14. Correlation coefficients for total and relative nutrient losses and fuel consumption variables for windrow burn plots 109 3-15. Correlation coefficients for total and relative nutrient losses and fuel consumption variables for broadcast and windrow plots combined 110 X Page 3-16. Pre and post-treatment surface 0-15 cm mineral soil bulk density (g/cm3) averaged for the experimental plots 113 3- 17. Differences between the 1-year postburn and prebura quantity of nutrients in the surface 0-15 cm of mineral soil (kg/ha) in the experimental plots 114 4- 1. The average height, height increment, basal diameter and survival for planted lodgepole pine seedlings in the experimental plots during the first two growing seasons 126 4-2. The average height, height increment, basal diameter and survival at the end of the second growing season of lodgepole pine seedlings planted in the experimental plots, averaged by site preparation treatment and fire severity 127 4-3. Summary of the biomass of the most important understory species in the experimental plots during the second growing season, averaged by site preparation treatment and fire severity 132 4-4. Shrub, herb, and moss biomass during the first and second post-treatment growing seasons averaged by site preparation treatment and fire severity 134 xi LIST OF FIGURES Page 1-1. Location of the study area 7 1-2. Layout of experimental plots 12 3-1. Site preparation and fire severity treatment interaction for forest floor phosphorus changes 82 3-2. Site preparation and fire severity treatment interaction for forest floor potassium changes 83 3-3. Site preparation and fire severity treatment interaction for forest floor sodium changes 84 3-4. Site preparation and fire severity treatment interaction for forest floor magnesium changes 85 3-5. Site preparation and fire severity treatment interaction for forest floor calcium changes ...86 3-6. Site preparation and fire severity treatment interaction for forest floor sulphur changes 87 3-7. Site preparation and fire severity treatment interaction for phosphorus jnineral soil changes 88 3-8. Site preparation and fire severity treatment interaction for potassium mineral soil changes 89 3-9. Site preparation and fire severity treatment interaction for magnesium mineral soil changes 90 xii ACKNOWLEDGEMENTS I would like to thank Dr. Michael Feller, the chairman of my supervising committee, for support and direction provided throughout this study. This project would not have been possible if not for the work of Mr. Richard Trowbridge. I would like to thank him for his dedication to making this study a success and the guidance he has provided throughout all phases of my graduate study. I would also like to thank the other members of my committee Drs. Tim Ballard and Karel Klinka for their advice on this thesis project. I would like to thank all Lakes Forest District staff including; Bill Davidson, Robert Krause, Neil Endacott, and Allison Patch, who helped organize and carried out all operational aspects of the project, including site preparation, burning, mop-up and planting. Bruce Hutchinson, Prince Rupert Forest Region fire suppression coordinator, deserves special thanks for the professional way in which he conducted burning operations. Thanks are also due to A l Gorley (District Manager, Morice Forest District), Paul Pasnik (District Manager, Port Alberni Forest District), Anne Macadam and Dave Yole, of the Research Branch Prince Rupert Forest Region, who provided direction and field assistance during the project. Many individuals from U.B.C. provided invaluable assistance with field sampling laboratory and data analyses. I am grateful to Denise Blackwell, Glyn Davies, Mark Duscher, Jim Haberl, Gail Lyttle, Dermot McCarthy, Neil Neilson, Audrey Pearson, Cam Penfold, Sandra Thomson, Cathy Turner, Mailis Velenius, Vicki Vernier, and Barry Wong. I would especially like to thank Heather Jones for assistance in supervision of field sampling and laboratory analyses. I also wish to thank Drs. Peter Marshall, Bob Green and Reid Carter for advice on statistical analyses. Financial support for this study was provided by the British Columbia Ministry of Forests and the Canadian Forestry Service under the Canada-British Columbia Forest Resource Development Agreement (1985-1990). This support is gratefully acknowledged. CHAPTER 1  INTRODUCTION TO THE STUDY INTRODUCTION 2 The recognition of lodgepole pine (Pinus contorta Dougl.) as an important commercial species has increased significantly since the early 1960's as the last old growth forests of British Columbia are liquidated. The species currently accounts for 20 and 40 percent of the annual harvest in British Columbia and Alberta respectively (Kennedy 1985), while in the U.S., the annual lumber harvest of lodgepole pine is between 20-70 percent in those states which harvest lodgepole pine, and represents 16 percent in the Rocky Mountain States (van Hooser and Keegan 1985). The literature on the distribution and botanical characteristics of lodgepole pine has recently been reviewed (Critchfield 1980, Wheeler and Critchfield 1985). It is the most widely distributed conifer species in Western North America with a range spanning 33 degrees of latitude and 35 degrees of longitude and over 3900 m of elevation. The fact that this conifer forms pure or nearly pure stands as a result of repeated fires is by no means a coincidence as strong evidence suggests that cone serotiny associated with many lodgepole pine stands is largely an evolutionary response to frequent fires (Perry and Lotan 1979). Cone serotiny and the early reproductive habit of this species often lead to immense cone reserves which, following a fire release millions of seeds per hectare (Wheeler and Critchfield 1985). After germination the number of seedlings remains high with competition resulting in only a small reduction in the total number. Stand densities exceeding 100,000 stems/ha have been observed in young stands (Smithers 1957) and as many as 25,000 stems/ha have been reported for a 70-year-old stand (Mason 1915). 3 The regeneration of lodgepole pine in extremely high densities is not unique - western hemlock (Tsuga heterophylla (Ref.) Sarg.), amabilis fir {Abies amabilis (Dougl) Forbes), red alder [Alnus rubra Bong.) and black cottonwood (Populus trichocarpa Torr. and Grey) are also capable of regenerating dense stands (Keane 1985). The mechanism which causes "stagnant" or "repressed" growth of lodgepole pine is unclear with a number of studies finding inconclusive results. Mitchell and Goudie (1980) hypothesized that excessive respiration and a shortage of moisture may cause the entire growth system to slow down while Worrall et al. (1985) suggested that differences in the form and activity of the root systems is a potential cause of stagnation in lodgepole pine. Keane (1985), looking at a number of physiological processes and biomass allocation, suggested a complex pathway whereby the ratio of leaf arearsapwood area shifts as stand density increases, causing an increasing ratio of energy consuming to energy producing tissue in stagnant stands. As the trees grow the situation does not improve because of a reduction in available moisture and nutrients which leads to a reduction in foliage production which, in turn, reduces the amount of earlywood production. Large areas in the interior of B.C. are covered with densely stocked lodgepole pine. These forests are growing very slowly and are not considered to be capable of contributing to future timber supplies. It is considered desirable to bring these forests back into an optimal timber production potential to augment future timber supplies and help alleviate falldown effects. If stocking is not too dense the stands may respond well to thinning or spacing. However, when the stands have densities of around 20,000 stems/ha or greater they are unlikely to produce merchantable trees within a reasonable period of time. To bring such 4 stands back into timber production it is necessary to clear them and regenerate a new stand with a more desirable stocking level (rehabilitation). Attempts have recently begun to do this but the benefits and ecological effects of various possible rehabilitation treatments, particularly on subsequent tree growth, are unknown. Such densely stocked lodgepole pine areas are of particular concern in the Lakes Forest District within the Prince Rupert Forest Region where an estimated 86,000 ha of such 40-60 year old lodgepole pine occur. Rehabilitation of an estimated 20,000 ha of the 86,000 ha may be necessary in this one district alone (N. Endacott, B.C. For. Serv., Lakes Forest District: personal communication). Stands that are comprised of densely stocked lodgepole pine have several distinguishing characteristics. A vast majority have originated from wildfire and the volume produced by these severely overstocked stands is far below site potential. Foresters are currently faced with the dilemma of deciding what to do with such stands. In order to prepare these sites for new plantations, the current biomass from the stands must be removed. It appears that burning is the most appropriate and viable rehabilitation option available in the Lakes Forest District. Worrall et al. (1985), through casual examination of logdecks in the Prince George area, found no logs with large numbers of very narrow rings adjacent to the pith that would be present in a tree that had recovered from stagnation. They concluded that in nature, stagnant stands are destroyed by fire and a new stand is regenerated at lower densities, from the small quantity of cones present on stagnant trees. They suggested that the best management decision to rehabilitate these stands might well be to emulate nature and burn them. 5 A study of the effects of rehabilitation treatments, using prescribed fire, on such densely stocked lodgepole pine stands in the Lakes Forest District was begun in July 1985. STUDY OBJECTIVES The objectives of the study are twofold -1. To assess the economics, and quantify the effects on the site, of feasible site rehabilitation techniques for lodgepole pine stands which are considered too densely stocked to respond to thinning or spacing. 2. To quantify the effects of such treatments on subsequent development of lodgepole pine plantations. The present study is concerned primarily with the initial ecological effects of treatments on fuels, vegetation, soils and their nutrient status. To properly assess the feasibility and effectiveness of different operational treatments, information other than ecological is required, in particular economic data. Such data were collected and analysed and are given in Appendix 2-1. 6 STUDY AREA Location Field work for the study was conducted in an area located between Francois and Ootsa lakes, southwest of the town of Burns Lake in west central B.C. (Figure 1-1). The area contains several densely stocked lodgepole pine stands originating from fires in the 1930's. Physiography The study area is located at approximately 1050 m elevation on the Nechako plateau. It is a flat area of low relief, just slightly sloping (south aspect), surrounded by gently rolling country (Holland 1964). Climate The climate of the area is locally influenced by Ootsa Lake. The study area has a cold sub-boreal continental humid climate which is characterized by severe, snowy winters and relatively warm, moist and short summers. The mean annual precipitation is approximately 440 mm with an average snowfall of 1765 mm and mean frost-free period of approximately 67 days (Pojar et al. 1984). Geology The geology of the Nechako plateau is dominated by tertiary lava flows which cover older volcanic and sedimentary rocks of the Takla and Hazelton groups (Holland 1964). 8 The most common rock types of the area are basalts, andesites, rhyolites, tuffs, breccias, and granites (Pojar et al. 1984). Ice occupied the plateau surface leaving behind a pattern of grooves and drumlin-like ridges which parallel the ice flow. Near the vicinity of Ootsa lake, ice moved east- and northward to the Rocky Mountains. The retreat of the glaciers left many lakes and ponds scattered on the plateau surface. Soils Soils in the area are predominantly Brunisolic Grey Luvisols (Agriculture Canada Expert Committee on Soil Survey 1987) with Hemimor forest floors (Klinka et al. 1981). The study area soils are mainly well drained clay loams with 25 - 30% coarse fragments. However, some flat areas and depressions with very slow or without external drainage are imperfectly drained. The main characteristic of soils in the area are a discontinuous whitish leached layer (Ae) below the forest floor surface, a reddish brown surface horizon, (Bm/Bfj), and clay accumulation in the subsoil (Bt). Vegetation Two stands within the area were selected for study. These stands are considered unlikely to respond to thinning or spacing within a reasonable period of time. Tree density data for the stands are given in Table 1-1. These stands are considered typical of the densely stocked lodgepole pine stands within the Lakes Forest District and occur primarily within one ecosystem type - the Mesic bunchberry-moss ecosystem association (ecosystem unit SBSel/01) of the Subalpine Fir Subzone of the Sub-Boreal Spruce biogeoclimatic zone (Pojar et al 1984). Table 1-1. Tree density in the treatment plots in the study area. 9 Tree density (stems/ha) Living trees Standing dead trees Range Mean Standard Deviation Range Mean Standard Deviation Block 1 KB p l o t s WB p l o t s 16,400-47,000 13,800-31,400 26,000 19,700 9,700 6,200 200-6,400 400-1,800 2,500 500 2,200 500 Block 2 KB p l o t s UB p l o t s 10,400-28,400 14,600-33,200 17,600 19.900 5 , 700 6,100 200-4,200 200-6,000 1 ,600 2, 100 1 ,300 1 , 700 Block 3 KB p l o t s UB p l o t s 10,200-17,400 10,600-19,600 14,100 14,800 2,600 2,400 600-3,800 1 , 200-4 , 200 2.000 2,400 1,200 900 . Means and standard deviations were determined from 9 estimates K B WB = knock down and burn = windrow and burn 10 The shrub layer is dominated by Rosa acicularis, Spirea betulifolia and Vaccinium membranaceum which are all typically low lying. Cornus canadensis, Linnaea borealis, Arnica cordifolia and Lycopodium annotinum comprise the herb layer. The moss layer is composed primarily of a continuous carpet of Pleurozium schreberi and Ptilium crista-castrensis. METHODS Field Procedures Discussions with regional and district Forest Service staff indicated that two rehabilitation treatment techniques were operationally most feasible for the study stands. These techniques consisted of a combination of mechanical and slashburning treatments. Consequently, the treatments used in the study were as follows: K B - Knocking down the trees using a bulldozer, followed by broadcast burning of the slash (the knockdown and burn, or K B treatment). WB- Knocking down the trees using a bulldozer, followed by windrowing of the slash then burning of the windrows (the windrow and burn or WB treatment). Three experimental blocks were delineated within two stands in the study area. For each experimental block a control plot was delineated which was to have been left untreated for the duration of the study. Unfortunately, one of the control plots was spaced during Spring, 1986. The rectangular shaped blocks, were each approximately 6 ha in size. A bulldozer trail 11 was constructed around the perimeter of each block during the summer of 1985. Within each of these blocks six treatment plots, each approximately 1 ha in size, were delineated. Three of these plots were randomly assigned to be given the K B treatment while the remaining three were assigned to be given the WB treatment. Thus, there were 9 K B plots and 9 WB plots (Figure 1-2). The knocking down part of the K B and WB treatments was carried out in September and November of 1985, respectively. The original experimental design involved burning three randomly selected K B plots and three randomly selected WB plots on each of 3 different occasions with each occasion being characterized by a different burning severity. In this way the effects of three different levels of burning severity were to be studied. However, it was found to be operationally feasible to burn only 4 or 5 randomly located plots during any one burning period. In addition, fuel moisture prediction problems encountered in attempting the first set of burns in relatively fresh slash suggested it would be interesting to compare burning of fresh versus one year old slash under similar fire weather conditions. Consequently, the final experimental design involved burning 2-3 K B or WB plots on each of four occasions. The burns on these occasions were characterized as 1) low severity in fresh slash, 2) low severity in cured slash, 3) moderate severity, and 4) high severity. During 1986, plots were burned on 3 occasions - 29-30 May (low severity in fresh slash), 28-29 June (moderate severity), and 20 July (high severity). One plot was accidentally burned during a B.C. Forest Service hazard abatement project in October, 1986. The remaining 4 plots were burned during spring 1987 - May 20 (low severity in cured slash). The layout of the burned plots is given in Figure 1-2. Figure 1-2 Layout of experimental plots. 12 Block 3 (plots 13-18) Block 1 Block 2 (plots 9-12) Q_ plot number @> water hole • broadcast burn plots Ez3 windrow burn plots low impact burns ^ moderate impact burns f5J high impact burns @ accidentally burned plot 13 The prevailing weather and the Canadian Forest Fire Weather Index (FWI) System codes and indices for each of the burning days are given in Table 1-2. Fire weather data were obtained from an on-site weather station. A l l FWI system codes and indices were calculated using the most recent FWI System equations (Van Wagner and Pickett 1985). Prescriptions for the burns were designed using the Prescribed Fire Predict or/Planner (Muraro, 1975), to give different fire severities ranging from what has been designated as "low" to what has been designated as "high". Due to persistence of frozen forest floors after snow had disappeared and the presence of uncured fuels, the prescriptions and FWI System moisture codes proved unreliable in early May (Trowbridge and Feller 1988). The 29-30 May burning period was the first opportunity to achieve reasonable ignition and combustion. The calculated FFMC, D M C and D C are given for the May burning period but they are not considered to accurately reflect fuel moisture conditions. The true values are considered to be lower than the calculated values. The prescriptions for the 1987 low severity burns were similar to that for the 1986 low severity burns. The following chapters report on the treatment effects on fuels, ecosystem nutrient status, plant competition and development of planted lodgepole pine seedlings. 14 Table 1-2. Canadian Fire Weather Index System codes and indices for each burning period, together with prevailing weather conditions and severity prescriptions. Date P l o t s Time Temp R . H . Ui nd F FMC DMC DC I S I BUI FWI Burned (DST) (°C) (%) (km/h r) Low s e v e r i t y burns i n f r e s h s l a s h (1986) Hay 29 2,10,7 1800-2100 14-19 41-58 15-16 85-87 19 110 6 26 1 0 May 30 1 7 1900 19 24 6 88 21 1 1 5 6 29 1 1 PRESCRIPTION <10 78-86 <15 <1 00 Low s e v e r i t y burns i n cured s l a s h (1987) May 20 1,3,4,5 1700-2100 7-16 27-52 0-9 76-77 18 82 1 24 2 PRESCRIPTION <1 0 78-86 <1 5 <1 00 Moderate s e v e r i t y burns (1986) Jun 28 8,11 1900-2100 16-21 44-53 0-13 89-90 23 188 7 35 14 Jun 29 12,16 2100 17 35 23 88 26 195 8 44 18 PRESCRIPTION <10 80-86 15-25 150- 200 High s e v e r i t y burns (1986) J u l 20 9,13 2000 17-23 41-58 15-18 82-84 42 317 4 6 3 1 3 14,15,18 PRESCRIPTION <1 0 80-86 >30 >300 Windspeed is for a height of 10 m above the ground. F F M C = Fine Fuel Moisture Code, D M C = Duff Moisture Code, D C = Drought Code, ISI = Initial Spread Index, BUI = Buildup Index and FWI = Fire Weather Index. F F M C was adjusted to the time of the burn according to Anon. (1984). CHAPTER 2 EFFECTS OF TREATMENTS ON FOREST FUELS 16 INTRODUCTION Slashburning has been a common practice in British Columbia since the turn of the century. Originally slashburning was practised to reduce accumulations of fuels which created a significant fire hazard (hazard abatement). The evolution of slashburning saw its application broaden as the area of land clearcut throughout the province each year increased and the concern to improve areas for planting intensified. The advent of the prescribed fire predictor (Muraro 1975) and aerial ignition systems greatly improved both the economics and the appeal of slashburning. As the application of slashburning has increased so too has the concern of land managers and the general public with the potential effects of slashburning on forest productivity and the environment. This increased awareness and the growing need to address site-specific concerns has led forest managers to intensify their efforts to understand the resulting effects of slashburning. The site-specific effects of any slashburning operation are very dependent on the fuel complex of an area. Differences in fuel loading, fuel continuity and species composition all contribute to differences in burning response. Therefore the quantification of fuel changes caused by burning is critical to the understanding of resulting slashburning effects. As part of the study to rehabilitate densely stocked lodgepole pine in the Lakes Forest District, the effects of burning treatments on fuels were quantified to help assess the most economically and ecologically desirable method of treatment. 17 LITERATURE REVTEW-SLASHBURNING EFFECTS WITH SPECIFIC REFERENCE TO LODGEPOLE PINE Slashburning has been used (Feller 1982) to -1. reduce fire hazard 2. facilitate planting 3. provide an environment favourable to seedling establishment and growth 4. reduce brush competition or undesirable advance regeneration 5. control disease or insect problems 6. improve aesthetics 7. enhance browse or grazing potential 8. improve an area for use by some wildlife species, primarily ungulates Although slashburning is used frequently to achieve different management objectives, in many cases it is difficult to predict its effects. This is mainly the result of poor documentation of previous experiences and the variability that is encountered within and between different forest ecosystems. The role of fire in lodgepole pine ecosystems has been addressed in many studies investigating the life history and ecology of lodgepole pine forests (Brown 1975, Habeck 1976, Lotan et ah 1985, Perry and Lotan 1979, Smithers 1961, Wellner 1971). This particular species has the ability to exploit an environment in which fire is common. Therefore, it seems only logical that if managers are to be successful in the management of lodgepole 18 pine, strategies which simulate natural events should be utilized whenever possible. Effects of slashburning in British Columbia have been discussed in a number of reviews which have been summarized by Feller (1982). It is beyond the scope of this discussion to review all studies which have investigated fire effects. The following review focuses on the effects of slashburning on fuels, with particular reference to lodgepole pine. EFFECTS OF SLASHBURNING ON FUELS Fire severity Interpretation of the effects of different studies is often confused by inadequate definitions and the use of the terms "fire severity" and "fire intensity" to describe the nature of the fire being studied. The term "fire severity" has been used to indicate the overall effects of the fire on the ecosystem. However fire severity is often used interchangeably with "fire intensity." Brown and DeByle (1987) have defined fire severity as " the total effect of fire on the ecosystem including consumption of organic material, and mortality of plants and soil organisms," while fire intensity is defined as, " the heat pulse up from the fire and is frequently described as fire line intensity (kW/m) that relates empirically to flame length" (Byram 1959). Fire intensity influences the effects of fire severity by causing mortality and pulsing heat downward (Brown and DeByle 1987). Fire severity, especially as it relates to the forest floor, depends more on the moisture content of the organic layers than it does on the intensity of the fire. Viereck and Schandelmeir (1980) considered that a very intense crown fire could have little effect on the forest floor, especially if the soil organic layers were saturated. Conversely, it is possible for a low-intensity surface fire to burn deeply into the organic layer by smouldering over long periods of time. 19 In this discussion fire severity will be used to indicate the degree to which fire effects the ecosystem - forest floor, overstory vegetation, understory vegetation, soils, or slash. There are very few quantitative data which relate fire severity to fuel consumption and vegetation effects. This makes development and testing of prescriptions difficult and allows for only crude predictions of fuel consumption and resulting ecological effects. In reviewing the literature it becomes apparent that fire severity depends on many variables which interact in a complex and poorly understood manner. Thus fire severity can be related to fuel moisture, drying conditions and prevailing weather, and forest floor and slash consumption which in turn, depend on loading, piece size and arrangement, and ignition pattern (Kiil 1971, Muraro 1968, Taylor 1987). Several "studies have investigated the effect of different fire severities on lodgepole pine ecosystems (Blackwell et al. 1986, Endean and Johnstone 1974, Lawson 1973, Quintillio 1970). A l l of these studies looked at different burning prescriptions and the resultant fuel consumption as a function of codes and indices of the Canadian Fire Weather Index (FWI) System by measuring fuel quantities removed and mortality of regeneration (if present) following the burns. Effects of slashburning on organic matter The soil organic matter consists of the surface layers referred to as L, F, and Humus (above mineral soil) or O (wet) horizons together with any organic matter mixed with or combined with mineral soil (Wells et al. 1979). This soil organic matter layer (forest floor) is an important reserve of nutrients which is significantly influenced by burning treatments. Jurgensen et al. (1981) and others have cautioned that the destruction of the forest floor 20 by clearcutting and slashburning could have a significant impact on site fertility. Slashburning induces organic matter consumption which is often necessary to facilitate the creation of plantable spots and reduce planting difficulty. Percentage reduction of organic horizons is generally considered a function of horizon depth and moisture content, season of burning and slash loading (Sims 1976). Ki i l (1971) reported that depth of burn was highly variable but that duff consumption was generally greatest around greater surface fuel accumulations. Taylor (1987), studying the effects of low severity slashburning on hybrid white spruce-subalpine fir (Piceaglauca (Moench) Voss x engelmannii Parry ex Engelm. - Abies lasiocarpa (Hook.) Nutt.) forests in the Sub-Boreal Spruce zone of British Columbia, found forest floor depth reductions were greater in mesic ecosystems than in subhygric ecosystems despite greater slash consumption in the subhygric ecosystems. It was believed that this was the result of higher forest floor moisture content in the subhygric ecosystem at the time of burning. Forest floor depth reduction was poorly correlated with slash consumption in the mesic ecosystems but was better correlated with large (> 8.0 cm) diameter slash consumption and total slash consumption in the subhygric ecosystem. According to Taylor (1987) consumption of moist forest floor material by burning is thought to be influenced by the duration of radiant heating from above, which in turn is influenced by the degree of coarse slash consumption. The poorer correlation in the mesic ecosystem was thought to be a result of a more restricted data set which had only a relatively narrow range of slash load and consumption. Ottmar et al. (1985) found that depth of burn was related to fire duration when the surface layer of forest floor was dry and acted as an insulation layer. However, if burning 21 occurred within 25 days of a significant rainfall (> 13mm) which wetted the surface forest floor layer, then depth of burn depended on the total amount of heat available to vaporize free moisture rather than on fire duration. In this case total woody fuel consumption was a better predictor of depth of burn than the variable which was a surrogate for fire duration. Reports of forest floor consumption by fire in lodgepole pine forests are limited. Lawson (1973) reported for 28 low severity fires that the depth of burn ranged from 0.5 cm to 1.7 cm and that consumption did not exceed 50% of the initial depth on any of the plots studied. Forest floor consumption for the fires averaged 0.33 kg/m . Endean and Johnstone (1974) reported average depth of burn for a "moderate" and a "high" severity slashburn as 1.8 cm and 5.6 cm respectively. Forest floor consumption was reported as 0.5 kg/m for the moderate severity burn and 2.9 - 6.7 kg/m 2 for the high severity burns. Effects of slashburning on slash fuels In describing the results of any slashburning operation it is important to investigate the resultant effects on the fuel complex. Many studies have described the slash fuel complex before and after a prescribed fire with the intent of deterrnining whether management prescriptions and objectives have been met. A knowledge of the effects of fire on the slash fuel complex is also of critical importance in the assessment of changes to site nutrient status. The interaction of the slash fuel complex with the fire environment depends on fuel loading, species, age, size, distribution and continuity of fuels, and drying conditions influenced by weather and fuel moisture. These parameters all make the prediction of fire 22 effects on slash extremely difficult and variable. Muraro (1971) indicated that the variables most likely to influence burn severity were those that determined the proportion of fuel available for combustion: fuel load, size distribution, and moisture content. Muraro (1968) evaluated hazard abatement using slashburning in cedar-hemlock (Thuja plicata-Tsuga heterophylla) slash located in the British Columbia interior. He found that the size class distribution in the burned fuel complex may be quite different from that in the initial fuel complex depending on the effectiveness of the treatment. The smaller fuel component distribution was affected most. A l l studies reviewed, where the consumption of different size classes of slash fuel were determined, confirm that relative slash consumption is inversely related to slash diameter (Endean and Johnstone 1974, Ki i l 1969, Lawson 1973, Muraro 1968, Quintilio 1970, Taylor 1987). Slash consumption of lodgepole pine fuels and the relationship to danger classes of the Canadian FWI System have been studied by Quintilio (1970) and Lawson (1973). Quintilio found a strong relationship between consumption and the buildup and spread index while Lawson reported highly variable consumption which was not well correlated with FWI codes and indices. Lawson attributed the poor correlations to highly variable initial fuel loads and reported fuel consumption of 0.2 kg/m 2 to 1.3 kg/m 2 for fires with Duff Moisture Codes ranging from 37 to 76 and Fine Fuel Moisture Code values ranging from 90 to 95. EFFECTS OF WINDROWING A N D BURNING SLASH Piling and burning of slash has been used for many years as a variation of broadcast burning in British Columbia forests. Most forest regions, with the exception of Vancouver, 23 have been windrowing since 1971 to accumulate slash and debris into rows or piles to facilitate their burning (Revel 1976). During 1986-87 6,136 hectares were windrowed and burned in the province (B.C. Ministry of Forests 1986-87 Annual Report). The effects of severe burning on individual site and soil chemical, physical and biological properties have been well documented in the general literature. However, little attempt has been made to outline changes in these properties caused by burning in combination with windrowing. Effects on organic matter The effects on organic matter removal by windrowing will depend on the initial soil fertility, the distance the material is moved and the effects of scalping on the soil microclimate and nutrient cycling processes. An increase in productivity may occur when part of a deep organic layer is removed from a wet site where decomposition is slow (Glen 1975). The distance that material is moved depends on factors such as topography, fuel loading and the type of machinery used. However, the distance material is moved is not as good a measure of nutrient redistribution as is the percentage of an area occupied by windrows (Glen 1975). Machine redistribution and mixing of organic matter with a brush blade may enhance microbial populations within the remaining organic matter to increase nitrogen availability where nitrogen is often in short supply (Kalmakoff 1982). On the other hand, forest floor removal may also result in a significant reduction in the supply of nitrogen and other elements for plant growth. DeByle (1982) found that, in comparing four different residue removal treatments for lodgepole pine, the lowest soil organic matter concentrations (4.1%) occurred beneath burned windrows. Greater concentrations occurred 24 in areas which were broadcast burned, chipped or in which slash was removed. DeByle found that mineral soil organic matter concentration increased following residue treatments that did not involve burning and decreased where burning was involved. EFFECTS OF SLASHBURNING ON FUELS A N D M I N E R A L SOIL E X P O S U R E Prescribed fires reported in the literature seldom remove more than 50% of the surface organic matter (Beese 1987, Lawson 1973, Muraro 1968 and Taylor 1987). However, even with small reductions in forest floor, mineral soil may be exposed. The complete removal of forest floor exposes mineral soil to more dramatic fluctuations in both temperature and moisture. Exposed mineral soil may also become susceptible to erosion following a fire, by increases in bulk density and by decreases in infiltration rates and porosity (Pritchett 1979). Dobbs and McMinn (1977) inferred that improved spruce growth on scalped areas when compared to untreated areas was attributable to improvements of soil temperature. Higher soil temperatures were the result of the higher thermal diffusivity of mineral soil (vs forest floor). Ballard et al (1977) suggested that when the entire forest floor is removed surface soil temperatures could be higher, lower, or the same as those of unburned organic surfaces. Exposure of mineral soil may favour the establishment of undesirable competing vegetation which is adapted to this medium. Where seedling establishment is favoured by increased temperatures then maximizing mineral soil may be appropriate. However, where the conservation of soil moisture is an important management consideration then mineral soil exposure should minimized. METHODS 25 1. Treatment effects on fuels The effect of the treatments on fuel load was assessed by determining the preburn and postburn fuel loads in each plot. The total pre-burn fuel load was made up of tree overstory biomass, understory, dead surface fuel, and forest floor. Measurements of these were made during summer, 1985 prior to treatment. The total postburn fuel load was made up of forest floor and dead surface fuels, which were measured immediately after each burn except for forest floor load in the windrow plots which was measured in summer, 1987. A. Pre-burn fuels 1. Lodgepole pine overstory Aerial and ground fuels, which became surface fuels following the knockdown and windrow treatments, were estimated by determining the biomass of all tree components present on each plot. The biomass of each tree component (needles, live branches, dead branches, stemwood, stembark and roots, with branches and stems being separated into < 1 cm, 1-7 cm and > 7 cm diameter categories) was determined using biomass regression equations which related biomass to dbh. These regression equations were developed from data obtained by destructively sampling trees during summer 1985. Twenty-three lodgepole pine trees, covering the range of size classes present in the stands were selected from stand 1. These trees ranged in dbh from 1.3 to 16.9 cm and in height from 2.4 to 13.5 m. The trees were felled, had their height measured, and then were separated into their different components. For the smaller trees, all of each component was taken to the laboratory for oven-drying and weighing. For the larger trees, the total field (wet) mass of each component 26 was measured using field scales then subsamples of each component were taken, weighed in the field then taken to the laboratory for oven-drying and weighing. By subtracting the oven-dry mass from the field mass of the subsamples the moisture content of each component of each tree was calculated. This was then applied to the total field mass of each component to determine its oven-dry mass. For tree stems, the subsamples were three discs, each about 5 cm thick. One was cut from near the base of the stem, another from near the top, and the third from near the midpoint of the stem. In the laboratory, these discs were separated into wood and bark, which were weighed separately after oven-drying. For each disc the proportion of total mass due to bark was thus determined. Applying this proportion to the section of the tree stem represented by the disc (the bottom disc represented the bottom quarter of the stem, the midpoint disc - the middle half, and the top disc - the top quarter) and knowing the relative mass of each of these three sections, from field measurements, the total mass of stemwood and stembark was estimated for each tree. Tree roots were collected after excavating. Roots from the larger trees were extracted with the assistance of a winch. These procedures resulted in some of the smaller roots not being collected but these roots are considered to make a minor contribution to the total root biomass. A l l tree biomass and size class data were analyzed to obtain the best regression equations which related component biomass, by size class for stems and branches, to functions of dbh. A l l regression equations were developed on a dry mass basis. The regression equations developed for the lodgepole pine trees present on the study site are given in Table 2-1. These equations were then applied to tree dbh data obtained from tree 27 inventory plots to estimate the total tree biomass, by component or size class, in each treatment plot. Three tree inventory plots each 50 m in area (circular plots with a radius of 4.0 m) were randomly located within each of the treatment plots, in 1985, and the control plots in 1986. The dbh of each living and dead tree present, within each inventory plot was measured. Tree density data were also obtained from these inventory plots. 2. Understory Living understory vegetation biomass was determined by destructive sampling of five randomly located 0.5 m 2 plots per treatment and control plot. The understory vegetation was separated into three categories - 1. mosses and lichens, 2. grasses and herbs, and 3. shrubs. The understory materials were placed in labelled bags and weighed after oven drying at 70°C. The average mass of understory fuels was then calculated for each treated and control plot. 3. Dead surface fuels a) < 1 cm diameter Dead woody surface fuels < 1 cm in diameter were estimated by destructive sampling of 5 randomly located 0.5 m plots per treatment and control plot. Each sample was individually bagged and weighed after oven drying at 70°C in the laboratory, b) > 1 cm diameter Dead woody surface fuels > 1 cm diameter were assessed during summer 1985 in each of the treatment and control plots using the line intersect technique (Van Wagner, 1968) and three 50 m transects oriented at 60° to each other. The starting point for each transect and the direction of the first transect were randomly chosen. Calculation of fuel load from Table 2-1. Biomass regression equations used to estimate tree component biomass Tree species/component Regression equation n I SE 28 P i nus c o n t o r t a Stembark In (BSB) = - 4 .319 + 2 . 147 In (D) 23 0 .90 0 . 264 Stemwood In (BSU) = - 2 .660 + 2 .303 In <D) 23 0 .91 0 .255 Dead branches In (BOB) = - 5 . 1 78 + 2 .224 In (D ) 21 0 .66 0 .519 L i v e branches In (BLB) = - 5 .337 + 2 .837 In <D ) 23 0 . 94 0 .629 F o I i a g e In (BFO) = - 4 .664 + 2 .216 In (D ) 14 0 .85 0 .601 Roots In (BRO) = - 3 .829 1 .581 In (D ) + 0.169 (D ) 23 0 .92 0 .353 < 1 cm woody In <B17) = - 4 . 196 + 1 .569 In (D) 19 0 .90 0 . 264 m a t e r i a l s > 7 cm woody In (BG7) = - 6 . 1 66 + 3 .752 In (D) 8 0 .63 0 .255 m a t e r i a l s n = number of data p o i n t s used to develop the e q u a t i o n . i = index of f i t . SE = s t a n d a r d e r r o r of the e s t i m a t e i n l o g a r i t h m i c u n i t s BDB = biomass of dead b r a n c h e s , BFO = biomass of f o I i a g e , B G 7 = bi omass of > 7 cm aboveground diameter woody m a t e r i a l s , BLB = biomass of l i v e b r a n c h e s , BRO = biomass of r o o t s . BSB = biomass of stembark, BSU = biomass of stemwood. B17 = biomass of 1-7 cm aboveground diameter woody m a t e r i a l s . D = t r e e diameter at b r e a s t h e i g h t . 1. Equations were developed from data from trees sampled at the study area. 2. A l l equations have been corrected for logarithmic backtransform bias. 3. 1-7 cm woody materials were calculated by subtracting the < 1 cm and > 7 cm woody materials from the total of all woody materials present. 29 line intersect data requires information on wood relative density. Relative densities were determined for five size classes (1.1-3.0, 3.1-5.0, 5.1-7.0, 7.1-12.0, and > 12 cm diameter) of dead surface fuel. This was done by collecting 3 samples of each size class from each of the treatment plots. This gave 54 samples of each size class of each category for which relative densities were estimated from measurements of volume (water displacement method) and dry mass (weighing after oven drying at 70°C). A mean relative density was then calculated for each size class (Table 2-2). 4. Forest floor Forest floor load was estimated by removing all forest floor down to mineral soil in 16 subsamples, each 20 cm x 20 cm in area, and randomly located in each treatment and control plot. The subsamples were placed in labelled bags and weighed after oven drying at 70°C in the laboratory. The preburn bulk density of five of these cores was measured in the field by noting the volume of silica chips or water required to fill the excavated hole lined with a plastic sheet. The mass of each of these five cores divided by its volume was used to determine the bulk density of the forest floor. Due to variation in density with depth it was also necessary to determine the bulk density of the surface 5 cm of forest floor since this portion of the forest floor was more representative of the density of material consumed by the fires. In 1985 the volume of fifteen additional subsamples of the surface 5 cm of forest floor was measured in the field using the same technique outlined above. 30 Table 2-2. Relative densities for lodgepole pine dead woody materials in the study plots. S i z e c l a s s (cm) R e l a t i v e D e n s i t y (a/cm ) Standard e r r o r i n p a r e n t h e s i s pre ( o l d dead burn & down) post ( r e c e n t burn s l a s h ) 1 - 3 0.49 (0.08) 0 .49 (0.01) 3 - 5 0.42 (0.07) 0.49 (0.01) 5 - 7 0 .39 (0.06) 0 .47 (0.01) 7 - 12 0.39 (0.06) 0.47 (0101) > 1 2 0.39 (0.06) 0.42 (0.01) (n = 54 per s i z e c l a s s ) (n = 48 per s i z e c l a s s ) Standard errors are given in parenthesis. 31 B. Postburn fuels 1. Dead woody surface fuels a) < 1cm diameter Postburn < 1 cm fuels were assessed by destructively sampling fuels in 20 randomly located 0.5 m plots in each broadcast burn plot and in each of the windrow and between-windrow areas in the windrow burn plots. The total postburn < 1 cm fuel load of a windrow plot was calculated by weighting the windrow and between-windrow loads according to the proportion of the total plot area occupied by windrow and between-windrow areas, respectively. b) > 1 cm diameter The postburn assessment of slash fuels > 1 cm in the broadcast burn plots was conducted in an identical fashion to the preburn assessment of dead surface fuels. The windrow plots were stratified into windrow and between-windrow areas for the postburn assessment. Randomly located and oriented transects 50 m long and totalling 150 m in length were used in three separate windrow and between windrow areas whereas 3 transects, each oriented at 60° to each other with randomly located starting points and 50 m in length were used for the broadcast burn areas. The total postburn surface fuel load of a windrow plot was calculated by weighting the windrow and between-windrow loads according to the proportion of the total plot area occupied by windrow and between-windrow areas, respectively. The fuel loads were determined using relative densities measured on the materials present immediately after the burns. These relative densities were again determined for five size classes (1.1-3.0, 3.1-5.0, 5.1-7.0, 7.1-12.0 and > 12 cm diameter) using 3 samples per size class per type of burn (windrow or broadcast) per 32 burning period. 2. Forest floor Forest floor depth-of-burn was estimated using 104 depth-of-burn pins which were systematically placed at thirteen random locations (8 per location) using a grid system (McRae et al. 1979). These were inserted into the forest floor of each plot prior to burning. The pins were inserted in such a way as to measure the depth of burn from the surface of the litter layer. Thus, depth of burn in the forest floor (L + F + H horizons combined), and not the duff (F and H only), was obtained. The prebura forest floor depth was estimated at each pin by adding the depth of burn to the postbura forest floor thickness. Forest floor mass consumption in each broadcast burn plot was estimated by determining the proportion of the forest floor mass that was consumed using forest-floor depth of burn and bulk density data. This was done by firstly determining the proportion of the total forest floor depth that was burned (PDB) using the average depth of burn for a given plot. This proportion is not the same as the proportion of the mass that is consumed since the surface forest floor layers have a lower density than the deeper layers. To estimate the proportion of the mass that was consumed the PDB was multiplied by the ratio B D 5 / B D E where B D 5 is the bulk density of the surface 5 cm of forest floor and B D E is the bulk density of the entire forest floor. The average depths of burn varied between plots but were all < 5 cm, so this procedure assumes that the forest floor bulk density does not vary with depth in the 0-5 cm layer. If this is not the case for low depths of burn, this procedure would overestimate the proportion of the mass that is consumed. The actual forest floor mass that was consumed by the fires, was obtained by multiplying the prebura forest floor mass by the estimated proportion of forest floor mass that was consumed. This method of 33 estimating forest floor mass loss was found to produce less variable results than determining the postburn mass from destructive sampling and subtracting the postburn mass from the preburn mass. For the windrow plots all forest floor in windrow areas was consumed by the fires. Remaining forest floor mass in between-windrow areas was estimated by determining the percentage of the area covered by forest floor and assuming the remaining forest floor had the same mass per unit area as the preburn forest floor. The percentage of remaining forest floor was estimated using three randomly located 90 m transects in each plot. 2. Treatment effects on mineral soil exposure Pre-burn mineral soil exposure was estimated by determining the number of depth of burn pins which would have been inserted into exposed mineral soil if the systematic grid point pin locations had been rigidly used. If exposed mineral soil was encountered the location was recorded and the pin location moved to measure forest floor depth-of-burn. The percentage of mineral soil exposure was determined by dividing the recorded number of mineral soil points by the 104 original systematic grid locations. Postburn mineral soil exposure was estimated by recording the number of depth of burn pins where forest floor was consumed to mineral soil and dividing by the number of total pins recovered to give a percentage estimate. This percentage was added to the preburn percentage to give the total post burn percentage of mineral soil exposure. 34 3. Statistical analysis Fuel consumption data were analysed with the objectives of determining -a) which fuel consumption variables, both absolute and percentage values [ total fuel (slash + forest floor) consumption, total slash consumption, large (>7cm diameter) slash consumption, medium (l-7cm diameter) slash consumption, fine (<lcm diameter) slash consumption, and forest floor depth of burn] were influenced by site preparation treatment and fire severity type. b) which fuel consumption variables were correlated with one another. Objective a) was achieved by subjecting the fuel consumption variables listed above to a two-way analysis of variance, testing the following null hypotheses: H 0 1 : Fire severity had no effect on fuel consumption. H 0 2: Site preparation treatment had no effect on fuel consumption. H 0 3: There were no fire severity type x site preparation treatment interactions with respect to the fuel consumption. Significant group means were distinguished using Tukey's HSD multiple comparison test to determine how fuel consumption changes as a function of fire severity. For the two way analysis of variance the assumption of normality could not be tested because of the limited number of data points. To test the assumption of homogeneity the residuals were plotted against estimated values to determine if the data exhibited heteroscedasticity. A l l percent consumption data were transformed using an arcsine transformation to normalize the data (Zar 1984). Objective b) was achieved by determining the highest Pearson correlation coefficient between both amount of fuel consumed and percentage consumption on the one hand and, on the other, five functions of each fuel consumption variable - the linear, logarithmic, 35 square, square root, and the reciprocal functions. RESULTS AND DISCUSSION 1. Preburn fuel distribution in the forest and rearrangement by treatment. The regression equations developed for the lodgepole pine overstory biomass components are reported in Table 2-1. The equations for all components, with the exception of dead branches, had I 2 values > 0.85 (Furnival 1961). The reduced accuracy of the equation for dead branches is attributable to both the small quantity of dead branch biomass present on individual trees and/or sampling error. The largest standard error was obtained for equations predicting live branches and this was a function of large variability within the regression data set (Table 2-1). Pretreatment biomass quantities ranged from 21 to 38 kg/m 2 (Table 2-3). The largest quantity of biomass in the pretreatment lodgepole pine ecosystem was contained in the dead woody materials (Table 2-3). Preburn biomass of dead woody material ranged from 3 to 25 kg/m with the largest estimates obtained for plots in Block 1 (1-6) and the lowest for plots in Block 3 (15-18) (Table 2-4). Greater than 7 cm slash made up greater than half of the dead woody material biomass present in the experimental plots (Table 2-4). The next largest estimate was made for overstory lodgepole pine. Lodgepole pine biomass ranged from 5 to 14 kg/m 2 (Table 2-3). The greatest quantity of biomass contained in lodgepole pine was found for stemwood, while dead branches contributed the lowest quantity (Table 2-5). Forest floor accounted for less than 25% of the total organic matter 36 Table 2-3. Prebura and postbura fuel loads (kg/m2) for the experimental plots. 1) Low Severity Burns (fresh slash - 1986) Plot No. 02 17 07 10 Pre Post Pre Post Pre Post Pre Post 1. Slash fuel Overstory biomass 7.1 9.9 9.7 8.4 Dead surface fuels 11.8 7.3 15.6 18.2 Total slash fuel 18.9 5.4 17.2 8.6 25.3 1.1 26.6 1.3 Understory biomass 0.4 0.5 0.4 0.5 2. Forest floor 5.4 3.8 3.0 2.1 6.3 0.7 3.1 0.0 3. Total fuel 24.7 9.2 20.7 10.7 32.0 1.8 30.2 1.3 2) Low Severity Burns (cured slash - 1987) Plot No. 01 04 03 05 06 Pre Post Pre Post Pre Post Pre Post Pre Post 1. Slash fuel Overstory biomass 5.4 6.0 9.5 7.0 7.4 Dead surface fuels 17.2 24.6 15.1 20.3 19.2 Total slash fuel 22.6 7.9 30.6 8.7 24.6 1.1 27.3 2.0 26.6 1.9 Understory biomass 0.5 0.3 0.3 0.3 0.3 2. Forest floor 3.9 2.6 3.1 1.8 4.6 0.1 4.2 0.5 3.9 0.2 3. Total fuel 27.0 10.5 34.0 10.5 29.5 1.2 31.8 2.5 30.8 2.1 3) Moderate Severity Burns Plot No. 08 11 12 16 Pre Post Pre Post Pre Post Pre Post 1. Slash fuel Overstory biomass 9.4 11.8 11.9 11.0 Dead surface fuels 15.0 19.9 17.1 13.6 Total slash fuel 24.4 6.5 31.7 5.8 29.0 0.9 24.6 0.7 Understory biomass 0.5 0.4 0.4 0.4 2. Forest floor 7.7 5.2 3.8 2.4 3.4 0.0 3.7 0.0 3. Total fuel 32.6 11.7 35.9 8.2 32.8 0.9 28.7 0.7 4) High Severity Burns Piot No. 09 13 14 15 18 Pre Post Pre Post Pre Post Pre Post Pre Post 1. Slash fuel Overstory biomass 11.6 10.7 9.3 12.4 14.4 Dead surface fuels 16.7 17.4 21.3 17.8 3.8 Total slash fuel 28.3 4.9 28.1 9.1 30.6 6.2 30.2 1.3 18.2 2.1 Understory biomass 0.3 0.4 0.3 0.2 0.3 2. Forest floor 4.5 3.1 4.1 2.3 4.3 2.5 7.3 0.2 6.2 0.1 3. Total fuel 33.1 8.0 32.6 11.4 35.2 8.7 37.7 1.5 24.7 2.2 5) Control plots Plot No. 02 03 Pre Post Pre Post— 1. Slash fuel Overstory biomass 6.1 10.2 Dead surface fuels 11.2 12.3 Total slash fuel 17.3 22.5 Understory biomass 0.4 0.3 2. Forest floor 7.5 7.3 3. Total fuel 25.2 30.1 Table 2-4. Pretreatment mass of surface dead woody material in the study plots. Mass (kg/m ) PLOT/ < 1 cm 1-7 cm > 7 cm TOTAL s i z e c I a s s 1 0 . 2 1 .3 15.7 17.2 2 0.0 2.3 9.5 11.8 3 0.2 2.2 12.8 15.1 4 0.3 0.7 23.6 24.6 5 0.1 0 . 5 19.7 20.3 6 0.0 1 . 1 18.1 19.2 7 0. 1 1 .7 13.8 15.6 8 0 . 0 1 .5 13.5 15.0 9 0 . 1 0.7 15.9 16.7 1 0 0 . 0 1 .4 16.9 18.2 1 1 0 . 1 0.9 18.9 19.9 1 2 0 . 1 0 . 4 16.6 17.1 13 0. 1 0.7 16.7 17.4 14 0.1 0 . 5 20.7 21.3 15 0.0 0.6 17.2 17.8 16 ' 0 . 1 0.5 13.0 13.6 1 7 0 . 1 0.3 6.9 7.3 18 0.0 0.7 3 . 1 3.8 I 2 0 . 0 0 . 8 10.4 11.2 1 3 0 . 1 0.8 11.4 12.3 Note control plot No. l was mistakenly spaced and therefore excluded from the study. 38 Table 2-5. Average mass of lodgepole pine stemwood, stembark, needles, branches, dead branches and roots in each of the 3 experimental blocks. • Component loading (kg/m ) B l o c k / p l o t STEMWOOD STEMBARK NEEDLE BRANCH DEAD ROOTS BRANCHES TOTAL B I OMASS B lock 1 -p l o t s 1-6 mean 4.0 0.6 0.5 0.7 0.4 0.9 7.1 s.d. 0.8 0.1 0.1 0.2 0.1 0.3 1.4 Block 2-p l o t s 7-12 mean 5.9 0.9 0.7 1.1 0.4 1.6 10.5 s.d. 0.8 0.2 0.1 0.2 0.1 0.2 1.5 Block 3-p l o t s 13-18 mean 6.3 0.9 0.7 1.3 0.4 1.7 11.3 s.d. 0.9 0.2 0.1 0.3 0.1 0.4 1-9 39 biomass and ranged from 4 to 7 kg/m 2 (Table 2-6). The smallest pretreatment biomass component measured was understory vegetation which accounted for less than 1 kg/m in all treatment plots (Table 2-7). No study found in the literature has attempted to quantify lodgepole pine biomass in these densely stocked stands. Previous studies have only quantified mature forest biomass or evenly spaced plantations, therefore meaningful comparison of these results is not possible. Fuels in the undisturbed stands included all standing trees, understory vegetation, dead surface fuels, (mainly decaying snag-fall of the 1932 to 1938 wildfires), and forest floor. Following the treatments only two categories of fuel were recognized. These were a) slash (consisting mainly of the snag-fall and pretreatment overstory and understory), and b) forest floor. Complete pretreatment plot information is given in Appendix 2-2. 2. Slash consumption Pre- and post-treatment fuel loads for all treated plots are given in Appendix 2-3 and summarized in Table 2-3. Fuel consumption was similar for the 4 different severity windrow burns, averaging 26-30 kg/m 2 or approximately 91-98% of the preburn loads (Table 2-8). The relatively low fuel consumption in the high severity windrow burns, particularly in plot 18, was due to the placement of several windrows in wet depressions (glacial striations). This not only restricted runoff, but also resulted in the lower portions of these windrows having a relatively higher fuel moisture content and less complete fuel consumption than other windrows. Fuel consumption in the broadcast burn plots was more variable, averaging from 13 to 25 kg/m 2 or approximately 56-72% of the preburn loads (Table 2-8). Average fuel consumption generally increased from the low severity (fresh and cured) through to the 40 Table 2-6. Average preburn, postburn mass and consumption of forest floor in the experimental plots. Mass (kg/m ) Preburn Postburn Consumption A c t u a l P e r c e n t LOU SEVERITY BURNS IN FRESH SLASH Broadcast p l o t s 4.2 3.0 1.2 29 Windrow p l o t s 4.7 0.4 4.3 91 LOW SEVERITY BURNS IN CURED SLASH Broadcast p l o t s 3 . 5 2.2 1.3 37 Windrow p l o t s 4.4 0.3 4.1 93 MODERATE SEVERITY BURNS Broadcast p l o t s W i n dro w p l o t s 5.8 3.6 3.8 0 . 0 2.0 34 3.6 100 HIGH SEVERITY BURNS Broa d c a s t p l o t s Windrow p l o t s 4.3 6.8 2.6 0.2 1.7 40 6.6 97 41 Table 2-7. Average understory vegetation mass, by component in each of the experimental blocks. Component l o a d i n g (kg/m ) ;  B l o c k / p l o t HERBS SHRUBS MOSSES TOTAL LICHENS BIOMASS Block 1 -p l o t s 1-6 mean 0.01 0.02 0.32 0.35 s.d. 0.01 0.01 0.09 0.09 Block 2-p l o t s 7-12 mean 0.01 0.06 0.28 0.40 s.d. 0.01 0.04 0.15 0.08 Block 3-p l o t s 13-18 mean 0.02 0.01 0.23 0.36 s.d. 0.01 0.10 0.08 0.09 42 Table 2-8. Summary of fuel consumption during the burns in the experimental plots. Treatment Broadcast Burn Windrow Burn (KB) (WB) Type of P l o t Consumption P l o t Consumption F i r e S e v e r i t y No . (kg/m2) (%) No. (kg/m2) {%) Low s e v e r i t y burns i n f r e s h s l a s h (1986) 2 15.5 63 17 10.0 48 average 12.8 5 6 7 1 0 30.2 28.4  29.6 94 96 95 Low s e v e r i t y burns i n cured s l a s h (1987) 1 4 average 16.5 23 . 5  20 . 0 61 69 65 28.3 29.3  28.8 96 £ 1 94 Moderate s e v e r i t y burns (1986) 8 20 .9 1 1 27.7 average 24.3 64 77 71 12 16 31.9 28 . 0  30 . 0 97 98 98 High s e v e r i t y burns (1986) 9 25 .1 13 21.2 14 26 . 5 average 24.3 76 65 75. 72 1 5 18 36.2 22.5 29.4 96 91 94 43 high severity burns, although there was little if any difference between moderate and high. Fuel consumption for the low severity fresh broadcast burns was lower than for the low severity cured broadcast burns (13 vs. 20 kg/m 2 respectively). The average preburn slash loads by size class in the experimental plots are given in Table 2-9. The greatest degree of consumption occurred in the < 1 cm size class where there was 100% consumption for both the windrow and broadcast burns for all severity levels (Table 2-9). For larger diameter fuels there was a general trend of increasing percent consumption with increasing fire severity in the case of broadcast burns (Table 2-9). However, this trend was not apparent in the windrow burn plots. Percent consumption was invariably greater in the windrows than in the broadcast burn plots. The type of site preparation (windrowing vs. just knockdown) significantly (p<0.05) influenced total fuel consumption (Table 2-10). Fire severity type had no statistically significant effect on total fuel consumption, although for the broadcast burns, fuel consumption did increase with severity. In this case Tukey's HSD comparisons indicated that totaf fuel consumption was significantly (p<0.05) less in the low severity burns in fresh slash. Percentage consumption of fuel in the 1-7 cm size class was also significantly influenced by both treatment and severity type effects (Table 2-10). Significant interactions between treatment and severity type were not found for either total fuel consumption or percentage fuel consumption in the 1-7 cm size class. When tests were carried out on the influence of severity type and treatment on consumption of different size classes of woody fuels, treatment and severity type both significantly (p<0.05) affected only the 1-7 cm fuel consumption (Table 2-10). The other slash consumption variables which were not significantly affected by treatment and severity type generally fell 44 Table 2-9. Average preburn, and postburn mass of slash fuels in the experimental plots. s i zee I ass < 1 cm Mass (kg/m ) 1-7 cm > 7 cm TOTAL LOU SEVERITY BURNS IN FRESH SLASH Broadcast p l o t s Preburn 0.4 Postburn 0 . 0 Consumption 0.4 (X) 100 Windrow p l o t s Preburn 0.4 Postburn 0.0 Consumption 0.4 (%> 100 8.2 2.0 6.2 80 8.8 0.5 8.3 94 9.5 5 . 1 4.4 50 16.8 0.7 16.1 96 18.1 7.1 11.0 60 26.0 1 . 2 24.8 95 LOW SEVERITY BURNS IN CURED SLASH Broadcast p l o t s Preburn 0.6 Postburn 0.0 Consumption 0.6 (X) 100 Windrow p l o t s Preburn 0.5 Postburn 0 . 0 Consumption 0.5 (X) 100 6.5 1 . 0 5.5 85 8.2 0.5 7.7 94 19.8 7.5 12.3 62 17.3 1 . 1 16.2 94 26.9 8.5 1&.4 68 26.0 1 .6 24.4 94 MODERATE SEVERITY BURNS Broadcast p l o t s Preburn P o s t b u r n Consumpt ion (X) Windrow p l o t s Preburn P o s t b u r n Consumpt i on (X) 0.4 0.0 0.4 100 0 . 5 0 . 0 0 . 5 100 9.4 1 .3 8.1 90 9.3 0.3 9.0 97 18.4 5.0 13.4 70 17.0 0.6 16.4 97 28.2 6.3 21.9 80 26 . 8 0.9 25.9 97 HIGH SEVERITY BURNS Broa d c a s t p l o t s Preburn P o s t b u r n Consumption (X) Windrow p l o t s Preburn Postburn Consumption (X) 0.4 0 . 0 0.4 100 0.4 0.0 0.4 100 8.3 0 . 7 7.6 90 9.7 0.3 9.4 97 20.3 6.0 14.3 70 14.1 1 . 5 12.6 89 29.0 6.7 22.3 80 24 . 2 1 .8 22.4 93 Table 2-10. A N O V A table for the influence of fire severity and site preparation (TRT) on total fuel consumption. SOURCE SUM-OF-SQUARES D F MEAN - SQUARE F - RATI 0 P SEVER I TY 88.416 3 29.472 1 .212 0 .36 TRT 316.529 1 316.529 13 .021 0 .00 TRT*SEVER I TY 99.146 3 33.049 1 .360 0 .32 ERROR 218.777 9 24.309 A N O V A tables for the influence of percentage fire consumption of < 1 cm, 1-7 cm and > 7 cm diameter woody fuels on severity and site preparation (TRT). 1 . < 1 cm diameter woody f u e l s SOURCE SUM-OF-SQUARES DF MEAN- SQUARE F -RATIO P SEVERITY 3 . 189 3 1 .063 0 .709 0 . 57 TRT 4.668 1 4 .668 3 .113 0 . 1 1 TRT*SEVERITY 3 . 578 3 1 . 193 0 . 795 0 . 53 ERROR 13.495 9 1 .499 2. 1-7 cm diameter woody f u e l s SOURCE SUM-OF-SQUARES DF ME AN - SQUARE F -RATIO P SEVERITY 240 .398 3 80 .133 10 .535 0 . 00 TRT 568.192 1 568 .192 74 .701 0 . 00 TR T*SE VE RIT Y 78.885 3 26 .295 3 .457 0. 07 ERROR 68.456 9 7 . 606 3. > 7 cm diameter woody f u e l s SOURCE SUM-OF-SQUARES DF MEAN -SQUARE F -RATIO P SEVERITY 182.058 3 60 .686 0 .817 0 . 52 TRT 2398.014 1 2398 .014 32 .298 0. 00 TRT*SEVER I TY 321.817 3 107 .272 1 .445 0. 29 ERROR 668. 222 9 74 . 247 46 into two categories - those variables that exhibited large variability making detection of differences difficult and those variables which violated one of the A N O V A assumptions. Total fuel (slash + forest floor) consumption and large slash (> 7 cm) consumption were significantly correlated with both total and large slash consumption, as was 1-7 cm slash load with 1-7 cm slash consumption (Table 2-11). 3. Forest floor consumption Forest floor consumption was considerably less than slash consumption for all broadcast burns, and ranged from 1 to 3 kg/m or approximately 30-45% of the preburn forest floor load (Table 2-3). In the windrow plots forest floor consumption ranged from 4 to 7 kg/m or approximately 88-100% of preburn forest floor load. This large reduction in comparison to the broadcast plots was due mainly to the fact that most of the forest floor was piled in the windrows. The only forest floor remaining following the windrow burns was the small amount located in the interwindrow areas. Forest floor depth of burn in the broadcast burn plots ranged from 2.6 to 5.2 cm (Table 2-12). The depth of burn generally increased with fire severity, from 38% through to 48% of the initial forest floor depth. These results are supported by other work by Feller (1988) and Ottmar et al. (1985) who suggested that consumption of the L layer is controlled by heat convection. Large standard deviations in the depth-of-burn and forest floor consumption precluded determining statistically significant differences. However, the reported values are similar to those found for slashburns in west coast Tsuga heterophylla - Pseudotsuga menziesii - Thuja 47 Table 2-11. Correlations between slash consumption and initial slash load, by slash diameter class. C o r r e l a t i o n C o e f f i c i e n t s ( D I n i t i a l S l a s h - Consumption by Diam. C l a s s (cm) Load by D i am. C l a s s (cm) < 1.1 1 . 1 - 7 . 0 > 7. 1 T o t a l < 1.1 1 .00 ** 0.08 0.22 0.15 1.1 - 7.0 -0 . 09 0.92 ** 0 . 04 0.35 > 7.1 0 .41 -0.56* 0.82 ** 0.60 * T o t a l 0 . 26 0.27 0.84 ** 0.77 ** Significant at p < 0.001 * Significant at p < 0.01 n = 17 48 Table 2-12. Forest floor depth, depth-of-burn and postburn mineral soil exposure for the broadcast burns in the experimental plots. Preburn f o r e s t Depth of burn (cm) f l o o r depth (cm) Percentage No. of depth- % P l o t Ho. r e d u c t i o n o f - b u r n p i n s M i n e r a l Mean s.d. Mean s.d. i n depth r e c o v e r e d S o i l Exposure Low s e v e r i t y burns i n f r e s h s l a s h (1986) 2 6.8 1.9 2.6 1.9 17 9.7 2.7 3 .6 2.7 average 3 .1 1 . 7 38 37 38 1 03 103 Low s e v e r i t y burns i n cured s l a s h (1987) 7.7 5.6 2 . 7 2.4 average 3.3 2.9 3 . 1 2 . 2 1 .8 1 . 7 43 52 48 1 03 95 1 10 6 Moderate s e v e r i t y burns (1986) 8 7.8 2.6 3.1 11 7.8 2.6 3.4 average 3 • 3 2 . 6 2.6 1 • 8 40 44 42 102 96 1 0 .10 1 0 High s e v e r i t y burns (1986) 9 8.4 2.3 3.3 13 8.9 2.9 4.7 14 10.0 3.4 5.2 average 4.4 2.3 2.9 3.4 1 .7 39 53 52 48 91 99 102 1 0 20 20 1 7 Note 1. Forest floor depths were estimated from 91-103 measurements per plot. 2. In each plot 104 depth-of-burn pins were placed in the ground prior to burning. 3. s.d. = standard deviation. 4. Pre-burn mineral soil exposure averaged between 1-2% for all experimental plots. 49 plicata forests (Feller 1986, Ottmaref al. 1985), and British Columbia central interior Pinus contorta - Picea spp. forests (Macadam 1987). Macadam (1987) found depth-of-burn ranging from 1.3 to 4.2 cm for the operational slashburns she was studying in Sub-Boreal Spruce zone ecosystems. Taylor (1987) found depth-of-burn ranged from 1.5 to 3.2 cm for the operational slashburn he was monitoring. Although the distinction between the fire severity classes is not that great, the range in depth-of-burn and fuel consumption includes most of the severities normally considered operational for the study area (Macadam 1987, and Taylor 1987). Depth-of-burn was significantly (p < .01) correlated with initial forest floor depth (Table 2-13). This result was likely a function of the variability in forest floor depths between different treatment plots. The depth-of-burn data do not support delineation of the four sets of broadcast burns into three different fire severity types. It is apparent from the results that both the low severity burns in fresh slash and the low severity burns in cured slash had similar depths of burn. This is probably a consequence of forest floors being saturated from snowmelt during spring (low D M C and D C values) and not being influenced to a great extent by changes in slash fuel consumption. 4. Total fuel consumption The consumption in windrow burns was greater than in broadcast burns for the same fire severity (Table 2-8). It is apparent that when slash is accumulated into large windrow piles the influence of fire severity is minimal, as all windrow burns had similar consumption results. However, for broadcast burns fuel consumption was more closely related to fire severity. It appears that low severity burns in cured slash consume similar quantities to those of the moderate and high severity burns. This result is of operational value as risk of fire escapes can be reduced by burning cured slash during the spring rather than by burning during a dryer period later in the summer yet maintaining the integrity of the forest floor. Table 2-13. Correlations between forest floor depth-of-burn and slash consumption and initial forest floor depth for the broadcast burn plots. C o r r e l a t i o n C o e f f i c i e n t ( r ) - - - - S l a s h Consumption by Diam. C l a s s (cm)---- I n i t i a l F o r e s t F l o o r Depth < 1 1 - 7 > 7 T o t a l Broadcast Burn P l o t s Depth-of-burn -0.61 0.24 0.01 0.09 0.80 ** Percent Depth-of-burn 0.37 0.08 0.61 0.54 -0.01 Significant at p<0.01 n=9 51 5. Treatment effects on mineral soil exposure Mineral soil exposure measured immediately after the burn in the broadcast plots ranged from 3 to 17% (Table 2-12). Mineral soil exposure increased with increasing fire severity and was greatest for high severity burns. For low severity burns in fresh and cured slash exposed mineral soil was similar, measuring 3 and 6% respectively. Results of the low severity burns were similar to those reported for coastal spring burns (Beese 1987). However, Beese (1987) reported mineral soil exposure for coastal fall burns of 29 to 74%, which is substantially higher than found in this study. Other studies, (Kiil 1971, Lawson 1973), have reported that mineral soil exposure was not significant and only occurred in isolated areas adjacent to stumps, roots and heavy slash accumulations. Only Beese (1987) quantitatively assessed mineral soil exposure. Comparison of this study to those of other interior slashburns is limited as these studies only qualitatively estimated mineral soil exposure. The objective of rehabilitation treatments is to remove the large accumulation of organic material to facilitate establishment of a new plantation, it appears that this can be achieved without large areas (<20%) of mineral soil being exposed, if this is the desired objective. Thus, it may be concluded that, for the study area -1. Over the range of burning conditions used, windrow burns consumed similar amounts of slash fuels, unlike broadcast burns which consumed greater amounts of slash fuel with increasing fire severity or severity. 52 2. Forest floor consumption was generally only a small proportion of the total fuel consumption. 3. It is operationally feasible to conduct different severity burns in (partially cured) slash from recently knocked down dense lodgepole pine stands. 4. If the desired objective is to achieve a degree of fuel consumption similar to that of the low severity burns in cured slash, moderate severity burns, or high severity burns, then the recommended choice of severity would be low cured due to the low risk of escape associated with this fire severity class. 5. Although degree of fire severity had no statistically significant effect on depth of burn it would nevertheless appear that if both slash removal and conservation of forest floor are important then these can be jointly achieved by broadcast slashburning either fresh "or cured lodgepole pine slash, under low severity ( F F M C 85-87, D M C < 20, DC < 120) conditions. 6. For windrow plots, the accumulation of fuels into piles creates a situation where the degree of fuel drying plays a limited role in determining the fire severity and amount of fuel consumed once a fire has been ignited in the piles. CHAPTER 3 EFFECTS OF TREATMENTS ON NUTRIENTS 54 INTRODUCTION Slashburning is a common tool used to prepare a site for planting following clear-cutting. On sites that have no commercially valuable species, or where normal forestry practices have produced unwanted weed species, fire is more frequently being considered as a method of rehabilitation by which the undesirable species are removed and a new forest is established. To date, the effects of fire rehabilitation treatments on nutrients have not been studied. Other types of fire have been found to generally cause an increase in available nutrients in the soil, but, at the same time, also a loss of nutrients to the atmosphere through volatilization and/or upward movement of particulates with further losses occurring as a result of wind removal (of ash after a fire), erosion, and leaching. The use of fire as a rehabilitation tool involves removal, in most cases, of large quantities of biomass and conceivably the loss of large quantities of nutrients. As part of the study to rehabilitate densely stocked lodgepole pine in the Lakes Forest District, soil nutrient status and ecosystem nutrient losses were quantified to help assess the impacts of burning treatments on future site productivity and lodgepole pine plantation development. This chapter reports literature findings related to the study as well as pre- and post-burn nutrient status associated with the four fire severity and two site preparation treatments. 55 L I T E R A T U R E REVIEW -EFFECTS OF SLASHBURNING ON CHEMISTRY A N D NUTRIENTS Mechanisms of nutrient transfer during slash fires Nutrients are constantly being added to and released from undisturbed forest stands. When trees are harvested and removed or when fire is used for site preparation or rehabilitation purposes, the nutrient status of the site is changed. Fire mobilizes nutrients by heating of the soil and by combustion of forest floor and slash leading to deposition of ash. Nutrients may be lost from the site by atmospheric transfer, leaching, overland flow and the erosive action of wind and water. The contribution of volatilization to atmospheric transfers depends, to a large extent, on the vaporization temperature of an element and fire intensity, which affects both temperatures generated and the amount of ash removed in the convection column (Raison et at. 1985a). The volatilization temperatures of N and S are relatively low (<500°C) while for inorganic forms of other elements the vaporization temperatures extend from 774°C for P and K to 1484°C for Ca (Weast 1980). Elements which are bound in organic and inorganic compounds of plant material exhibit wide ranges of volatility depending on combustion conditions (Raison et al. 1985a). Raison et al. (1985b), studying atmospheric transfer of elements during low-intensity prescribed fires in Australia, showed that loss of N was almost solely due to volatilization, loss of Ca was due to transport of small amounts of fine Ca-rich ash, and loss of K and P as well as other elements occurred via volatilization and particulate pathways. They 56 confirmed that nutrient-rich ash is very light and thus susceptible to transport from the site either in smoke, or via the action of wind and water and that removal of only small amounts of ash could result in a significant export of elements from the site. Particulate transfer to the atmosphere is thought to depend on smouldering combustion and the influence of convection. Ottmar et al. (1985) discovered that increases in smouldering combustion and particulate emissions occurred when drier fuels were slashburned in Washington. At the soil surface very steep temperature gradients may be produced resulting in the heating of the upper soil surface. If the temperature climbs above 200°C, volatilization of N will occur. When the upper soil surface and lower litter layer are moist the risk of N losses from the soil will be reduced. Nutrient transfer to the atmosphere increases with organic matter consumption (Wells et al. 1979, Feller 1982) with the strength of the relationship dependent upon the nutrient being assessed. Raison et al. (1985b) showed that the relative transfer to the atmosphere of elements followed the order N > K > P > Ca and that the loss of nutrients increased linearly with increasing combustion of fuels. Following burning and before ash compaction by rain, wind may redistribute or completely remove the ash from the burning site. Heavy rain after a fire may lead to nutrient redistribution on soils of low erosion potential or may lead to loss from sites of high erosion potential if ash and organically enriched surface soil are washed away. 57 Changes in total N Many studies have shown a loss of total N from forest floor and slash due to burning while others have reported gains in N . Mroz et al. (1980) found that the amount of N lost by volatilization depends on the intensity of the burn with more intense fires causing greater losses. They found significant losses of total N from the L and F horizons, while the total N content in the H horizon increased. Combining data for both the L, F, and H horizons indicated that loss of total N was not significant. These findings illustrated the importance of sampling methodology and showed that by sampling only burned material after a fire, an overestimation of N loss from the site is likely. The findings also showed that N concentrations are extremely variable after fire, making the time of sampling critical in obtaining an accurate estimation of fire effects. The findings also suggested that any generalization about the effects of fire on total N over wide areas and different fuel materials may not be valid. The variability in N results emphasized by Mroz et al. (1980) is supported by many other studies. For example, N losses have been reported to vary from 20 to 900 kg/ha for various fuel types and fire severities (Allen 1964, Christensen 1977, Feller et al. (1983), Grier 1975, Harwood and Jackson 1975, Issac and Hopkins (1937), Taylor and Feller (1987), Wells 1979). Grier (1975) summarized results from a number of studies confirming a close 1:1 relationship between organic matter loss and nitrogen loss for fires exhibiting temperatures of 550-1040°C, the range observed in most fires. However, data from Knight (1966) show that at lower temperatures this relationship does not hold; differences between nitrogen and mass loss of 17% or more were calculated for fires of 500°C or less. 58 Raison et al. (1985a) studying nutrient transfer to the atmosphere during vegetation fires, using data from 34 literature sources, found that the percentage loss of N and fuel mass showed a significant linear correlation. The data included a wide range of fuel consumption (<2 to >300 t/ha), fuel types (grass, shrubs, woody litter), fire severity (from low-severity prescribed burns to high-severity wildfires in forests) and elemental transfers (11-982 kg N/ha). Under field or simulated field conditions the slope of the regression line approached unity. The slope was less, however, when the samples were ashed in a muffle furnace. Raison et al. (1985a) attributed reduced loss of N during ashing in a muffle furnace to reduced temperatures in the absence of flaming combustion or because of oxygen deficiency and partial combustion in some of the samples. Changes in nutrients other than N The major emphasis of studies on nutrient loss, due to fire, has been nitrogen (Debell and Ralston 1970, Klemmedson et al. 1962, Knight 1966, Mroz et al. 1980). More recently, work by Raison (1980), in Australia, has emphasized the importance of phosphorus as well as nitrogen losses. In the U.S. the importance of sulphur losses from fire has been documented by Tiedemann (1987). Canadian research by Feller et al. 1983 has reported changes of five important nutrients (total N and P, K, Mg, and Ca) from a Southwestern B.C. clearcut slashburn. As well many other studies have also reported losses of different nutrients (Allen 1964, Feller et al. 1983, Flinn et al. 1979, Grier 1975, Harwood and Jackson 1975, Isaac and Hopkins 1937, Nissley et al. 1980, Smith and Bowes 1974, Tiedemann and Anderson 1980). The comparison of nutrient loss studies is difficult, since nutrient losses will depend on fire severity, the method of measurement, timing of measurement and the 59 nature of the losses being quantified (eg: whole ecosystem versus losses from slash and forest floor fuels). Although comparability is limited, studies suggest that the percentage loss of Ca and Mg is considerably less than the percentage loss of slash biomass (Feller 1982, Flinn et al. 1979, Harwood and Jackson 1975, Taylor 1987). Volatilization of Ca is likely to be negligible in most slash fires (the vaporization temperature of Ca is 1484°C and that of organic Ca compounds is also very high (Weast 1980)). The same also applies to Mg which has a vaporization temperature above 1500°C. Raison et al. (1985a) showed that the main mechanism for loss of Ca to the atmosphere was through particulate transfers of ash. For situations where the loss of particulates during burning is small or where absence of wind leaves ash undisturbed, relatively low amounts of Ca and Mg are lost. The chemical behaviour of these two divalent metallic elements is expected to be somewhat similar but different from that of non metallic N , S, and P. A summary of slashburning induced losses of Mg and Ca, by Taylor and Feller (1987) showed that recorded losses of Mg ranged from 1-136 kg/ha while Ca losses ranged from 20-252 kg/ha. The recognition of sulphur as an important nutrient has only recently occurred as fertilization research has emphasized the significance of the N:S ratio and because S has a low vaporization temperature similar to N , with potential relative losses of S as great as those of N (Tiedemann and Anderson 1980). Tiedemann (1987) found that sulphur incorporated in the foliage of Alnus, Ceanothus and Pinus in forest Utter is highly vulnerable to volatilization loss at combustion temperatures of 375-575°C for five minutes. Under these conditions sulphur losses ranged from 24-79% while losses ranged from 61 to 92% for temperatures between 975°C-1,175°C for 60 minutes. Tiedemann and Anderson (1980) found volatilization of S was greater for deciduous foliage and litter combined (63-82%) 60 than for coniferous foliage (24-69%) and litter (32-37%) at temperatures of 375-575°C, which they attributed to differences in the sulphur compounds present in conifer versus deciduous foliage. Taylor and Feller (1987) reported sulphur losses, due to slashburning, ranged from 2 kg/ha, for Douglas-fir slash, to 87 kg/ha, for a white spruce-subalpine fir slash which Taylor (1987) was studying. Investigations into phosphorus changes following fire indicate that temperature, the form of P in the fuel, the cation content of the ash and the amount of ash transported all influence the quantity lost to the atmosphere from a burned site. Since the volatilization of phosphorus occurs at lower temperatures than for the divalent cations (774°C), this transfer mechanism plays an important role in moderate to high severity fires. However, during fires of low severity, losses of phosphorus to the atmosphere are probably mainly due to particulate transfer. Raison et al. (1985a) found that a simple linear relationship between P loss during vegetation fires and mass loss accounted for 21 to 70% of the variation in P loss. They concluded that this poor relationship could have been caused by differences in the original nutrient content and burning characteristics of the different fuel types used in the analysis. The summary results of Taylor and Feller (1987) are very limited for phosphorus with losses ranging from 8 kg/ha (for radiata pine forest) to 55 kg/ha for white spruce-subalpine fir forest. Feller (1988) found that P losses for small plot burns he was studying ranged from 0 to 28 kg/ha. The response of K to burning appears to be very similar to that of P. Feller et al. (1983) reported K losses of 17-37 kg/ha for slashburning in western hemlock-western redcedar fuels. Taylor and Feller (1987) found K losses of 60 kg/ha for a mesic ecosystem and 30 kg/ha for a subhygric ecosystem which compares with P losses of 55 kg/ha and 33 61 kg/ha for the mesic and subhygric ecosystems respectively. Changes in pH Nutrients released within the slash and forest floor materials following fire produce a temporary increase in soil pH (Feller 1982). This temporary decrease in soil acidity in the surface layers depends on the amount of ash released, original soil pH, the chemical composition of the ash and the influence of climate (DeByle 1976, Grier 1975, Lutz 1956, Wells 1971). Ahlgren and Ahlgren (1960), Austin and Baisinger (1955), Issac and Hopkins (1937), Macadam (1987), and Tarrant (1953) (1956) attributed marked increases in soil pH to the presence of exchangeable bases and carbonates in organic matter burned to ash. Work by Tarrant (1953) indicated that surface soil pH increases of 1-3 pH units may be common for areas where severe burning conditions have completely consumed all surface organic matter. These results have also been supported by data of Austin and Baisinger 1955, Baker 1968, Issac and Hopkins 1937, Knight 1964, Neale et al. 1965, Tarrant 1953 and Tarrant 1956. Baker (1968) predicted that the duration of pH increases after burning will be variable depending on the intensity and duration of precipitation, the buffering capacity of the soil and the presence of soluble salts at depth. Braathe (1974) and Skokelefald (1973) studying Norway spruce - Scots pine cutovers in Norway found pH increased 2.7 units (from 4.0 to 6.7) in the litter layer and 0.3 units in the duff in the first year following burning but pH values were similar to unburned plots after 8 years. Following a severe burn on a thin forest floor site in Sweden, Uggla (1967) found increases in pH which persisted for 21 years. DeByle (1982) reported that pH 62 increases after broadcast burning in lodgepole pine fuels lasted for several years after the fire. Effects of slashburning on nutrient availability Several factors govern the availability of plant nutrients in response to decomposition, disturbance and removal of organic matter. These include soil pH, soil aeration, soil moisture movement, ion mobility and the relative amount of an element present (Dyck 1976). The effect of soil pH on nutrient availability varies for different nutrients as illustrated by data from Ballard (1985), Clinnick and Willatt (1981), Dyck (1976), Humphreys and Lambert (1965), and Neale et al. (1965). Greater alkalinity may increase Mg and K availability as a smaller portion of cation exchange sites will be occupied by H ions. Increased solubility and susceptibility to leaching of Cu, Fe and Mn at high pH may account for their lower availability on more severely burned sites (Ballard 1985). Nissley et al. (1980) found that pH increases were highly correlated with N losses from burning. Dryness and Norum (1983) found that pH, and extractable and total P concentrations in the forest floor, and extractable P concentrations in the mineral soil also increased with fire severity, following experimental fires in black spruce stands in Alaska. Mroz et al. (1980) found that burning resulted in an increase in the available N content of mineral soils, perhaps in part due to leaching from the forest floor. Different effects on N nutrition depend on the influence of various processes such as N fixation, nitrification and leaching of mineralized N into the soil. A postburn increase in N may be sufficient to compensate in the short term for total N losses caused by volatilization. However, such 63 increases in available N may be insufficient to prevent long term nutrient deficiency following severe fires (Ballard 1985). High levels of ash and charcoal may reduce phosphate availability due to a) formation of relatively insoluble Ca, Fe, or A l compounds, [(Smith and Jones (1978) attributed a decrease in extractable P concentration in the forest floor following burning in part to fixation by Fe and Al)] or b) the adsorption of phosphate ions on charcoal which is often formed in large quantities during a fire (Beaton et al. 1960). Effects of windrowing on nutrients The literature suggests that the effects of windrowing and burning on nutrient changes are extremely variable. Most studies to date have been carried out in Australia and New Zealand where windrowing and burning is an important treatment used to convert indigenous forest to Pinus radiata (D. Don) plantations. A few studies have looked at nutrient changes due to windrowing and burning in the southern pine region and the rocky mountains of the United States while Canadian studies have been limited to British Columbia. Windrowing and burning causes three major changes in nutrient status. Firstly there is an accumulation (concentration) of nutrients through the process of piling. Nutrients are then either lost by volatilization and leaching or are concentrated in the remaining ashbed as a result of burning. A study on windrowing on pumice soil in New Zealand (Webber 1978) revealed that windrow operations which moved large amounts of surface soil with woody materials could remove 1400 kg/ha of nitrogen from interwindrowed areas. The amount of nutrients 64 displaced during windrowing was proportional to the quantity of slash and soil moved (Webber 1978). Most of the nutrients displaced were moved in the mineral soil. The amount of nitrogen moved with the mineral soil was approximately ten times greater than the nitrogen moved with woody components. Morris et al. (1983) pointed out that much of the nitrogen removed was part of the biologically active forest floor litter layer and the surface soil which are disproportionately important to nutrition of the young plantations. They noted that P, K, Ca and Mg contents of the windrows represented accumulation of between 15% and 40% of the total organic (slash and forest floor) plus mineral soil extractable reserves of the ecosystem. Ballard (1985) reported that foliar nitrogen and sulphur concentrations were not significantly lower in trees planted in burned windrows. He concluded that accumulations of nitrogen and sulphur in windrows followed by their release in available form in the soil may compensate for the effects of volatilization losses. Feller (1988) found burning resulted in significantly greater nutrient losses from heavy slash load plots than from low slash load plots. These results were found to be consistent with those of Little and Klock (1985) who found N and S losses to the atmosphere during operational slashburns were greater with higher slash loads. Therefore, it seems likely that volatilization losses from windrow burns would be greater than those from broadcast slashburns because of greater fuel accumulations in piles, as well as greater consumption of these fuels during burning. Many studies have described an "ashbed effect" in burned windrows (Ballard 1985, Clinnick and Willatt 1981, Cromer 1967, Debyle 1982, Gifford 1981, Humphreys and Lambert 1985, Pryor 1963). However, reported changes in soil nutrient levels were highly variable. Humphreys and Lambert (1965) found a marked increase in the soil active 65 inorganic P, particularly Al-phosphates after laboratory heating of soil. They concluded that an increase in P availability was the factor most closely associated with improved tree growth on ashbed soils in Australia. They considered that the increase could arise from a change in the composition of soil phosphorus or from a reduction in the ability of soil to adsorb phosphorus, presumably leading to greater P mobility. Following burning of slash piles there is generally a significant increase in mineral soil K, Mg, Ca, and P concentrations (Adams and Boyle 1980, Benson 1982, Packer and Williams 1980). However, DeByle (1982) found that mineral soil K concentrations after five years were lowest for a piling and burning treatment than for 3 other treatments. It would seem probable that leaching of nutrients would be higher in soils beneath burned windrows than in soils between windrows due to greater quantities of leachable nutrient ions in the ash and remaining organic matter in the windrow areas. Higher leaching losses beneath burned windrows is supported by studies such as that of Grier (1972) which found increased leaching when greater quantities of slash are burned. Further losses would be expected to occur through subsequent wind and surface water erosion which could remove ash particles and more nutrients (Wells et al. 1979). This latter type of nutrient loss does not appear to have been quantified in piling and burning studies. Piling and burning generally causes significant increases in soil pH which then decreases with time (Clinnick and Willatt 1981, Gifford 1981). Although the effects on nutrients of 1) slashburning and 2) windrowing and burning have been studied independently, few if any studies have tried to compare the two treatment types on the same site under similar burning conditions. Because both of these treatments were thought to be operationally feasible to convert lodgepole pine stands to 66 young plantations, the B.C. Forest Service (Lakes Forest District) felt it desirable to investigate the effects of both treatments on nutrients and quantify losses. The objective of the research described in this chapter is to quantify the effects on ecosystem nutrient status of the different fire severity/site preparation treatments used to rehabilitate densely stocked lodgepole pine stands. METHODS Study Area Fieldwork for the study was conducted in an area located between Francois and Ootsa lakes, southwest of Burns Lake in west central B.C. Two experimental blocks were delineated within a dense lodgepole pine stand. Each block was divided into six 1 ha experimental plots, in addition, one control plot, which was to remain untreated, was also delineated adjacent to each of the three blocks. This stand occurred primarily within one ecosystem type - the Mesic bunchberry-moss ecosystem association (ecosystem unit SBSel/01) of the Subalpine Fir Subzone of the Sub-Boreal Spruce biogeoclimatic zone (Pojar et al. 1984). The study area has a cold sub-boreal continental humid climate which is characterized by severe, snowy winters and relatively warm, moist and short summers (Pojar et al. 1984). Soils in the area are predominantly Brunisolic Gray Luvisols (Agriculture Canada Expert Committee on Soil Survey 1987) with Hemimor humus forms (Klinka et al. 1981). The experimental design involved burning 2-3 knockdown and windrow plots on each of four occasions. The burns on these occasions were characterized as 1) low severity in 67 fresh slash, 2) low severity in cured slash, 3) moderate severity, and 4) high severity. For more information on the study area and experimental design refer to Chapter 1. 1. Treatment effects on nutrient budgets Nutrient (N, P, K, Na, Mg, Ca, and S) quantities in each plot were estimated before the treatments and immediately after each of the four sets of burns to assess the effects of different site preparation/fire severity treatments on ecosystem nutrient losses and nutrient status. The nutrient content of each component of the ecosystem was estimated both before and after rehabilitation treatments. This was done by quantifying the mass of each organic component and the surface (0-15 cm) mineral soil in the ecosystem and multiplying the masses by-their nutrient concentrations which were measured on samples from each component. Ecosystem biomass quantities were estimated as follows: Biomass assessment has been described in detail in Chapter 2 and briefly summarized here. Preburn biomass of overstory lodgepole pine was determined using regression equations developed from lodgepole pine trees sampled from the study area. Preburn dead woody materials were sampled using the line intersect method of fuel sampling (Van Wagner 1968). Fine, ( < 1 cm) woody materials and understory vegetation biomass (shrubs, herbs, mosses and lichens) were determined by destructive sampling of 5 lm subsamples per plot. Preburn forest floor was estimated by removing all forest floor down to mineral soil in 16 cores, randomly located in each treatment plot. Postbura slash fuels and forest floor were sampled in an identical fashion to the preburn assessments. Total biomass consumption was determined by subtracting postbura from preburn organic material 68 quantities. Field operations and fire severity assessment procedures are detailed further in chapter 1. Ecosystem nutrient quantities were estimated as follows: a) for lodgepole pine overstory - from measurements of the various biomass components present (obtained from regression equations) and the average nutrient concentrations in stemwood, stembark, needles, branches, dead branches and roots (determined from 23 samples per component.) b) for downed woody materials -for the < 1 cm slash - from measurements of the mass of these materials (by destructive sampling), 5 samples per plot preburn and 20 samples postburn, and their total nutrient concentrations (determined from 6 composite samples per treatment block.) for the > 1 cm slash - from measurements of the mass of these materials (from the line intersects) and their mean weighted nutrient concentrations from 18 samples for each size class pretreatment and 3 samples for each size class per plot postburn. Windrow postburn woody materials were estimated by making measurements in areas both beneath and between windrows. Plot totals were then calculated as a weighted mean of the beneath and between windrow quantities, weighting each according to the percentage of the total plot area they represented. c) for understory vegetation - from measurements of the mass of shrubs, herbs, mosses and lichens (5 samples of each category per plot), and their average nutrient concentrations determined from 6 composite samples for each category per treatment block. 69 d) for forest floor - from measurements of forest floor mass, 16 samples per treatment plot pre- and postburn, and its average nutrient concentrations from 4 composite samples per plot pre- and postburn. Because nearly all forest floor was consumed beneath windrows no postburn forest floor was collected. In areas between windrows forest floor mass was determined by three 90 m line transects used to estimate the area occupied by forest floor, and then assuming that the remaining forest floor had the same mass and nutrient concentrations as those measured preburn. Samples of ash were mistakenly not collected from windrows following the burns which made it necessary to estimate the quantity and nutrient content of ash produced. An approximation of windrow ash mass was used in combination with ash nutrient concentrations from Grier (1975) to estimate postburn nutrient quantities present in windrow areas. The forest floor samples were the ones used to estimate forest floor mass, described in chapter 2. The mineral soil samples were collected from beneath the forest floor samples. Within each plot, 5 of the samples had their volumes measured in the field to estimate bulk density. Forest floor mass was determined by destructive sampling of 20 x 20 cm square plots down to mineral soil. Forest floor was also sampled again in 1987 which gave one year post-burn results for the low severity burns in fresh slash, moderate severity burns, and high severity burns and 2 month post-burn results for the low severity burns in cured slash. The sampling method for 1987 was identical to the method used immediate post-burn and pretreatment. 70 e) for the 0-15 cm layer of mineral soil - from measurements of bulk density of the < 2 mm fraction, 15 samples from broadcast areas, 9 samples from between windrow areas, and 9 samples from beneath windrow areas post-treatment (unpublished data from R. Trowbridge), and its average nutrient concentrations from 4 composite pretreatment samples and 4 composite post-treatment samples per site preparation/fire severity treatment. It was assumed that the broadcast area bulk densities were unchanged following treatment and therefore were representative of pretreatment values. During August 1985, pretreatment mineral soil samples were collected from each of the 21 experimental plots in the study area. Twenty-one randomly located samples of each of the mineral soil and forest floor were collected for chemical analysis from each of the treatment plots, while 16 such samples were collected from the control plots. The first postburn mineral soil (0-15 cm layer) sampling was conducted during August, 1987. Nineteen samples were collected from each of the treated and control plots. Three of the 19 samples were used to estimate the bulk density while the remaining 16 were analyzed for chemistry in an identical fashion to the prebura samples. 71 Laboratory procedures 1. Mineral soil analysis The mineral soil samples collected for bulk density determination were dried at 105°C, weighed, then sieved to obtain the < 2 mm fraction which was weighed again. This allowed the determination of coarse fragment content and the mass of the nutrient-containing < 2 mm fraction present per unit volume of soil. The remaining 16 mineral soil samples were air dried in the laboratory and then sieved to retain the < 2 mm fraction. A portion of this fraction was set aside for analysis of mineralizable N . The remainder were oven dried at 70°C then the samples from each of the treated plots were bulked into 4 groups of 4 samples, which were then subjected to chemical analysis. For the control plots analyses were done on each of the 16 samples. Soil pH was measured with an Orion pH meter using a 1:1 suspension in water, as described by Lavkulich (1978). Total N was determined by semimicro Kjeldahl digestion followed by colorimetric estimation of N H 4 - N using a Technicon Autoanalyzer II for pretreatment samples and a Technicon TRAACS 800 continuous flow analyzer for postburn samples. Mineralizable N was determined by the anaerobic incubation method of Page et al. (1982). Released N H 4 was determined colorimetrically by a Technicon Autoanalyzer II for the pretreatment samples and by a Technicon TRAACS 800 continuous flow analyzer for the postburn samples. Available P was determined by the Bray P method of acid ammonium fluoride extraction (Page et al. 1982) followed by colorimetric determination of P 0 4 using a Technicon Autoanalyzer II for pretreatment samples and a Technicon TRAACS 800 continuous flow analyzer for postburn samples. Total S was determined using a Leco SC-72 32 Sulphur Determinator (which involves sample pyrolysis and infrared detection of the evolved S 0 2 gas) for pretreatment samples and using a Fisher model 475 Sulphur Analyzer for postburn samples. Extractable K, Mg and Ca were determined by using a Morgan's extraction solution of pH 4.8 sodium acetate (Greweling and Peech 1960). The extracted cations were measured by atomic absorption spectrophotometry. 2. Forest floor analysis The 5 forest floor samples collected for bulk density analysis were oven-dried at 105°C, and weighed. The mass of these samples was divided by their volume (determined in the field) to yield bulk density. The remaining 16 forest floor samples were dried at 70°C in the laboratory. After weighing they were bulked in groups of 4 then subsamples were ground and analyzed for nutrient content. Total N and P were determined by using a Parkinson and Allen (1975) digestion followed by analysis of N H 4 and P 0 4 in solution using a Technicon Autoanalyzer II for pretreatment samples and a Technicon TRAACS 800 continuous flow analyzer for postburn samples (Parkinson and Allen 1975). Total S was determined using a Leco SC-32 Sulphur Determinator for pretreatment samples and using a Fisher model 475 Sulphur Analyzer for postburn samples. Total K, Na, Mg, and Ca were determined by either 1) dry ashing at 475°C for 3 hours, then dissolving the ash in HC1, diluting this solution with distilled water, and measuring the cation concentrations in solution by atomic absorption spectrophotometry or by 2) using a Parkinson and Allen digestion followed by measurement of cations by atomic absorption spectrophotometry. 73 3. Statistical analysis Organic matter and soil chemical and physical data were analyzed with the objective of determining -a) if nutrient quantities in slash, forest floor, surface mineral soil and for the total above ground biomass, were influenced by site preparation treatment and fire severity. b) if quantities of nutrients lost were correlated with fuel consumption variables. c) the relationship between the % loss of organic matter (slash and forest floor) and percent loss of nutrients. Objective a) was achieved by subjecting chemical and physical data to a two way analysis of variance, testing the following null hypotheses: H Q I : Fire severity had no effect on the variable of interest. HQ2: Site preparation treatment had no effect on the variable of interest. FLj3: There were no fire severity x site preparation treatment interactions with respect to the variable of interest. Significant group means were distinguished using Tukey's HSD multiple comparison test to determine how nutrient quantities changed as a function of fire severity level. For the two way analysis of variance the assumption of normality could not be tested because of the limited number of data points. To test the assumption of homogeneity, residuals were plotted against estimated values to determine if the data exhibited heteroscedasticity. A l l percent consumption data were transformed using an arcsine transformation to normalize the data (Zar 1984). Objectives b) and c) were achieved by determining the highest Pearson correlation coefficient between both the absolute and relative loss of each nutrient and fuel 74 consumption variables (which included forest floor consumption and depth-of-burn for broadcast burns, fine slash (< 1 cm diameter) consumption, medium slash (1-7 cm diameter) consumption, large slash (> 7 cm diameter) consumption, and total slash consumption). Slash consumption variables were correlated separately for broadcast burns, windrow burns, and broadcast and windrow burns combined. Results and Discussion 1. Nutrients in the undisturbed ecosystems The largest quantity of nutrients in the pretreatment lodgepole pine ecosystem was contained in the mineral soil (Table 3-1). Forest floor total N ranged from 388-965 kg/ha, while P, K and S were similar to each other ranging from 30-76, 30-75, and 30-75 kg/ha, respectively (Appendix 3-5). Sodium exhibited the lowest nutrient quantities measured in forest floor, ranging from 3-8 kg/ha. Calcium quantities ranged from 82-204 kg/ha while Mg ranged from 25-62 kg/ha. Pretreatment forest floor biomass was estimated to be between 31,000-77,000 kg/ha. The next largest reserve of nutrients was measured in lodgepole pine biomass. The average nutrient quantities in these trees for all the experimental plots are given in Table 3-1 and for individual plots in Appendix 3-3. Nitrogen quantities were the highest of all nutrients measured in all components (stemwood, stembark, needles, live branches, dead branches and roots). Total average N content of all components for all experimental plots was 226 kg/ha. 75 Table 3-1. Pretreatment nutrient quantities (kg/ha) and mass of lodgepole pine, understory vegetation, dead woody materials, forest floor and mineral soil averaged over all experimental plots. Component Mass N T o t a l N M i n e r a l i z a b l e P K Na E x t r a c t a b l e Mg Ca S T o t a l 1) Lodgepo I e pine t rees Stemwood 51000 57 - 10 23 2 13 31 1 1 Stembark 8000 26 - 3 9 0 6 17 4 Needles 6000 63 - 9 12 1 13 30 8 L i v e branch 1 0000 51 - 7 8 1 5 18 6 Dead branch 4000 1 1 - 0 3 0 3 4 1 Roots 1 4000 1 8 - 1 6 1 5 1 0 3 2) U n d e r s t o r y veget a t i o n Shrubs 552 8 - 1 2 0 1 2 1 Herbs 167 2 - 0 1 0 0 4 0 Mosses/Lichen 3019 72 - 3 6 0 2 12 4 3) Dead woody mater i a I s < 1cm f u e l s 850 6 - 0 0 0 0 2 1 1 - 7cm f u e l s 9800 8 - 0 1 0 1 7 1 > 7cm f u e l s 1 47200 80 - 3 7 2 20 97 1 0 4 ) F o r e s t f l o o r 48000 596 - 47 46 5 39 126 46 5) M i n e r a l s o i l 1035000 1 138 3 49 182 - 85 459 98 A l l nutrients are totals with the exception of mineral soil available P and mineral soil exchangeable cations. 76 Sodium quantities were the lowest of any nutrient measured for all components. The total average sodium content of all components for all experimental plots was 4 kg/ha. Although foliage had the highest concentrations of nutrients (Appendix 3-1), stemwood contained the largest quantities of nutrients measured, with the exception of Mg whose stemwood concentrations were relatively low (Appendix 3-1). The relatively high quantities of nutrients in stemwood can be explained by its relatively high mass (Table 3-1). Understory vegetation nutrient quantities were highest for mosses plus lichens for all nutrients measured (Table 3-1). The quantity of N contained in mosses and lichens was, on average almost 10 times greater than that contained in herbs, which can be attributed partly to the greater biomass of mosses plus lichens (Table 3-1). No detectable quantities of Na were measured in either herbs or shrubs and only a small amount was measured in mosses and lichens (Table 3-1). Calcium represented the second most abundant nutrient after N with 18 kg/ha being present in the understory - substantially lower than the 81 kg/ha of N (Table 3-1). Of all the ecosystem components studied dead woody materials had the lowest nutrient concentrations (Appendix 3-1). Although the average total estimated biomass for dead woody materials far exceeded that of any of the other biomass categories measured (Table 3-1). Nutrient concentrations were extremely low for the 1-7 and >7 cm size classes (Appendix 3-1). The < 1 cm size class had higher concentrations but the overall mass of this size class was small in relation to the other 2 size classes measured (Appendix 3-1). Nutrient quantities in mineral soil were similar in proportion to the quantities of surface biomass. The quantity of N contained in the surface 15 cm of mineral soil was the largest of any soil nutrients measured (Table 3-1). Mineralizable N quantities were lowest of all 77 soil nutrients, quantified possibly due to analytical procedures (H 20/KC1) (Table 3-1). The total N reserve in mineral soil was greater than the N content of the biomass. Calcium mineral soil quantities, as with biomass, were the second most abundant after nitrogen (Table 3-1). Mineral soil extractable P quantities were all below 100 kg/ha which was low in relation to all other nutrients quantified, with the exception of mineralizable N (Table 3-1). 2. Nutrients in the disturbed ecosystems Nutrient changes in forest floor Changes in forest floor nutrient content result from changes in forest floor nutrient concentrations and forest floor mass. Burning-induced increases in nutrient concentration and reduction in forest floor mass, may cause increases, decreases, or no net change in nutrient content depending on the relative magnitude of the changes in concentrations and mass. When slashburning consumes some of the forest floor but causes slight increases to decreases in nutrient concentrations, forest floor nutrient content will be generally be reduced. Forest floor nutrient changes may also be influenced by ash from slash which may become part of the forest floor following burning. Treatment induced changes in forest floor nutrient quantities are given in Table 3-2. The greatest losses were for N , with a range of 232 to 894 kg/ha. In general, losses decreased in the order N > C a > S > P » K « Mg > Na. The range and magnitude of these losses reflects the varying degrees of forest floor loss due to the treatments and the varying amounts of ash and charcoal deposited on the forest floor from the burned slash. In general, losses from the windrow treatments exceeded losses from the knockdown treatments. 78 Table 3-2. Estimated nutrient changes (kg/ha) in the forest floor following the burns in the experimental plots. T reatment/PIot Na Mg Ca Low s e v e r i t y burns i n f r e s h s l a s h a) b r o a d c a s t burns P l o t 2 P l o t 17 AVERAGE b) windrow burns P l o t 7 P l o t 10 AVERAGE 393 , 232 . 312. 703. 388. 546 . 1 18. 1 1 . 1 4 . 51 . 30. 41 . 10. 6 . 8. 51.4 30. 1 40.8 44.5 25 . 1 34.8 26.1 17.5 21.8 142. 82. 112, 33.8 19.8 26.8 54.3 30 . 1 42.2 Low s e v e r i t y burns i n cured s l a s h a) b r o a d c a s t burns P l o t 1 297.5 9.0 -13.4 0.3 -2.7 43.5 19.9 P l o t 4 256.0 10.2 -5.4 0.6 1.3 40.8 17.7 AVERAGE 276.8 9.6 -9.4 0.5 -0.7 42.2 18.8 b) windrow burns P l o t 3 561.0 44.3 43.5 4.5 36.5 119.4 .43.6 P l o t 5 455.0 36.2 35.6 3.9 30.0 102.2 35.8 AVERAGE 508.0 40.3 39.6 4.2 33.3 110.8 39.7 Moderate s e v e r i t y burns a) b r o a d c a s t burns P l o t 8 564.2 27.8 P l o t 11 291.2 15.3 "AVERAGE 427.7 21.6 b) w i ndrow burns P l o t 12 426.4 33.7 P l o t 16 464.0 36.6 AVERAGE 445.2 35.2 0 . 3. 2. 33 , 35 , 34. -7.4 -3.2 -5.3 1 . 2. 2 . 27. 30 . 20 , 16. 18, 28.8 90. 1 98. 1 94 . 1 49. 25 . 37. 33 . 35 . 34 . High s e v e r i t y burns a) b r o a d c a s t burns P l o t 9 326.5 8.3 -13.7 -4.5 -0.7 -39.4 23.5 P l o t 13 337.7 13.7 -2.8 -2.6 5.6 -9.1 24.8 P l o t 14 247.4 13.3 -4.6 -3.0 4.8 -14.0 25.4 AVERAGE 303.9 11.8 -7.0 -3.4 3.2 -20.8 24.6 b) windrow burns P l o t 15 894.1 70.3 68.9 7.0 57.0 186.2 68.9 P l o t 18 764.3 60.6 59.4 6.1 49.2 160.4 59.1 AVERAGE 829.2 65.5 64.2 6.6 53.1 173.3 64.0 Negative values represent gains by the forest floor. 79 Relative forest floor nutrient losses for all windrow plots studied were greater than 90%, indicating that different fire severities had little effect on the loss of nutrients for this treatment (Table 3-2). The broadcast burn losses of N , P, and S determined for the high severity burns were lower than those of the moderate severity burns due probably to forest floor mass variability, nutrient concentration variability and/or sampling error. Variability in broadcast burn forest floor losses may also have been caused by other factors including forest floor moisture content, preburn slash fuel loadings and the type of ignition pattern used. Even though there were increasing losses of forest floor and N , P, and S with increasing fire severity the high spacial variability of forest floor mass confounded results, making comparisons difficult. Statistically significant differences in forest floor mass losses and depth-of-burn between the different fire severity levels were not found (chapter 2) so similar results were expected for N , P, and S losses. Relative P losses from the broadcast burns were lower than those of N (Table 3-3). This may be due to the greater susceptibility of N to volatilization whereas P losses occur primarily in particulate form (Raison 1985b). Tiedemann (1987) demonstrated the high susceptibility of S to loss by volatilization and the effect of increased burning temperatures on the amount of S lost during combustion. Although the present study did not demonstrate a definitive increasing loss of sulphur with increasing fire severity it is reasonable to assume that, with more replication and reduced variability, this might be the case. The four cations (K, Na, Mg, and Ca) were found to either increase or decrease in the forest floor, with different site preparation and fire severities. Increases in total forest floor 80 Table 3-3. Estimated relative nutrient changes (%) in the forest floor following the burns in the experimental plots. T r e a t m e n t / P l o t N Low s e v e r i t y burns i n f a) b r o a d c a s t burns P l o t 2 Broadcast 58 P l o t 17 Broadcast 60 AVERAGE 59 b) windrow burns P l o t 7 Windrow 89 P l o t 10 Windrow 99 AVERAGE 94 Low s e v e r i t y burns i n c a) b r o a d c a s t burns P l o t 1 Broadcast 61 P l o t 4 Broadcast 66 AVERAGE 64 b) windrow burns P l o t 3 Windrow 97 P l o t 5 Windrow 86 AVERAGE 92 Moderate s e v e r i t y burns a) b r o a d c a s t burns P l o t 8 Broadcast 58 P l o t 11 Broadcast 61 AVERAGE 60 b) windrow burns PIot 12 W i nd row 99 P l o t 16 Windrow 99 AVERAGE 99 High s e v e r i t y burns a) b r o a d c a s t burns P l o t 9 Broadcast 58 P l o t 13 Broadcast 66 P l o t 14 Broadcast 64 AVERAGE 63 b) windrow burns P l o t 15 Windrow 98 P l o t 18 Windrow 98 AVERAGE 98 P K Na esh s l a s h 34 19 2 36 23 7 35 21 5 82 84 89 99 99 99 91 92 94 red s l a s h 8 -35 7 33 -18 19 21 -27 13 97 98 98 87 87 93 92 93 96 36 1 -96 41 10 -84 39 6 -90 99 99 99 99 99 99 99 99 99 19 -31 -99 34 -7 -42 31 -11 -68 28 -16 -70 97 97 96 99 98 98 98 98 97 Mg Ca S 14 18 65 17 21 66 16 20 66 87 85 89 99 99 99 93 92 94 -29 42 53 5 49 59 - 1 2 4 6 5 6 . 98 98 98 88 92 88 93 95 93 3 10 67 9 16 69 6 13 68 99 99 99 99 99 99 99 99 99 2 -33 54 17 -8 62 14 - 12 61 11 - 18 59 97 96 97 98 98 98 98 97 98 Negative values represent nutrient gains by the forest floor. 81 nutrient quantities can be explained by the deposition of nutrient rich ash and slash particles which drop down onto the forest floor during the burning of slash. When compared to N and S losses of cations were generally lower for the different broadcast burns studied. This may be due to the susceptibility of N and S to large volatilization losses while cation losses are via particulate pathways. A significant interaction between site preparation treatment and fire severity was found for P, K, Na, Mg, Ca, and S losses (Figure 3-1 to 3-9). The interaction was the result of increased losses for high severity windrow burns when compared to moderate severity windrow burns, while high severity broadcast burns had decreased losses compared to moderate severity broadcast burns. For all nutrients quantified, A N O V A indicated that differences between windrow and broadcast treatments were statistically significant (p <0.05) but that fire severity had no significant effect on forest floor nutrient losses (Appendix 3-10). Results of Tukey's (HSD) multiple comparison test showed that high severity windrow burn losses were significantly different when compared to high severity broadcast burns (Appendix 3-11). Violation of A N O V A assumptions, in both untransformed and transformed variables, prevented interpretation of relative nutrient loss results. The scatter plot of residuals indicated that variances were not homogenous. Losses of forest floor N , P, Na, and S during broadcast burning were significantly (p<0.01) correlated with forest floor consumption (Table 3-4). Broadcast burn forest floor losses of P and S were significantly (p<0.01) correlated with fine (< 1 cm) broadcast burn slash consumption (Table 3-4). 82 70 Low-fresh Lov^cured Moderate High F i re severity • B-nodcost burns + Windrow bLITIS Figure 3-1 Site preparation and fire severity treatment interaction for forest floor phosphorus changes. 83 Figure 3-2 Site preparation and fire severity treatment interaction for forest floor potassium changes. Negative values indicate gains in forest floor potassium. 84 Low-fresh Low-cured Moderate High F i re severity • Broodcost burns + Windrow burns rigure 3-3 Site preparation and fire severity treatment interaction for forest floor sodium changes. Negative values indicate gains in forest floor sodium. 85 BO Low-fresh Low-cured Moderate High F i re severity • B-nodcost burns + Windrow burns Figure 3-4 Site preparation and fire severity treatment interactions for forest floor magnesium changes. Negative values indicate gains in forest floor magnesium. 86 1B0 170 160 150 140 130 -120 110 -1D0 90 80 70 -| 60 50 -40 -30 -20 10 H 0 Low-fresh Low-cured Broodcost burns F i re severity Moderate Windrow burns High Figure 3-5 Site preparation and fire severity treatment interaction for forest floor calcium changes. Negative values indicate gains in forest floor calcium. 87 Figure 3-6 Site preparation and fire severity treatment interaction for forest floor sulphur losses. 88 Figure 3-7 Site preparation and fire severity interaction for phosphorus mineral soil changes. Negative values indicate gains in mineral soil phosphorus. 89 100 Low-fresh Low-cured Moderate High F i re Severity • Broadcast burns + Windrow burns Figure 3-8 Site preparation and fire severity interaction for potassium mineral soil changes. Negative values indicate gains in mineral soil potassium. 90 Figure 3-9 Site preparation and fire severity interaction for magnesium mineral soil changes. Negative values indicate gains in mineral soil magnesium Table 3-4. Correlations between nutrient changes in forest floor and fuel consumption variables in broadcast burn plots. N u t r i e n t s N P K Na Mg Ca S 1) TOTAL N U T R I E N T L O S S E S F o r e s t f l o o r c o n s u m p t i o n 0 . 8 3 * * 0 . 8 2 * * 0 . 0 5 - 0 . 7 7 * * 0 . 1 5 - 0 . 1 5 0 . 8 6 * * D e p t h - o f - b u r n 0 . 0 0 0 . 2 7 0 . 3 1 - 0 . 3 1 0 . 6 5 - 0 . 4 8 0 . 2 4 F i n e s l a s h < 1 cm c o n s u m p t i o n - 0 . 6 3 - 0 . 7 3 * - 0 . 5 9 0 . 3 5 - 0 . 5 7 0 . 1 0 - 0 . 7 6 * * M e d i u m s l a s h 1-7 cm c o n s u m p t i o n 0 . 1 0 0 . 1 0 - 0 . 0 2 - 0 . 6 0 0 . 0 8 ^ 0 . 5 9 0 . 1 2 L a r g e s l a s h > 7 cm c o n s u m p t i o n - 0 . 1 1 - 0 . 1 0 - 0 . 4 6 - 0 . 3 7 - 0 . 1 9 - 0 . 3 4 - 0 . 0 7 T o t a l s l a s h c o n s u m p t i o n - 0 . 0 9 - 0 . 0 8 - 0 . 4 2 - 0 . 4 4 - 0 . 1 6 - 0 . 4 2 - 0 . 0 5 2 ) R E L A T I V E T O T A L N U T R I E N T L O S S E S F o r e s t f l o o r c o n s u m p t i o n - 0 . 0 9 0 . 2 1 - 0 . 0 1 - 0 . 4 9 0 . 0 8 - 0 . 2 9 0 . 2 5 D e p t h - o f - b u r n 0 . 0 7 0 . 3 3 0 . 3 7 - 0 . 8 2 * * 0 . 5 2 - 0 . 5 3 0 . 3 8 F iner s l a s h < 1 cm c o n s u m p t i o n 0 . 4 6 - 0 . 3 2 - 0 . 5 8 0 . 4 2 - 0 . 3 7 - 0 . 2 7 - 0 . 5 1 M e d i u m s l a s h 1-7 cm c o n s u m p t i o n - 0 . 0 5 0 . 3 2 0 . 0 5 - 0 . 6 6 0 . 2 9 - 0 . 5 9 0 . 2 9 L a r g e s l a s h > 7 cm c o n s u m p t i o n 0 . 3 9 0 . 0 2 - 0 . 4 9 - 0 . 2 8 - 0 . 0 2 - 0 . 2 8 - 0 . 2 0 T o t a l s l a s h c o n s u m p t i o n 0 . 3 4 0 . 0 7 - 0 . 4 3 - 0 . 3 7 0 . 0 3 - 0 . 3 6 - 0 . 1 3 * indicates correlation coefficients are significant (p<0.05) ** indicates correlation coefficients are significant (p<0.01) Correlation coefficients are for n = 9 92 The nutrient changes caused by broadcast burns fell within the range of forest floor nutrient changes found in other B.C. studies. Taylor and Feller (1987) found similar forest floor nutrient changes for low and moderate severity plots in a broadcast burn in two ecosystems dominated by "interior spruce" (Picea glauca x engelmannii) in the Sub-Boreal Spruce zone. Feller (1983) reported nutrient losses from forest floor for slashburns in west coast, Tsuga heterophylla - Pseudotsuga menziesii - Thuja plicata forests which were comparable to the results of this study. Only one study quantified nutrient losses caused by burning of windrow organic matter (Benson 1982). The results reported from this study, however, determined the nutrient losses from both slash and forest floor combined making forest floor loss comparisons impossible. Forest floor nutrient losses from high severity windrow burns exceeded any of those reported in the literature. The nutrient losses in this study are higher for several reasons. Firstly, no other study in the literature investigated' forest floor losses seperately from slash during windrow burns. Secondly, no study looked at windrow burning independent of slash removal by timber harvesting activities. In this study higher pretreatment nutrient quantities would be expected as no slash was removed prior to burning. It would also be reasonable to assume that nutrient loss through particulate mechanisms would be increased as windrow fire intensity increases causing greater convective forces. Windrow burns, with a greater fuel consumption and rate of heat output, would be more intense than operational broadcast burns. Changes in forest floor nutrient quantities measured one year following treatment ( as compared to pretreatment values) decreased in the following order: N > C a > P > S > Mg > K > Na (Table 3-5). Forest floor N , P, K, Mg and S changes were similar to those 93 Table 3-5. Immediate and one year postburn estimated nutrient changes (kg/ha) in the forest floor caused by broadcast burn treatments. T r e a t m e n t / P l o t N P K Na Mg Ca S 1) IMMEDIATELY POSTBURN Lou s e v e r i t y burns in f r e s h s l a s h (May 1986) P l o t 2 393.7 18.2 10.2 0 . 1 6. 1 26. 1 33 .8 P l o t 17 232 .0 11.2 6.8 0 . 2 4 . 3 17. 5 1 9 . 8 AVERAGE 312.9 14.7 8.5 0. 2 5 . 2 21 . 8 26 . 8 Low s e v e r i t y burns i n cured s l a s h (May 1987) P l o t 1 297.5 9.0 -13.4 0. 3 -2. 7 43 . 5 1 9 . 9 P l o t 4 256 .0 10.2 -5.4 0 . 6 1 . 3 40 . 8 1 7 .7 AVERAGE 276 . 8 9.6 -9.4 0 . 5 - 0 . 7 42 . 2 18 .8 Moderate s e v e r i t y burns (J une 1986) P l o t 8 564 .2 27.8 0.9 -7. 4 1 . 6 20 . 5 49 . 7 P l o t 11 291.2 15.3 3 . 7 -3 . 2 2 . 7 1 6 . 0 25 . 4 AVERAGE 427.7 21.6 2.3 -5 . 3 2 . 2 18. 3 37 . 6 High s e v e r i t y burns ( J u l y 1986) P l o t 9 326 .5 8.3 -13.7 -4 . 5 -0. 7 -39. 4 23 .5 P l o t 13 337.7 13.7 -2.8 -2. 6 5 . 6 -9. 1 2 4 78 P l o t 14 247.4 13.3 -4.6 -3. 0 4 . 8 -14. 0 25 .4 AVERAGE 303.9 11.8 -7.0 -3. 4 3 . 2 -20. 8 24 . 6 1) ONE YEAR POSTBURN Low s e v e r i t y burns i n f r e s h s l a s h ( Aug . 1986) P l o t 2 376 . 2 27.7 3.4 2 . 0 3. 0 -43 . 1 1 9 . 7 .Plot 17 222.4 16.4 3.0 1 . 2 2 . 6 -20. 7 1 2 . 0 AVERAGE 299.3 22.1 3 . 2 1 . 6 2. 8 -31 . 9 1 5 .6 Low s e v e r i t y burns i n cured s l a s h (Aug . 1987) * P l o t 1 262 .1 14.2 -11.9 0. 3 2 . 5 -54 . 3 16 .2 P l o t 4 231.6 13.8 -4.3 0. 6 4 . 9 -26. 9 1 5 . 2 AVERAGE 246 .9 14.0 -8.1 0. 5 3 . 7 -40 . 6 1 5 . 7 Moderate s e v e r i t y burns (Aug. 1986) P l o t 8 580.3 34 . 1 -12.1 2 . 5 -3. 1 -27. 3 44 . 8 P l o t 11 298 . 7 18.2 -3.2 1 . 4 0. 6 -6. 1 1 7 .2 AVERAGE 439 . 5 26 . 2 -7.7 2 . 0 - 1 . 9 - 16. 7 31 . 0 High s e v e r i t y burns (Aug. 1986) P l o t 9 349.2 20.4 - 10.9 0. 2 -0. 7 - 10. 1 13 .6 P l o t 13 354 . 5 22.7 -0.7 0. 9 5 . 6 12. 8 1 7 .5 P l o t 14 365 .7 23 . 1 -2.3 0 . 8 4 . 8 9. 7 1 7 .4 AVERAGE 356 .5 22 . 1 -4.6 0. 6 3 . 2 4. 1 16 . 2 Negative values represent gains by the forest floor. •Actually 2 month postburn 94 measured immediately postburn (Table 3-5). Small differences measured between the immediate and one year postburn periods for these nutrients were probably the result of seasonal variation or sampling error. The effects of the treatments on forest floor nutrients can be summarized as follow: 1. Windrow burning caused greater changes than broadcast burning. This was expected as windrowing concentrated the forest floor with slash into piles and these large accumulations of fuels were in all cases almost completely consumed by the windrow fires. 2. The burning conditions had no significant effect on nutrient losses from the forest floor in windrow plots, which averaged more than 90% of the preburn nutrient quantities for all burning conditions or fire severity levels. 3. A l l treatments caused losses of forest floor N , P and S while some gains and some losses of K, Na, Mg, and Ca were found. Increases in forest floor cations after burning can be explained by the deposition of cation rich-ash and slash particles from burning slash. 4. Forest floor nutrient losses generally decreased in the order N > C a > S > P > K > Mg > Na - while relative losses for broadcast burns generally followed the order N > S > P > C a > K > Mg > Na. Relative losses for windrow burns followed no consistent trend as changes in individual nutrients were all very high and similar. 5. Burning cured fuels tended to cause smaller nutrient losses than burning fresh fuels but the differences were not statistically significant. 95 Nutrient changes in the slash The absolute nutrient losses from slash were higher than losses from forest floor, with the exception of N which was found to have greater losses from forest floor. For the broadcast burns, relative losses from the slash were also generally greater than those from the forest floor. For windrow burns, relative losses from slash were similar to those found for the forest floor. Nutrient losses from the slash generally decreased in the order N > Ca > K, Mg > S > P > Na, which differed from the forest floor in that S and P losses were less relative to those of Ca, K and Mg (Table 3-6). Nutrient losses generally increased with fire severity for both windrow and broadcast burning treatments, and were generally greater for windrow than for broadcast burning treatments (Table 3-6). Relative losses of K, Mg, and Ca in the broadcast plots were, on average, lower than losses obtained for N and P (Table 3-7). Cation losses from broadcast slash fuels averaged between 72-92%, with losses generally decreasing in the order- low severity fresh > moderate severity > high severity > low severity cured. Relative losses of nutrients from slash in were very high (> 90%) and similar for all windrow treatments (Table 3-7). With the exception of N , broadcast plots in cured slash were found to have slightly lower nutrient losses when compared to fresh slash. Since the difference between these two treatments was small it may be assumed this was not a treatment effect but more likely a function of site differences or measurement errors. Variation in slash chemistry, slash loading, slash distribution and slash moisture content may all have contributed to site differences. Table 3-6. Estimated nutrient losses (kg/ha) from slash during the burns in the experimental plots. T r e a t m e n t / P l o t N P K Na Mg Ca S Lou s e v e r i t y burns i n f r e s h s l a s h a) b r o a d c a s t burns P l o t 2 182 .9 23.3 44. 5 4. 9 51 . 7 138. 9 27 .3 P l o t 17 256 .6 31 .5 56. 9 5 . 0 48. 0 1 26 . 8 23 . 3 AVERAGE 219 .8 27.4 50. 7 5 . 0 49. 9 132. 9 25 . 3 b) windrow burns P l o t 7 327 . 1 33.4 70 . 1 6. 6 66. 6 212. 1 44 . 2 P l o t 10 295 . 8 29.6 61 . 2 6. 1 63 . 2 201 . 2 40 . 4 AVERAGE 311 .5 31.5 65 . 7 6. 4 64. 9 206. 7 42 .3 Low s e v e r i t y burns i n cured s l a s h a) b r o a d c a s t burns P l o t 1 217 . 5 17.8 34. 1 3. 6 39. 3 124. 0 17 .4 P l o t 4 270 .3 21 .7 38. 8 4 . 5 51 . 7 172. 3 22 .3 AVERAGE 243 .9 19.8 36 . 5 4 . 1 45 . 5 148. 2 19 .9 b) windrow burns P l o t 3 324 . 4 33.3 70 . 0 6. 8 65 . 6 209 . 3 44 . 5 P l o t 5 276 . 7 25 .9 51 . 6 5 . 5 60 . 7 208 . 2 37 .3 AVERAGE 300 . 6 29.6 60 . 8 6. 2 63. 2 208. 8 40 .9 Moderate s e v e r i t y burns a) b r o a d c a s t burns P l o t 8 289 . 0 31.4 47. 5 5 . 9 54. 6 149. 7 36 . 6 P l o t 11 384 . 5 41.4 66. 4 7. 3 75 . 4 213. 2 48 .9 AVERAGE 336 .8 36.4 57. 0 6. 6 65 . 0 181 . 5 42 .8 b) windrow burns PI o r 12 383 .8 40.9 83. 6 7. 5 80 . 3 249. 2 51 .9 P l o t 16 348 .5 37.7 76. 5 6. 8 70. 7 216. 3 46 .8 AVERAGE 366 .2 39.3 80. 1 7. 2 75 . 5 232 . 8 48 .9 High s e v e r i t y burns a) b r o a d c a s t burns P l o t 9 371 .4 40 . 9 71 . 5 6. 6 73 . 6 206 . 8 48 . 7 P l o t 13 323 .7 36.2 51 . 1 6. 0 61 . 0 147. 1 41 .4 P l o t 14 323 .0 32.7 51 . 8 5 . 7 64 . 5 188. 2 41 . 5 AVERAGE 339 .4 36.6 58. 1 6. 1 66. 4 180 . 7 43 .9 b) windrow burns P l o t 15 403 . 9 42.8 85 . 5 7. 7 82 . 6 255 . 1 54 . 1 P l o t 18 362 . 1 45 . 1 89. 5 6. 8 70 . 5 176. 9 49 . 7 AVERAGE 383 . 0 44.0 87. 5 7. 3 76. 6 216. 0 5 1 . 9 97 Table 3-7. Estimated relative nutrient losses (%) from slash during the burns in the experimental plots. T reatment/PIot N P K Na Mg Ca S Low s e v e r i t y burns i n f r e s h s l a s h a) b r o a d c a s t burns P l o t 2 Broadcast 93 94 83 94 89 86 81 P l o t 17 Broadcast 88 95 84 89 83 76 59 AVERAGE 91 95 84 92 86 81 70 b)wi ndrow burns P l o t 7 Windrow 98 99 97 99 98 97 98 P l o t 10 Windrow 98 99 96 97 97 96 97 AVERAGE 98 99 97 98 98 97 98 Low s e v e r i t y burns i n cured s l a s h a ) b r o a d c a s t burns P l o t 1 Broadcast 95 90 77 73 80 70 56 P l o t 4 Broadcast 96 91 77 76 82 74 57 AVERAGE 96 91 77 75 81 72 57 b)wi ndrow burns P l o t 3 Windrow 99 99 98 99 99 98 99 P l o t 5 Windrow 98 98 94 96 97 95 96 AVERAGE 99 99 96 98 98 97 98 Moderate s e v e r i t y burns a ) b r o a d c a s t burns P l o t 8 Broadcast 94 99 70 89 85 73 87 P l o t 11 Broadcast 95 99 77 92 89 78 89 AVERAGE 95 99 74 91 87 76 88 b)windrow burns P l o t 12 Wi ndrow 99 99 99 99 99 98 99 P l o t 16 Windrow 99 99 98 99 99 98 99 AVERAGE 99 99 99 99 99 98 99 High s e v e r i t y burns a ) b r o a d c a s t burns P l o t 9 Broadcast 96 99 85 88 92 82 93 P l o t 13 Broadcast 91 96 68 88 83 62 86 P l o t 14 Broadcast 94 89 75 83 88 76 89 AVERAGE 94 95 76 86 88 73 89 b)windrow burns P l o t 15 Windrow 99 99 97 97 98 96 98 P l o t 18 Windrow 98 99 96 94 96 92 97 AVERAGE 99 99 97 96 97 94 98 Percentage losses were calculated based on preburn nutrient quantities in aboveground organic matter and tree roots. 98 Both the type of site preparation (knockdown vs windrowing) and fire severity significantly (p < 0.05) effected the quantity of all nutrients lost from slash with the exception of Ca which was only significantly effected by the type of site preparation (Appendix 3-10). The reason Ca was not significantly influenced by fire severity was likely due to variability in the content of slash Ca. Of all slash nutrients quantified Ca had the highest variability, making detection of fire severity differences difficult. Tukey's (HSD) multiple comparison test differentiated the low cured fire severity type as being significantly (p<0.05) different from the high severity fire type for N . For P, Tukey's test differentiated the low severity cured fire type as being significantly (p < 0.05) different from the moderate and high severity types and the low severity burns in fresh slash as being different from the high severity burns. Tukey's test also differentiated the low severity cured slash as being significantly (p<0.05) different from the moderate severity burns for Na. The comparison test could not distinguish differences for K and Mg but found that the low severity cured slash burns were significantly (p <0.05) different from the high severity ones for S (Appendix 3-11). A l l broadcast burn losses of slash nutrients, with the exception of calcium, were significantly (p<0.05) correlated with medium (1-7 cm) slash consumption (Table 3-8). Broadcast burn calcium slash losses were significantly (p<0.01) correlated with large (> 7 cm) slash consumption (Table 3-8). Broadcast burn slash losses of N , Mg, Ca, and S were significantly (p<0.05) correlated with total slash consumption (Table 3-8). Relative broadcast burn slash losses of K were significantly (p<0.01) correlated with forest floor consumption (Table 3-8). Relative broadcast burn P and S slash losses were significantly (p<0.01) correlated with medium (1-7 cm) slash consumption (Table 3-8). Relative 99 Table 3-8. Correlations between nutrient losses in slash and fuel consumption variables for broadcast burn plots. N u t r i e n t s N P K Na Mg Ca S 1) TOTAL NUTRIENT LOSSES F o r e s t f l o o r consumption 0.12 0.13 -0. 12 0 . 28 0 . 16 0 . 04 0 .36 Depth-of-burn 0.22 0.42 0. 27 0. 37 0. 30 0. 06 0 .44 Fine s l a s h < 1 cm consumption 0.32 -0.05 -o. 04 0 . 09 0. 13 0 . 41 - 0 .07 Medium s l a s h 1-7 cm consumption 0.88** 0.90** 0. 80** 0 . 94** 0 . 90** 0 . 72* 0 .92** Large s l a s h > 7 cm consumption 0.66 0.33 0 . 22 0 . 45 0 . 65 0 . 84** 0 .58 T o t a l s l a s h consumption 0.76** 0.47 0. 36 0 . 59 0. 76** 0 . 89** 0 .70* 2) RELATIVE TOTAL NUTRIENT LOSSES F o r e s t f l o o r consumption 0.15 0.29 - 0 . 70* 0. 20 0 . 1 2 -0 . 1 9 0 .59 Depth-of-burn -0.50 -0.05 -0. 28 0 . 39 0. 25 -0. 08 0 .54 Fine s l a s h < 1 cm consumption 0.55 -0.18 0. 18 -0. 62 -0. 15 -0 . 15 -0 .39 Medium s l a s h 1-7 cm consumption 0.17 0.76** -0. 19 0 . 50 0 . 57 - 0 . 1 1 0 .76** Large s l a s h > 7 cm consumption 0.76** 0.06 -0 . 27 -0 . 24 0 . 38 -0. 1 1 0 .46 T o t a l s l a s h consumption 0.72* 0.21 -0. 27 0 . 12 0 . 45 -0. 02 0 .55 * indicates correlation coefficients are significant (p<0.05) ** indicates correlation coefficients are significant (p<0.01) Correlation coefficients are for n=9 100 broadcast burn total N slash losses were significantly (p<0.05) correlated with large (> 7cm) slash and total slash consumption (Table 3-8). In the case of windrow burns, P, K, Mg, and S losses were significantly (p<0.05) correlated with medium (1-7 cm) slash consumption while Ca losses were significantly (p < 0.05) correlated with total slash consumption (Table 3). Relative K and S losses were significantly (p<0.05) correlated with medium (1-7 cm) slash consumption (Table 3-9). When windrow and broadcast slash nutrient losses were combined, all nutrient losses from slash were significantly (p<0.01) correlated with medium (1-7 cm) slash consumption (Table 3-10). Nitrogen, Mg, Ca, and S slash losses for windrow and broadcast burns combined were significantly (p<0.05) correlated with large (< 7 cm ) slash consumption (Table 3-10). Combined windrow and broadcast N , Na, Mg, Ca, and S were significantly (p<0.01) correlated with total slash consumption (Table 3-10). A l l relative slash nutrient losses, with the exception of S for medium (1-7 cm) slash consumption, were significantly (p<0.05) correlated with medium (1-7 cm), large (> 7 cm) and total slash consumption for windrow and broadcast burns combined (Table 3-10). Nutrient loss results reported by Feller et al. (1983) and Taylor and Feller (1987) are similar to those of the broadcast burns in the present study, but less than those of the windrow burns. Losses of N , P, K, Na, and Mg from the windrow burns were higher than those of any study reviewed and were similar to those reported for whole tree harvesting operations (Kimmins 1974, Weetman and Webber 1972). This is probably due to the relatively high fuel consumption in the windrow burns. As discussed early in this chapter the lack of studies which stratified nutrient loss by either forest floor or slash prevented further comparisons. 101 Table 3-9. Correlations between nutrient losses in slash and fuel consumption variables for windrow burn plots. N u t r i e n t s N P K Na Ca S 1) TOTAL NUTRIENT LOSSES Fine s l a s h < 1 cm consumption 0.37 0.28 0 .33 0. 47 0. 36 0 . 36 0 .38 Medium s l a s h 1-7 cm consumption 0.69 0.72* 0 .79* 0. 79* 0. 55 0. 14 0 .73* Large s l a s h > 7 cm consumption -0.09 -0.44 -0 .47 -0 . 03 o. 15 0 . 74 -0 .15 T o t a l s l a s h consumption 0.11 -0.26 - 0 .24 0. 22 0. 34 0. 86** 0 . 06 2) RELATIVE TOTAL NUTRIENT LOSSES Fine s l a s h < 1 cm consumption 0.63 0.51 0 .59 0. 63 0. 66 0 . 47 0 .62 Medium s l a s h 1-7 cm consumption 0.50 0.54 0 .80* 0 . 40 0 . 39 0 . 26 0 . 73* Large s l a s h > 7 cm consumption 0.25 0.10 - 0 .02 0 . 20 0 . 33 0 . 46 0 .01 T o t a l s l a s h consumption 0.44 0.28 0 . 23 0. 35 0. 49 0. 60 0 .25 * indicates correlation coefficients are significant (p<0.05) ** indicates correlation coefficients are significant (p<0.01) Correlation coefficients are for n=8 Table 3-10. Correlations between nutrient losses in slash and fuel consumption variables for windrow and broadcast burn plots combined. N u t r i e n t s N P K Na Mg Ca S 1) TOTAL NUTRIENT LOSSES Fine s l a s h < 1 cm consumption 0.24 0.03 0.13 -0.03 0.09 0.20 -0.05 Medium s l a s h 1-7 cm consumption 0.83** 0.83** 0.87** 0.91** 0.83** 0.68** 0.87** Large s l a s h > 7 cm consumption 0.51* 0.17 0.23 0.45 0.59* 0.81** 0.51* T o t a l s l a s h consumption 0.67** 0.39 0.43 0.63** 0.74** 0.90** 0.68** 2) RELATIVE TOTAL NUTRIENT LOSSES Fine s l a s h < 1 cm consumption Medium s l a s h 1-7 cm consumption 0.85** 0.59* 0.61** 0.59* 0.77** 0.66** 0.71** Large s l a s h > 7 cm consumption 0.92** 0.64** 0.75** 0.79** 0.92** 0.88** 0.81** T o t a l s l a s h consumption 0.94** 0.71** 0.82** 0.83** 0.96** 0.92** 0.83** * indicates correlation coefficients are significant (p<0.05) ** indicates correlation coefficients are significant (p<0.01) Correlation coefficients are for n=17 103 The effects of the treatments on nutrients in the slash can be summarized as follows: 1. Absolute nutrient losses from slash followed the order: N > Ca > K, Mg > S > P > Na. 2. Losses from broadcast burns were less than those for windrow burns conducted under the same burning conditions. 3. Losses of N , P, K, Na, and Mg from the windrow burns were greater than those reported for operational slashburns and were more similar to losses reported in studies of whole tree harvesting. 4. Phosphorus, S, K, Na, Mg, and Ca losses from slash were not influenced by age of slash whereas N losses were significantly greater in fresh slash. 5. Fire severity significantly (p<0.05) influenced the loss of all nutrients from slash with the exception of Ca. 6. Absolute and relative losses of all nutrients from slash were significantly correlated with" forest floor consumption and medium slash (1-7 cm) consumption. 7. Relative losses from slash were high (> 94%) for all nutrients in the windrow burns and were also high (> 90%) in the broadcast burns for N and P. For the broadcast burns, relative losses were generally highest for N and P and least for Ca. Fire severity had no consistent effect on relative losses. Total nutrient changes in above ground biomass and forest floor When the total postburn nutrient content of organic material is compared to that preburn, it can be seen that losses generally decreased in the order - N > Ca > K, Mg, S, 104 > P > Na (Table 3-11). Nitrogen losses were particularly high, averaging from 620 to 850 kg/ha for broadcast burns and 850 to 1200 kg/ha for windrow burns, which is near the upper limit of values for broadcast burns elsewhere in B.C. (Feller 1989). Nutrient losses were almost invariably less for broadcast than for windrow burns conducted during the same burning conditions, with many of these differences being statistically significant (Appendix 3-10). For windrow burns, nutrient losses tended to increase with fire severity except for the burns in fresh slash which caused relatively high losses. Broadcast burn total N , P, and S losses increased as fire severity changed as follows: low severity cured < low severity fresh < high severity < moderate severity. With the exception of low severity burns in fresh slash, P and K losses from broadcast burns were similar for different fire severities (Table 3-11). Relative nutrient losses were lower for broadcast burns than for windrow burns. Relative nutrient losses for all windrow burns were > 90% (Table 3-12). Broadcast burn relative nutrient losses were more variable and generally did not exceed 80% (Table 3-10). -Relative losses of both N and S were found to be generally similar to, or greater than, those of the other nutrients quantified. This was probably due to differences in nutrient loss pathways, N and S being more susceptible to volatilization losses with the other nutrients being lost mainly through particulate pathways. Losses of N , P, K, Mg, and S from organic materials were significantly (p<0.05) affected by site preparation and fire severity, while losses of Ca and Na were significantly (p<0.05) affected only by site preparation (Appendix 3-10). Tukey's (HSD) multiple comparison test did not isolate differences in fire severity for N , P, K, Mg, and S (Appendix 3-11). Tukey's comparison test was unable to detect differences between fire severity levels, even though 105 Table 3-11. Estimated total nutrient losses (kg/ha) during the burns in the experimental plots. T r e a t m e n t / P l o t N P K Na Mg Ca S Low s e v e r i t y burns i n f r e s h s l a s h a) b r o a d c a s t burns P l o t 2 679 . 4 46. 0 65 . 5 5 . 4 61 . 0 180. 1 66 .6 P l o t 17 591 . 0 48 . 3 75 . 5 5 . 5 57. 1 167. 5 48 . 5 AVERAGE 635 .2 47. 2 70. 5 5 . 5 59. 1 173. 8 57 .6 b) windrow burns P l o t 7 1081 .9 87. 0 131 . 1 12. 5 114. 7 369. 0 101 . 0 P l o t 10 740 .3 63 . 5 102. 3 9. 5 92 . 5 300 . 5 74 . 0 AVERAGE 911 . 1 75 . 3 116. 7 1 1 . 0 103. 6 334 . 8 87 . 5 Low s e v e r i t y burns i n cured s l a s h a) b r o a d c a s t burns P l o t 1 646 .4 32 . 4 34 . 1 4. 4 40 . 5 186. 8 44 . 2 P l o t 4 594 .5 35 . 0 40. 9 5 . 4 55 . 3 223. 9 43 .7 AVERAGE 620 .5 33 . 7 37. 5 4. 9 47. 9 205 . 4 44 . 0 b) windrow burns P l o t 3 934 . 5 77. 3 121 . 9 1 1 . 4 103. 9 335 . 3 88 .8 P l o t 5 764 .5 60 . 7 93 . 9 9 . 5 91 . 8 314 . 3 72 .6 AVERAGE 849 .5 69 . 0 107. 9 1 0 . 5 97. 9 324 . 8 ...8 0 .7 Moderate s e v e r i t y burns a) b r o a d c a s t burns P l o t 8 949 . 7 65 . 0 59. 1 0. 0 60 . 5 191 . 2 92 . 6 P l o t 11 748 . 6 61 . 4 78. 1 4 . 5 81 . 8 246 . 3 79 .2 AVERAGE 849 . 2 63 . 2 68 . 6 2. 3 71 . 2 218. 8 85 .9 b) windrow burns " p l o t 1 2 85 8 . 5 80 . 0 123. 2 1 1 . 1 110. 2 352 . 2 86 .9 P l o t 16 852 .8 68. 7 126. 3 10. 6 105 . 0 328. 8 83 .8 AVERAGE 855 .7 74 . 4 124. 8 10. 9 107. 6 340 . 5 85 .4 High s e v e r i t y burns a) b r o a d c a s t burns P l o t 9 753 . 0 52. 5 63. 4 9. 6 76. 2 181 . 3 75 . 8 P l o t 13 753 . 1 55 . 1 58. 1 2 . 7 71 . 8 160 . 5 . 71 .4 P l o t 14 723 .9 49. 7 53 . 8 2. 9 73 . 0 190. 8 70 . 5 AVERAGE 743 . 3 52 . 4 58. 4 5 . 1 73. 7 177. 5 72 .6 b) windrow burns P l o t 15 1286 . 2 109. 3 158. 5 14 . 6 140 . 9 448. 4 1 19 . 5 P l o t 18 1124 . 4 103. 0 156. 7 12. 8 121 . 9 342 . 9 109 .0 AVERAGE 1205 .3 106. 2 157. 6 13. 7 131 . 4 470 . 6 114 .3 106 Table 3-12. Estimated percentage nutrient losses from organic matter during the burns in the experimental plots. T r e a t m e n t / P l o t N P K Na Mg Ca S Low s e v e r i t y burns in f r e s h s l a s h a) b r o a d c a s t burns P l o t 2 Broadcast 70 56 56 49 58 56 73 P l o t 17 Broadcast 76 69 69 61 65 62 65 AVERAGE 73 63 63 55 62 59 69 b)windrow burns P l o t 7 Windrow 90 86 92 93 93 91 91 P l o t 10 Windrow 96 95 97 97 97 96 95 AVERAGE 93 91 9 5 95 95 94 93 Low s e v e r i t y burns i n cured s l a s h a ) b r o a d c a s t burns P l o t 1 Broadcast 76 51 36 48 48 62 58 P l o t 4 Broadcast 80 61 46 61 61 69 60 AVERAGE 78 56 41 55 55 66 59 b> wi ndrow burns P l o t 3 Windrow 94 93 97 97 98 96 94 P l o t 5 Windrow 87 86 91 93 93 92 87 AVERAGE 91 90 94 95 96 94 91 Moderate s e v e r i t y burns a ) b r o a d c a s t burns P l o t 8 Broadcast 70 57 39 0 46 44 75 P l o t 11 Broadcast 79 73 59 37 68 63 82 AVERAGE 75 65 49 19 57 54 79 b)windrow burns P l o t 12 Windrow 97 96 99 99 98 97 96 P l o t 16 Wi ndrow 96 95 99 98 98 97 95 AVERAGE 97 96 99 99 98 97 96 High s e v e r i t y burns a ) b r o a d c a s t burns P l o t 9 Broadcast 75 59 47 49 64 47 76 P l o t 13 Broadcast 78 67 46 2 4 64 43 76 P l o t 14 Broadcast 77 63 46 25 65 50 77 AVERAGE 77 63 46 33 64 47 76 b ) w i ndrow burns P l o t 15 Windrow 94 92 96 95 96 94 93 P l o t 18 Windrow 93 93 96 94 96 92 93 AVERAGE 94 93 96 95 96 93 93 Percentage losses were calculated based on preburn nutrient quantities aboveground organic matter and tree roots. 107 A N O V A indicated significant differences existed. Differences in statistical results between Tukey's comparison test and A N O V A were caused by the conservative nature of the comparison test when compared to the more robust A N O V A analysis. Broadcast burn total N and S losses were significantly (p < 0.01) correlated with forest floor consumption, while Mg, P, and S were significantly (p<0.05) correlated with medium (1-7 cm) slash consumption (Table 3-13). Relative broadcast burn total S losses were significantly (p<0.01) correlated with medium (1-7 cm) slash consumption (Table 3-13). Total relative losses of S from windrow burns were significantly (p<0.05) correlated with medium (1-7 cm) slash consumption (Table 3-14). For broadcast and windrow burns combined losses of all nutrients were significantly (p<0.05) correlated with medium (1-7 cm) slash consumption (Table 3-15). Calcium was also significantly (p<0.05) correlated with large (> 7 cm) and total slash consumption (Table 3-15). Total relative nutrient losses from both broadcast and windrow burns combined were significantly (p<0.05) correlated with medium (1-7 cm), large (> 7 cm) andnotal slash consumption (Table 3-15). With the exception of K, total nutrient losses from broadcast burns fall within published slashburning results (Feller et al. 1983, Feller 1988, Feller and Taylor 1987, Debano and Conrad 1978). Total losses of K from broadcast burns were generally greater than any losses reported for operational slashburning in the literature. Broadcast burn K losses from Feller (1983, 1988) and Taylor and Feller (1987) range from 0-56 kg/ha. Only K wildfire losses of 308 kg/ha, reported in Grier (1975), are greater than K losses found in this study. The results are more closely related to whole tree harvesting K loss estimates for lodgepole pine (Kimmins 1974). Total nutrient losses from windrows were much greater than those found 108 Table 3-13. Correlation coefficients for total and relative nutrient losses and fuel consumption variables for broadcast burn plots. N u t r i e n t s N P K Na Ca S 1) TOTAL NUTRIENT LOSSES Fo r e s t f l o o r consumption 0.89** 0.58 -0 .09 -0. 71* 0. 19 -0. 07 0 . 76** Depth-of-burn 0.30 0.49 0 .39 -0 . 42 0 . 47 -0 . 34 0 .44 Fine s l a s h < 1 cm consumption -0.50 -0.50 -0 .38 0. 50 -0. 05 0. 53 -0 .52 Medium s l a s h 1-7 cm consumption 0.50 0.74* 0 .57 0 . 08 0 . 87** 0. 31 0 .69* Large s l a s h > 7 cm consumption 0.26 0.14 -0 .22 0 . 02 0 . 53 0 . 61 0 .32 T o t a l s l a s h consumption 0.32 0.26 - 0 .08 0 . 05 0. 65 0. 61 0 .4 1 2) RELATIVE TOTAL NUTRIENT LOSSES Fo r e s t f l o o r consumption -0.50 -0.26 -0 .57 -0. 93 - 0 . 47 -0. 47 0 .46 Depth-of-burn -0.13 0.35 0 .19 -0. 53 0 . 31 0 . 31 0 . 60 Fine s l a s h < 1 cm consumption 0.81** 0.13 -0 . 1 1 0. 55 0. 29 0. 29 -0 .36 Medium s l a s h 1-7 cm consumption 0.23 0.59 0 .12 -0. 37 0 . 49 0. 49 0 .84** Large s l a s h > 7 cm consumption 0.45 0.11 -0 .43 -0 . 26 0 . 27 0. 27 0 .41 T o t a l s l a s h consumption 0.46 0.22 -0 .36 -0. 30 0. 34 0. 34 0 .52 * indicates correlation coefficients are significant (p<0.05) ** indicates correlation coefficients are significant (p<0.01) Correlation coefficients are for n=9 Table 3-14. Correlation coefficients for total and relative nutrient losses and fuel consumption variables for windrow plots. N u t r i e n t s N P K Na Mg Ca S 1) TOTAL NUTRIENT LOSSES Fine s l a s h < 1 cm consumption 0.11 0.16 Medium s l a s h 1-7 cm consumption 0.50 0.58 Large s l a s h > 7 cm consumption -0.27 -0.36 T o t a l s l a s h consumption -0.14 -0.21 2) RELATIVE TOTAL NUTRIENT LOSSES Fine s l a s h < 1 cm consumption 0.81* 0.12 Medium s l a s h 1-7 cm consumption 0.23 0.57 Large s l a s h > 7 cm consumption 0.45 -0.12 T o t a l s l a s h consumption 0.46 0.04 0.16 0.19 0.16 0.19 0.13 0.67 0.56 0.54 0.40 0.56 -0.47 -0.22 -0.15 0.20 -0.32 -0.30 -0.07 0.00 0.34 -0.18 0.28 0.35 0.35 0.35 0.17 0.59 0.43 0.62 0.62 0.74* -0.07 0.18 -0.11 -0.11 0.11 0.11 0.33 0.07 0.07 0.10 * indicates correlation coefficients are significant (p<0.05) ** indicates correlation coefficients are significant (p<0.01) Correlation coefficients are for n = 8 110 Table 3-15. Correlation coefficients for total and relative nutrient losses and fuel consumption variables for broadcast and windrow plots combined. N u t r i e n t s N P K Na Mg Ca S 1) TOTAL NUTRIENT LOSSES Fine s l a s h < 1 cm consumption -0.22 -0.21 -0. 1 7 0. 1 0 -0. 09 0. 01 -0 .30 Medium s l a s h 1-7 cm consumption 0.67** 0.77** 0. 75** 0. 60* 0. 79** 0. 64* 0 .77** Large s l a s h > 7 cm consumption 0.23 0.23 0. 22 0. 32 0 . 44 0 . 51* 0 . 29 T o t a l s l a s h consumption 0.37 0.40 0. 38 0. 44 0 . 59* 0 . 61** 0 .45 2) RELATIVE TOTAL NUTRIENT LOSSES Fine s l a s h < 1 cm consumption Medium s l a s h 1-7 cm consumption 0.84** 0.79** 0. 72** 0. 68** 0. 80** 0. 80** 0 .81** Large s l a s h > 7 cm consumption 0.81** 0.79** 0 . 78** 0 . 76** 0 . 83** 0 . 83** 0 . 87** T o t a l s l a s h consumption 0.87** 0.87** 0 . 86** 0 . 82** 0 . 90** 0 . 90** 0 .92** * indicates correlation coefficients are significant (p<0.05) ** indicates correlation coefficients are significant (p<0.01) Correlation coefficients are for n=17 Ill for operational slashburns and were more similar to losses reported in whole tree harvesting studies (Kimmins 1974, Weetman and Webber 1972). The large accumulations of fuel and higher fuel consumption are the only explanation for higher than previously reported loss estimates. From the proceeding discussion the following conclusions can be made: 1. For the windrow burns, generally > 90% of all nutrients present in the organic matter above the mineral soil surface were released from slash and forest floor during the burning. 2. Nutrient quantities lost from the windrow burns were generally greater than those lost from operational slashburns and were more similar to reported losses from whole tree harvesting operations. 3. Significantly greater nutrient losses were generally found for windrow than for broadcast burns. 4. Fire severity significantly influenced the quantities of nutrients lost. 5. Total nutrient losses decreased in the order N > Ca > K, Mg, S > P > Na, while relative losses for broadcast burns decreased in the order N > S > P > Mg > Ca > K > Na. Relative losses for windrow burns followed no consistent order. 6. The quantities of nutrients lost from slash were generally greater than those lost from the forest floor, with the exception of nitrogen which was found to have greater losses from forest floor. 7. For the broadcast burns, relative losses from the slash were also generally greater than those from the forest floor. For windrow burns, however, relative losses from slash were similar to those found for the forest floor. This can be attributed to the very high consumption of both slash and forest floor in the windrow plots. 112 Nutrient changes in the mineral soil one year following burning Mineral soil bulk density was unchanged by the knockdown and broadcast burn treatments, measuring 0.7 g/cm 3 pre and post treatment. However, soil bulk density increased both between and within windrows (Table 3-16). Mineral soil pH averaged between 4.0 to 4.2 in the untreated lodgepole pine forest (Appendix 3-8). The year after burning mineral soil pH values in broadcast burn plots and interwindrow areas were on average 0.2 units higher than pretreatment values (Appendix 3-8). Increases, of 0.8 pH units, were observed in the high severity windrow burns, beneath windrows. Other studies both in nearby areas in the SBS zone (Macadam 1987, Taylor 1987) and areas further afield (Austin and Baisinger 1955, Adams and Boyle 1980, Tarrant 1954 and Wells et al 1979) have found first year post-treatment increases in mineral soil pH to be relatively sihall ( < 0.5 pH units ) after broadcast slashburning. The intra-windrow mineral soil pH one year after burning increased approximately 1.5 units from the pretreatment values (Appendix 3-8). Benson (1982), comparing the effects of windrowing vs broadcast burning, found one year after treatment that mineral soil pH in the 0-5 cm layer had increased to 6.5 from a pretreatment value of 4.8 while in the 5-15 cm layer the increase was from 5.0 (pretreatment) to 5.3 (post-treatment). He concluded that greater pH increases in areas beneath windrows were due to greater leaching of soluble ash material from the surface layer by precipitation. Decreases in broadcast burn mineral soil P, K, S, total N and mineralizable N were found for low severity burns in fresh slash and for low severity burns in cured slash (Table 3-17). Total N and S in moderate and high severity broadcast burns were found to increase while P and K were found to decrease. Windrow soil changes were generally lower in Table 3-16. Pre and post-treatment surface 0-15 cm mineral soil bulk density (g/cm3) averaged for the experimental plots. Treatment Mean Standard Sample E r r o r S i z e ( n ) 1 ) P r e - t r e a t m e n t 0.7 0.1 9 2 ) P o s t - t r e a t m e n t a) Broadcast burn areas 0.7 0.1 9 b) Beneath windrow areas 0.9 0.1 9 c) Between windrow areas 0.9 0.1 9 114 Table 3-17. Differences between the 1-year post burn and preburn quantity of nutrients in the surface 0-15 cm of mineral soil (kg/ha) in the experimental plots. T r e a t m e n t / P l o t N N P K Mg Ca S T o t a l M i n e r a l i z a b l e Low s e v e r i t y burns i n f r e s h s l a s h a) b r o a d c a s t burns P l o t 2 -911 -2 - 14 -77 -22 -36 -73 P l o t 17 -21 - 2 -28 -20 29 94 -73 AVERAGE -466 -2 -21 -49 4 58 -73 b) windrow burns P l o t 7 52 -2 - 13 1 5 88 423 -37 P l o t 10 -62 - 1 -3 -0 87 485 56 AVERAGE -5 -2 -8 8 88 454 9 Low s e v e r i t y burns i n cured s l a s h a) b r o a d c a s t burns P l o t 1 -590 -2 -31 -99 23 1 1 0 P l o t 4 -342 - 1 -22 -87 33 72 - 73 AVERAGE -466 -2 -27 -93 28 41 -36 b) windrow burns P l o t 3 - 182 - 1 1 - 0 103 520 - 50 P l o t 5 260 - 1 8 8 102 536 23 AVERAGE 39 - 1 5 4 1 02 528 - 13 Moderate s e v e r i t y burns a) b r o a d c a s t burns P l o t 8 217 0 - 14 -35 53 267 1 0 P l o t 11 186 0 - 2 -26 12 92 31 AVERAGE 202 0 -8 -31 33 1 79 21 .b) windrow burns P l o t 12 58 0 -1 55 92 706 99 P l o t 16 113 0 -27 38 138 935 79 AVERAGE 85 0 - 14 47 1 1 5 820 88 High s e v e r i t y burns a) b r o a d c a s t burns P l o t 9 404 1 -22 -5 48 131 1 0 P l o t 13 114 0 -22 -2 72 196 31 P l o t 14 207 1 -37 -6 65 366 10 AVERAGE 242 1 -27 -7 62 231 17 b) windrow burns P l o t 15 -31 0 1 1 1 08 319 1450 22 P l o t 18 439 -2 4 90 232 989 1 14 AVERAGE 204 - 1 7 99 275 1220 68 Negative values represent post treatment nutrient losses by the mineral soil. 115 magnitude than those found for broadcast burning (Table 3-17). Windrow fire effects on soils appear to have been minimized by two factors. Firstly, windrowing took place when the soil was frozen reducing the amount of soil scraped from the surface and deposited in windrow areas. Secondly, the area which windrows occupied was small, on average only 20% of the total area treated, minimizing the overall effect of the very hot fires created in the burning piles. The quantity of mineral soil Mg and Ca generally increased after burning for both site preparation treatments with greater increases in the windrow burning plots (Table 3-17). Mineral soil Ca and Mg increased with increasing fire severity for both broadcast and windrow burning treatments (Table 3-17). A N O V A indicated that fire severity significantly (p < .05) influenced changes in total N and mineralizable N (Appendix 3-10). Tukey's (HSD) multiple comparison test could not detect differences in the levels of fire severity. Significant treatment interactions (p<0.05) were found for changes in P, K, and Mg (Figures 3-7 to 3-9) (Appendix 3-10). The mineral soil -K treatment interactions were caused by differences between broadcast and windrow low severity burns in both fresh and cured slash. Calcium changes were significantly (p<0.05) affected by site preparation and fire severity (Appendix 3-10). Tukey's multiple comparison test could not detect differences in the levels of fire severity. Sulphur changes in mineral soil were significantly (p<0.05) affected by site preparation and fire severity (Appendix 3-10). Tukey's (HSD) multiple comparison test differentiated changes from the low severity cured slash from those from the moderate severity (Appendix 3-11). Macadam (1987) found soil (forest floor and mineral soil combined) N losses to a depth of 30 cm averaged 376 kg/ha, while available P increases to a depth of 30 cm averaged 110 kg/ha. Taylor and Feller (1987) reported moderate increases in mineral soil N and P. 116 Adams and Boyle (1980), and Benson (1982) comparing windrowing and burning to other treatments (including whole tree harvesting and broadcast burning) found greater concentrations of soil N and P in windrows after burning. Macadam (1987) found slight increases in soil (forest floor and mineral soil combined) K and extremely variable changes in soil Ca after burning. Taylor and Feller (1987) found both increases and decreases in the quantity of mineral soil K following broadcast burning. Benson (1982) found mineral soil Ca and Mg concentrations beneath windrows were double those of undisturbed forest while Adams and Boyle (1980) found mineral soil Ca concentrations beneath burned windrows were almost double pretreatment levels. Taylor and Feller (1987), the only other study which quantified the loss of sulphur from soil, found both increases and decreases following burning. The effects of the treatments on mineral soil nutrients can be summarized as follows: h For N , P, S, and K some increases and some decreases in quantities were observed in the surface mineral soil in both windrow burning and broadcast burning treatments. 2. The treatments almost invariably resulted in increases in Ca and Mg quantities in the surface mineral soil. However, the greatest change in soil nutrients were generally observed for Ca, then N . 3. Fire severity significantly influenced the post-burn quantities of total N and mineralizable N in the surface mineral soil. 4. Post-burn quantities of S in the surface mineral soil were significantly influenced by both site preparation and fire severity (p < 0.05). 117 Significance of fire-induced changes in ecosystem nutrients Pretreatment assessment of nutrients showed that mineral soil N was below satisfactory levels (Shumway and Atkinson 1978, and Powers 1980). Both of these studies quantified levels of mineralizable N and indicated fertilizer response potential. Shumway and Atkinson (1978), looking at mineralizable N in Douglas-fir stands in western Washington and Oregon, found that stands responded significantly when mineralizable N fell below levels of 46 ppm. Powers (1980), studying Pinus ponderosa in northern California, found that soils testing less than 12 ppm of mineralizable N were judged clearly deficient, but stands of pine and fir on soils testing as high as 16 ppm of N may still respond to fertilization. Since, the pretreatment levels of mineralizable N in these stands were well below 12 ppm (approximately 3 ppm) it is probable that these stands will require fertilization or some other treatment to ameliorate the impacts of treatments. The burning treatments resulted in substantial losses of most nutrients from the surface organic matter. However, losses were minimized in the low severity treatments. Losses were particularly high for some of the windrow burning treatments. For long term nutrient conservation it would appear that knocking down followed by broadcast slash burning would be the most desirable treatment to convert the dense lodgepole pine forests in the study area into less dense lodgepole pine plantations. 118 CHAPTER 4 EFFECTS OF TREATMENTS ON PLANTED LODGEPOLE PINE SEEDLINGS AND ASSOCIATED VEGETATION 119 INTRODUCTION Growth and nutrition of planted seedlings may be dramatically affected by site preparation and burning treatments. The major problem in quantifying seedling response to treatment is that response is very site specific and often only one type of treatment is carried out on any one site making comparison of different treatments difficult. This factor limits the forester's ability to make widespread prescriptions that relate treatment to seedling growth and nutrition. The most effective type of treatment is one which results in good initial growth and survival of seedlings, conserves or enhances long term site productivity site, and. is economical to implement. The application of a successful rehabilitation strategy to large forested areas involves a sound understanding of treatment effects on future plantations. This not only includes early establishment but also long-term effects created by the rehabilitation treatment. Long term effects may include such things as fire induced nutrient deficiencies, development of associated vegetation, and other fire effects which have altered physical properties of soil and organic matter. L I T E R A T U R E REVIEW-EFFECTS OF TREATMENTS ON L O D G E P O L E PINE R E G E N E R A T I O N 120 The effects of slashburning on plant regeneration are influenced by climate and soil properties such as fertility, moisture and drainage. These properties often make comparison of different burning treatments difficult. Slashburning literature has generally not recognized the site-specific response of trees, accounting for much of the debate concerning tree seedling regeneration and growth following burning (Feller 1982). The debate is further clouded by the lack of documentation on the nature and severity of the fires studied. Studies reviewed by Feller (1982) reported that slashburning had both favourable effects as well as detrimental effects on the growth of lodgepole pine. Detrimental effects reported included damage to the physical and chemical properties of the soil and the destruction of advanced regeneration. Many individual factors or combinations of factors contribute to differences in seedling response. For example, low soil temperatures will inhibit plant water uptake, retard nutrient release and adsorption, and slow terminal leader growth. In addition, differences in net radiation, available nutrients, and the effects of vegetation competition all influence seedling performance. Schmidt and Alexander (1985) found that lodgepole pine seedlings grew more rapidly than most of their associates in both diameter and height and, given adequate space, lodgepole pine height growth equalled or exceeded that of most of its associates for 50 years or longer. This better growth performance was due in part to the adaptation of lodgepole pine to early successional conditions, which burning creates. 121 Only two published studies were found that studied survival and growth of planted lodgepole pine seedlings following burning. Endean and Johnstone (1974) found for bareroot seedlings, 52% survival after 2 years for a moderate severity burn and 67% for a high severity burn, while container stock seedling survival was 63% for the moderate and 76% for the high severity burn. Benson (1982) found lodgepole pine seedling survival was 95% at 3 years, 87% at 5 years and 80% at 10 years on areas that had been both piled and burned and broadcast burned. He found pocket gophers and other small mammals were responsible for at least one third of the seedling mortality on all treatments during the five to nine year period. Endean and Johnstone (1974) concluded that better survival and growth on burned areas was due to slash removal and better seedling placement, as well as temporary site improvement. The response of associated vegetation to burning is important in determining the growth of seedlings following burning. However, although the effects of burning on vegetation cover and biomass in lodgepole pine ecosystems have been documented, there have apparently been no studies which have evaluated the effects of associated vegetation on the survival and growth of planted seedlings. Lyon (1976) found an increase in vegetation cover of 53% over a ten year period following the Sleeping Child wildfire in Montana. The patterns of response were influenced mainly by the amount of precipitation that occurred in each growing season. Packer and Williams (1982) found vegetation cover in lodgepole pine ecosystems exceeded 80% during the 3rd and 5th year following broadcast burning. Piled and burned areas had covers of 40 to 48% while herbaceous biomass production in broadcast burn areas was double that of 122 the piled and burned areas. Packer and Williams (1982) concluded that the quantities of slash in the broadcast burn sites following logging were not sufficiently concentrated to support the hot fires that significantly reduced vegetation. There is, thus, a lack of information on the effects of different burning, treatments on vegetation in lodgepole pine plantations and certainly for the SBS zone in B.C.. This chapter reports on the effects of the dense lodgepole pine stand treatments on survival andjrjowth of planted lodgepole pine seedlings and resulting associated vegetation response for the first two years following treatment. METHODS Study Area Fieldwork for the study was conducted in an area located between Francois and Ootsa lakes, southwest of the town of Burns Lake in west central B.C. (Figure 1-1 in Chapter 1). Two stands within the area were selected for study and divided into three experimental blocks. These stands occur primarily within one ecosystem type - the Mesic bunchberry-moss ecosystem association (ecosystem unit SBSel/01) of the Subalpine Fir Subzone of the Sub-Boreal Spruce biogeoclimatic zone (Pojar et al. 1984). The study area has a cold sub-boreal continental humid climate which is characterized by severe, snowy winters and relatively warm, moist and short summers. Soils in the area were predominantly Brunisolic Gray Luvisols (Agriculture Canada Expert Committee on Soil Survey 1987) with Hemimor forest floors (Klinka et al. 1981). For a more detailed study area description refer to chapter 1. 123 1. Seedling establishment and assessment In the spring following broadcast and windrow burns in cured slash (late May, 1987) 1-0 PSB 211 lodgepole pine seedlings grown at the B.C. Ministry of Forests Surrey nursery from seedlot 13518 and lifted in January, 1987 were planted in all plots. Seedlings in all plots were planted at a spacing of 3x3 m (1200/ha). A l l sample plot trees were planted by the same two planters in approximately a one week period. With the exception of plots 1-6 all remaining fill in areas outside assessment plots were planted within a period of two weeks with 1-0 PSB 211 plug stock . Fill in trees in plots 1, 2 and 4 were 2-1 bareroot lodgepole pine seedlings, while fill in trees in plots 3, 5 and 6 were 2-0 bareroot lodgepole pine seedlings. Within each broadcast burn plot one 30 x 30 m square assessment plot containing 49 planted seedlings was established (Appendix 4-7). The seedling assessment plots within each windrow burn experimental area consisted of one plot spread over 3 windrows and another plot spread over the 3 adjacent interwindrow areas (Appendix 4-7). The combined number of trees assessed in both windrow and broadcast plots totalled 1413 trees. A l l assessment plots were buffered with two adjacent rows spaced at 3x3 m. Seedling height was measured immediately following planting and at the end of both the 1987 and 1988 growing seasons. In 1988 basal diameter was also measured. 2. Understory vegetation biomass assessment Postburn understory vegetation biomass was measured at the height of both the 1987 and 1988 growing seasons. In August of each year vegetation was collected from ten 1 m plots within each broadcast, windrow and between windrow assessment plots. Vegetation was separated into dominant species and into groups of the less significant species - fifteen 124 categories were recognized as follows: Rosa acicularis, Spirea betulifolia, Salix bebbiana, other shrubs, Aster foliaceus, Arnica cordifolia, Epilobium spp., Equisetum spp., Linnaea borealis, Lupinus sericea, Petasites palmatus, Cornus canadensis, grasses, other herbs, and mosses and lichens. Although each of these categories contributed greater than 1% of the total cover in the study plots, only seven categories were present in sufficient quantity to permit meaningful statistical analysis. Dominant species were determined on the basis of percent cover. Those species of shrubs and herbs which occupied greater than 1% of the total cover were considered dominant and collected separately. A l l mosses were bulked together as were all grasses to reduce analytical costs. A l l biomass samples were weighed after oven drying at 70°C and the mean mass per square meter of each category was calculated for each plot. 3. Statistical analysis Seedling and vegetation data were analysed with the objective of determining which measured seedling and vegetation parameters were influenced by site preparation treatment and fire severity. This was achieved by subjecting seedling and vegetation measurements to a two way analysis of variance, testing the following null hypotheses: H Q I : Fire severity had no effect on the variable of interest. HQ2: Site preparation treatment had no effect on the variable of interest. FLj3: There were no fire severity x site preparation treatment interactions with respect to the variable of interest. Significant group means were distinguished using Tukey's (HSD) multiple comparison test. 125 For the two way analysis of variance the assumption of normality could not be tested because of the limited number of data points. To test the assumption of homogeneity, residuals were plotted against estimated values to determine if the data exhibited heteroscedasticity. RESULTS AND DISCUSSION 1. Tree Seedling Response Survival of planted lodgepole pine seedlings varied between the different site preparation treatments. After the first growing season survival averaged 83% within windrow areas, 89% between windrows and 86% in broadcast burn areas. After the second growing season survival averaged 68 % within windrow areas, 83% between windrows and 72% in broadcast burn areas. The best overall survival was measured in areas between windrows (Table 4-1 and 4-2). The most probable explanation for this is that complete removal of the forest floor from these areas increased soil temperature, creating a more favourable environment for seedling establishment. Soil temperature data from a study by Macadam (1988) suggest that low temperatures may contribute to slow growth and survival of planted interior spruce seedlings. Macadam found that seedling root zone temperatures did not reach daily averages above 10°C in untreated soils until late June. Dobbs and McMinn (1977) inferred that the beneficial effects of organic matter removal (scalping) on growth of planted white spruce were attributable to reduced competition and an improved soil temperature regime. Their results suggest that improvement of the soil temperature regime may be due partly 126 Table 4-1. The average height, height increment, basal diameter and survival for planted lodgepole pine seedlings in the experimental plots during the first two growing seasons. Treatment T o t a l Annual Basal S u r v i v a l Height Increment Diameter (cm) (cm) (mm) (%) Growing season 1987 1988 1987 1988 1987 1988 1987 1988 1) Low s e v e r i t y burns i n f r e s h s l a s h B roadcast burn areas 16.1 23.3 2.3 7.1 - 6.0 85 84 A r e a s b e t w e e n w i n d r o w s 16.9 24.8 4.8 7.9 - 6.6 96 92 Areas beneath windrows 15.8 24.9 1.8 8.9 - 6.7 85 80 2) Low s e v e r i t y burns i n cured s l a s h B roadcast burn areas 15.5 23.2 3.1 7.6 - 5.9 92 63 Areas between windrows 15.8 24.2 2.8 8.3 - 6.9 93 86 Areas beneath windrows 14.6 24.3 0.2 9.7 - 5.9 90 64 3) Moderate s e v e r i t y burns Broadcast burn areas 15.7 23.7 2.4 7.0 - 6.2 81 75 Areas between windrows 16.3 28.3 2.0 11.7 - 8.5 84 73 Areas beneath u i n d r o u s 15.7 25.5 1.5 9.7 - 7.0 82 68 4) High s e v e r i t y burns Broadcast burn areas 15.2 25.2 2.5 9.1 - 9.1 87 75 Areas between windrows 16.7 27.6 3.2 11.3 - 7.6 90 84 Areas beneath windrows 14.6 24.0 0.4 9.2 - 6.4 76 59 127 Table 4-2. The average height, height increment, basal diameter and survival at the end of the second growing season of lodgepole pine seedlings planted in the experimental plots, averaged by site preparation treatment and fire severity. T o t a l I n c r e m e n t B a s a l S u r v i v a l H e i g h t D i a m e t e r ( c m ) ( c m ) (mm) ( X ) S i t e p r e p a r a t i o n treatments 1) Broadcast burn areas 2 3 . 9 c 7 . 8 b 6 . 1 b 72b 2) Areas between windrows 26.3 a 9.8 a 7.2 a 83a 3) Areas beneath windrows 24.7 b 9.4 a 6.8 a 68c F i r e s e v e r i t y 1) Low s e v e r i t y burns i n f r e s h s l a s h 24.4a 8.0a 6.5a 83a 2) Low s e v e r i t y burns i n cured s l a s h 23.9a 8.5a 6.3a 71b 3) Moderate s e v e r i t y burns 25.9a 9.5a 7.2a 72b 4) High s e v e r i t y burns 25.7a 9.9a 6.8a 72b Averages for site preparation treatments are for n=8 samples except for broadcast areas where n=9 samples. For each variable, means followed by the same letter are not significantly different at p < .05 for survival and p < .10 for height, increment and basal diameter. Averages for fire severity type are for n=6 samples except for high severity burns where n=7 samples. For each variable, means followed by the same letter are not significantly different at p < .05. 128 to higher thermal diffusivity associated with mineral (vs. organic) material. Poorer survival of seedlings in broadcast burn areas, when compared to between windrow areas, was likely the result of lower soil temperatures caused by residual forest floor. Low soil temperatures can inhibit plant-water uptake (Kramer, 1942; Babalola et al., 1968) and retard top growth of plants, perhaps by inhibiting hormone transfers from root to top (Lavender and Overton 1972). It would appear that removal of organic matter in these ecosystems has the capacity to create more favourable soil temperatures which will enhance seedling growth and survival. The lowest survival related to site preparation occurred in windrow areas where survival was only 68% in the 2nd growing season (Table 4-2). Two factors might account for this result. Firstly, a deep layer of ash was present in all windrow areas and seedlings inay not have been planted entirely in mineral soil. Secondly, the severe nature of the fires in windrow areas may have caused development of a hydrophobic layer in windrow soil. The planting of seedlings in the ash layer combined with creation of a hydrophobic layer may have limited moisture availability in these areas, thereby reducing survival. The highest mortality related to fire severity occurred in the plots which were burned just prior to planting - those given low severity burns in cured slash. Poor survival in these plots was likely caused by "hot planting" which was carried out within only a few days following the burns, after mop up was completed. For these burns, both windrow and broadcast areas had low survival when compared to other fire severity type combinations, on average 64% and 63% respectively (Table 4-1). Mortality in areas between windrows was highest in moderate severity burn plots, where survival on average was 73% (Table 4-1). The lowest mortality related to fire severity occurred in the plots which were given low 129 severity burns in fresh slash (Table 4-1). Nutrient losses were lowest in most cases for low severity burns in fresh slash and this may explain why survival might be highest for these plots. However, soil mineralizable N was found to decrease after these burns. As it is a measure of N availability, this result suggests that nutrient losses may not be significant in determining survival. Seedling survival was significantly influenced by both site preparation and fire severity (Appendix 4-1). Tukey's (HSD) multiple comparison test demonstrated that between windrow area survival was significantly (p<0.05) greater than broadcast burn area survival (Table 4-2). In addition, broadcast burn survival was significantly greater than survival in windrow areas. Survival in low severity burns in fresh slash was significantly (p<0.05) greater than that for the three other fire severities studied (Table 4-2). The results of this study are comparable to those of others. Lotan and Perry (1976), studying lodgepole pine regeneration following clearcutting of overmature lodgepole pine, found that the most vigorous seedlings grew in areas between windrows where scraping had removed all forest floor and associated vegetation. They found that the poorest performance of planted seedlings was on those areas where chipped residue was spread. They attributed this poor performance to insulating effects of the chip layer which acted in a similar way to forest floor. Average seedling heights measured immediately following planting were analyzed to determine if significant differences existed in the planted seedling population. Results of a two way A N O V A indicated that there was no significant (p < 0.05) height difference between seedlings planted in different site preparation and fire severity treatment combinations. Consequently, any differences in seedling heights between the treatment plots some time 130 after treatment can be attributed to the effects of the treatments. Average total height, height increment, and basal diameter were significantly less on the broadcast burn plots than on the windrow plots after two growing seasons (Table 4-2). Poorer seedling growth response in broadcast areas, like survival, were attributed to lower soil temperatures caused by residual forest floor. Seedlings in areas between windrows had greater heights but similar height increment and basal diameter to seedlings in areas beneath windrows (Table 4-2). Fire severity had no significant effect on either total height, height increment, or basal diameter after two growing seasons, although there was a tendency for these to increase with fire severity. It can be concluded that after 2 growing seasons, lodgepole pine seedling performance was best tin the areas between windrows. The influence of fire severity on seedling performance has been less clear. Although seedling growth has been better on the higher severity burns, survival has been better on the lower severity burns. The results of the present study appear to be inconsistent with those of Ballard (1985) who found that, six years following burning, white spruce height growth in areas beneath windrows was significantly greater than that between windrows. Ballard (1985) attributed this to the accumulation of N and S in windrows followed by their release in available form in the ash which he considered could more or less compensate for volatilization losses. He indicated that growth data were consistent with the hypothesis that severe nutrient deficiencies are associated with areas between windrows (scalped sites). Data from the present study are not consistent with this hypothesis, in that nutrient levels in mineral soils between windrows were not severely impacted by treatments (Chapter 3). The nutrient changes estimated in the surface 0-15 cm mineral soil in areas between windrows were 131 likely of lower severity than those found by Ballard as soils in this study were treated when the ground was frozen. Minore (1986), smdying the effects of broadcast burning and windrow burning on Douglas-fir in southwestern Oregon, found seedling height growth in windrow plantations was less than that in broadcast burned plantations. He concluded that windrow burning may be more detrimental to seedling height growth than broadcast burning. Based on results of this study and Ballard's and Minore's results, early initial growth of seedlings may not reflect their longer term growth response to treatment as future nutrient deficiencies in between windrow areas could decrease long term seedling growth in such areas. However, Schmidt and Lotan (1979) found lodgepole pine seedlings had the best height growth on windrow and burned areas when compared to residue removed and chip-spread treatments. Apparent height differences at age 3 were even more pronounced at age 5. This suggests that initial growth results may not change dramatically over a period of 5 years. 2. Understory vegetation growth Of all the understory species, Epilobiwn had the greatest biomass followed by Cornus, Spirea, grasses, then Rosa and Linnaea, in that order. Epilobium biomass was significantly (p < 0.05) affected by site preparation treatment, being significantly greater in windrow areas and significantly less in areas between windrows (Table 4-3). The effect of fire severity on Epilobium biomass is less clear in that although there was a tendency for biomass to increase with increasing severity these differences were not statistically significant except for the low severity windrow and broadcast burns in cured slash which exhibited biomass values less than those of the other treatments (Table 4-3). However, these burns were 132 Table 4-3. Summary of the biomass of the most important understory species in the experimental plots during the second growing season, averaged by site preparation treatment and fire severity. S i t e P r e p a r a t i o n Shrubs Herbs Treatment/Burn Type Rosa Spirea Epilobium Linnaea Grasses Comus 9\m2 S i t e p r e p a r a t i o n treatment 1) Broadcast burn areas 1.8a 3 . 4 a 2 . 9 a 1 . 2 a 9 . 5 a 3 . 1 a 2) Areas between windrows 3.6 a 5.8 a 7.9 a 1.7 a 5.8 a 5.8 a 3) Areas beneath windrows 1.7 a 4.5 a 11.8 a 1.2 a 3.1 a 12.2 a F i r e s e v e r i t y 1) Low s e v e r i t y burns i n f r e s h s l a s h 3.1 a 5.1 ab 10.2 ab 3.7 a 2.3 a 6.2 a 2) Low s e v e r i t y burns i n cured s l a s h 3.6 a 2.5 b 3.2 a 1.7 ab 7.3 a 7.3 a 3) Moderate s e v e r i t y burns 1.6 a 5.5 a 12.2 b 1.2 b 4.8 a 3.4 a 4) High s e v e r i t y burns 0.7 a 1.1 a 13.7 b 0.5 b 1.4 a 0.7 a Site preparation or burn type means followed by the same letter are not significantly different at p < .10 for Epilobium, Linnaea and Rosa and at p <.05 for Spirea. 133 conducted the year after the other burns so that vegetation in the areas subjected to low severity burns in cured slash had one year less time to develop. This is reflected in the generally lower total biomass values found for these areas than for the other treatments (Appendix 4-5). It does appear, however, that Epilobium biomass tended to increase as the severity of disturbance increased. Linnaea biomass tended to decrease with increasing degree of disturbance. Thus, it decreased from broadcast burn to windrow burn areas and as fire severity increased (Table 4-3), although not all the differences between treatments were statistically significant. No clear trends emerged for the other dominant species. Although Spirea biomass was significantly less on the plots given low severity burns in cured slash, this could again be due to the shorter period of time vegetation has had to develop on these plots. Of the three major groups of understory vegetation - shrubs, herbs and mosses - herbs dominated during the first two post treatment growing seasons, accounting for 50-80% of the total biomass present during the second growing season (Table 4-4). Moss biomass was relatively low. There were no obvious trends in biomass as a function of site preparation treatment or fire severity. Biomass values for each of the 3 groups of species, as well as the total plot biomass tended to be similar for the different treatments. The only exception was the area either broadcast or windrow burned in 1987 (low severity burns in cured slash) whose vegetation had one year less in which to develop, and consequently had a lower biomass. Schmidt and Lotan (1979) found that herbs accounted for 75% of the biomass on 5 year old broadcast and windrow burned treatment areas but accounted for about a third of the biomass in the uncut forest. Shrubs accounted for a third of the biomass in the uncut forest 134 Table 4-4. Shrub, herb and moss biomass during the first and second post-treatment growing seasons averaged by site preparation treatment and fire severity. Treatment Growing season Shrub Herb Moss g/m 1987 1988 1987 1988 1) Low s e v e r i t y burns i n f r e s h s l a s h B roadcast burn areas 6.0 7.4 3.2 28.0 Areas between windrows 8.0 14.0 5.1 11.7 Areas beneath windrows 5.8 7.2 3.1 22.0 2) Low s e v e r i t y burns i n cured s l a s h Broadcast burn areas 4.8 5.0 2.0 6.8 Areas between windrows 4.0 12.7 7.1 32.6 Areas beneath windrows 0.2 3.9 0.0 13.7 3) Moderate s e v e r i t y burns Broadcast burn areas 3.8 7.6 3.0 19.4 Areas between windrows 10.6 8.8 8.2 21.2 Areas beneath windrows 0.9 9.1 4.1 25.9 4) High s e v e r i t y burns Broadcast areas 2.7 8.0 3.2 24.2 Areas between windrows 13.9 4.6 22.7 22.7 Areas beneath windrows 4.7 6.2 7.0 19.5 0.0 0.3 0.0 0.0 0 . 2 0.0 0 . 0 0 . 0 0 . 0 0 . 0 0. 1 0.0 0. 1 0 . 9 0.4 1 .9 0.0 0.0 3.8 2.6 0.0 0.9 1 .0 1 .0 T o t a l 1987 1988 1987 1988 9.2 35.5 13.4 26.6 8.9 29.6 6.8 13.7 11.3 45.3 0.2 17.6 6.8 30.8 18.8 32.6 5.0 35.0 5 . 9 33. 1 36.7 28.3 1 1 .7 26.7 135 but a negligible amount on the treated areas. As the biomass of shrubs and herbs 5 years after treatment was not very high, Schmidt and Lotan concluded that vegetation competition with lodgepole pine regeneration in their study was not significant enough to influence seedling performance. Hamilton and Yearsley (1988) studying revegetation on moister sites following burning in the Sub-Boreal Spruce zone found that vegetation composition following disturbance was a function of the severity of disturbance, the suitability of conditions for germination and survival of seed-banking species, and the availability and establishment success of off-site seeds. They found that burning diniinished a number of species present prior to treatment, initially reducing shrubs and herbs, but within a short time significant regrowth of these species and invasion by Epilobium had occurred. From the preceding discussion the following conclusions can be made two years following treatment: 1. Seedling survival was highest on areas between windrows and lowest on areas beneath windrows. The better survival in areas between windrows was attributed to improved soil temperature, while poorer survival in windrows was attributed to moisture stress caused by the creation of a hydrophobic layer or seedlings being planted in ash rather than mineral soil. 2. Fire severity had little effect on survival. 3. Total height, height increment and basal diameter of lodgepole pine seedlings were greater on areas between windrows and least on broadcast burned areas. 136 4. Based on the preceding two points, growth performance of planted lodgepole pine seedlings after two growing seasons has been best in the unburned areas between windrows. 5. Biomass of dominant vegetation tended to decrease in the order - Epilobium > Comus > Spirea > grasses > Rosa > Linnaea. 6. Epilobium spp. biomass tended to increase and Lmnaeabiomass decrease with disturbance severity. No clear trends were apparent for the other dominant species. The generally lower biomass found for the plots given low severity burns in cured slash is probably due to vegetation on these plots having had less time to develop than on the other treatment plots. 7. Herb biomass was much greater than that of shrubs which, in turn, was much greater than that of mosses on the experimental plots. 8. Neither site preparation nor fire severity treatment appeared to have a significant effect on herb, shrub, or moss. 9. It does not appear that seedlings have been adversely affected by associated vegetation. 137 CHAPTER 5 RESEARCH SUMMARY AND OPERATIONAL RECOMMENDATIONS 138 This thesis has been concerned with the effects of treatments on fuels, and early effects on vegetation, and soils. Interpretations must be made with caution as they do not consider long-term treatment effects. The following conclusions can be made from this study: A. T R E A T M E N T EFFECTS ON FUELS 1. Over the range of burning conditions used, windrow burns consumed similar amounts of slash fuels, unlike broadcast burns which consumed greater amounts of slash fuel as the fire severity increase, ie. as fuel moisture decreased. 2. Forest floor consumption in broadcast burns was generally only a small proportion of the total fuel consumption. 3. It is operationally feasible to conduct different severity burns in slash from recently knocked down dense lodgepole pine stands. 4. The recommended choice of fire severity is low- with cured slash due to the low risk of escape associated with this fire severity class and similar fuel impacts to higher severity broadcast burns. 5. Although degree of fire severity had no statistically significant effect, due to variability of data, on depth-of-burn, it appears that if both slash removal and conservation of forest floor are important, then these can be jointly achieved by broadcast slashburning either fresh or cured lodgepole pine slash, under low severity ( F F M C 85-87, D M C < 20, D C < 120) conditions. 139 6. For windrow plots, the accumulation of fuels into piles creates a situation where the degree of fuel drying plays a limited role in determining the fire severity and amount of fuel consumed. B. T R E A T M E N T EFFECTS ON NUTRIENTS The effects of the treatments on forest floor total nutrients can be summarized as follows: 1. Windrow burning caused greater changes than broadcast burning. This was expected as windrowing concentrated the forest floor with slash into piles which were, in all cases, almost completely consumed by the windrow fires. 2. The burning conditions had no statistically significant effect on forest floor total nutrient losses in windrow plots, which exceeded 90% of the preburn nutrient quantities for all burning conditions or fire severities. 3. A l l treatments caused losses of forest floor N , P and S while some gains and some losses of K, Na, and Mg were found. Increases in forest floor cations after burning can be explained by the deposition of cation rich-ash and slash particles from burning slash. 4. Forest floor nutrient losses generally decreased in the order N > Ca > S > P > K > Mg > Na - while relative losses for broadcast burns generally followed the order N > S > P > C a > K > Mg > Na. Relative losses for windrow burns were similar as losses of individual nutrients were all very high (> 90%). 140 The effects of the treatments on nutrients in the slash can be summarized as follows: 1. Absolute nutrient losses from slash followed the order N > Ca > K, Mg > S > P > Na. 2. Losses from broadcast burns were less than those for windrow burns conducted under the same burning conditions. 3. Windrow burning results in slash nutrient losses of > 90% for all nutrients. 4. Losses of total N , P, K, Na, and Mg found for the windrow burns were greater than those reported for operational slashburns and were more similar to losses reported in studies of whole tree harvesting. 5. Phosphorus, S, K, Na, Mg, and Ca losses from slash were not influenced by age of slash whereas N losses were significantly (p<0.05) greater in fresh slash. 6. Fire severity significantly influenced the loss of all nutrients from slash with the exception of Ca. 7. Absolute and relative losses of all nutrients from slash were significantly correlated with forest floor consumption and medium slash (1-7 cm) consumption. 8. Relative losses were high (> 90%) for all nutrients in the windrow burns and were also high (> 90%) in the broadcast burns for N and P. For the broadcast burns, relative losses were generally highest for N and P and least for Ca. Fire severity had no consistent effect on relative losses in either treatment. 141 The effects of the treatments on total organic matter (non-mineral soil) nutrient changes can be summarized as follows: 1. For the windrow burns, generally > 90% of all nutrients present were lost to the atmosphere or transferred to the mineral soil during burning. 2. Nutrient quantities lost from the windrow burns were generally greater than those lost from operational slashburns and were more similar to reported losses from whole tree harvesting operations. 3. Significantly greater N , P, K, Na, Mg, Ca and S losses were generally found for windrow than from broadcast burns. 4. Fire severity significantly influenced the quantities of nutrients lost, but not the % losses, for all nutrients measured with the exception of Ca, whose losses were not significantly affected by fire severity. 5. Total nutrient losses decreased in the order N > Ca > K > Mg > S > P > Na, while relative losses for broadcast burns decreased in the order N > S > P > Mg > Ca > K > Na. Relative losses for windrow burns followed no consistent order. 6. The quantities of nutrients lost from slash were generally greater than those lost from the forest floor, with the exception of nitrogen which was found to have greater losses from the forest floor. 7. For the broadcast burns, % losses from the slash were also generally greater than those from the forest floor. For windrow burns, however % losses from slash were similar to those found for the forest floor. This can be attributed to the very high 142 consumption of both slash and forest floor in the windrow plots. The effects of the treatments on mineral soil nutrients can be summarized as follows: 1. For all N , P, S and K some increases and some decreases in quantities were observed in the surface mineral soil in both windrow burning and broadcast burning treatments. 2. The greatest changes in surface mineral soil nutrients were generally observed for Ca, then N . 3. Relatively large increases in mineral soil nutrient quantities were observed beneath windrows. The mineral soil between windrow areas, however, were found not to be greatly effected by the treatment. The large increases beneath windrows were attributed to the burning of large fuel accumulations. 4. Fire severity significantly influenced the losses of total N and mineralizable N from mineral soil (p<0.05). 5. The losses of S from mineral soil were significantly influenced by both site preparation and fire severity (p<0.05). C. T R E A T M E N T EFFECTS O N L O D G E P O L E PINE SEEDLINGS A N D ASSOCIATED  V E G E T A T I O N 1. Lodgepole pine seedling survival after two years was highest on areas between windrows and lowest on areas beneath windrows. The better survival in areas between windrows was attributed to improved soil temperature, while poorer 143 survival in windrows was attributed to moisture stress caused by the creation of a hydrophobic layer or seedlings being planted in ash rather than mineral soil. 2. Fire severity had little effect on survival. 3. Total height, height increment and basal diameter of lodgepole pine seedlings were greater on areas between windrows and least on broadcast burned areas. 4. Based on the preceding points, growth performance of planted lodgepole pine seedlings after two growing seasons has been best in the unburaed areas between windrows. 5. After 2 growing seasons biomass of dominant vegetation associated with lodgepole pine seedlings tended to decrease in the order - Epilobium > Cornus > Spirea > grasses > Rosa > Linnaea. 6. Epilobium spp. biomass tended to increase and Linnaea biomass decrease with disturbance severity. No clear trends were apparent for the other dominant species. The generally lower biomass values for the plots given low severity burns in cured slash can be attributed to the fact that these burns were conducted one year after the others so that the vegetation in these plots had less time to develop than the vegetation on the other plots. 7. During the first two post-treatment growing seasons, herb biomass was much greater than that of shrubs which, in turn, was much greater than that of mosses on the experimental plots. 8. Neither site preparation treatment nor fire severity appeared to have a significant effect on herb, shrub, or moss biomass during the first two post-treatment growing seasons. 144 9. It does not appear that, after two years of growth, seedlings have been adversely affected by associated vegetation. IMPLEMENTATION OF STUDY RESULTS Based on the results of this study, the following recommendations can be made pertaining to the management of dense lodgepole pine stands; If a dense lodgepole pine stand is to be removed to allow planting of lodgepole pine seedlings, once the stand is knocked down -1. If the desired treatment goal is to maximize slash and forest floor reduction then -Cured slash should be windrow burned under low severity conditions. 2. If the desired treatment goal is to maximize slash reduction and minimize forest floor reduction then -Cured slash should be broadcast burned under low severity conditions. 3. i f the desired treatment goal is to maximize mineral soil exposure then -Areas should be broadcast bumed under high severity conditions. 4. If the desired treatment goal is to minimize treatment expense then -Broadcast burning under low severity conditions is most economical 5. If the desired treatment goal is to minimize ecosystem nutrient loss then -Windrow burning should be avoided and broadcast burning should be conducted at the lowest severity possible when considering other management objectives. 6. If the desired treatment goal is to maximize survival, total height, height increment and basal diameter growth of lodgepole pine seedlings in the first two growing seasons then -145 Those treatments which maximize mineral soil exposure or complete removal of forest floor should be considered. If rehabilitation of densely stocked lodgepole pine is considered feasible on an operational basis then from the results of the study the most ecologically and economically sound treatment option would be: Broadcast burning of cured slash under low severity conditions. This treatment is considered desirable for the following reasons: Broadcast burning under low severity conditions was found to be one of the most economical of the treatments considered. The low severity broadcast burns in cured slash removed greater quantities of slash when compared to the low severity broadcast burns in fresh slash, while at the same time minimized the loss of forest floor. This is considered desirable as nutrient losses are reduced when compared to higher severity broadcast burns and windrow burn treatments, and "the site is more accessible for planting when compared to low severity burns in fresh slash. The only disadvantage of this treatment appears to be relatively poorer establishment and growth of seedlings. With a longer delay in planting this problem may be overcome. The poor survival results could be the result of planting immediately following burning and a planting delay could overcome this. Relatively good survival of seedlings planted on the plots given low severity broadcast burns in fresh slash indicate that seedling survival does not have to be poor following low severity burns. 146 R E S E A R C H RECOMMENDATIONS Future studies are required to assess nutrient input/loss rates and nutrient productivity relationships in these lodgepole pine ecosystems. Studies of this nature would help address the question of whether treatments such as the ones described severely reduce site productivity and whether ecosystem recovery from disturbance can occur within a single rotation. The design and layout of this experiment provides a unique opportunity to investigate long-term effects on seedling and vegetation development as well as site nutrient status. Therefore future work should include long-term monitoring of this study site. 147 BIBLIOGRAPHY Adams, P.W. and J.R. Boyle. 1980. Effects of fire on soil nutrients in clearcut and whole-tree harvest sites in Central Michigan. 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APPENDIX 2-1 Assessment of the costs of conducting the site preparation, burning and mop-up operations in the experimental treatments 158 Total Cost of Treatments For each of the eight rehabilitation technique/burning severity treatments completed, the total cost of mechanical preparation, burning and mop-up were estimated from the data supplied by Forest Service personnel. A l l treatment costs have been borne by the Lakes Forest District. Treatment costs were separated into three categories - mechanical preparation, burning, and mop-up. Mechanical preparation included fire-guard, fire access road and water hole construction, and knocking down and windrowing operations. Burning included all ignition and patrol operations; and mop-up included all mop-up operations until the burns were declared out. These costs included the salaries of all operational Forest Service staff, and contract crews who assisted with the operations. Salaries included different amounts of overtime for the ..different burning periods so to facilitate comparison all salaries for all burns were adjusted to regular hourly rates. A summary of the actual and relative treatment costs is given in the following 2 tables. The actual costs are not considered representative of true operational costs because of the small areas involved. Therefore it was felt that relative costs would provide a more meaningful comparison of burning costs. For the broadcast burns it can be seen that preparation costs generally exceeded burning or mop-up costs. However, for the windrow burns, mop-up costs exceeded preparation costs in the low severity burns in cured slash and the high severity burns. These high costs were caused by insufficient on-site water, resulting in prolonged smouldering of the windrows, causing lengthy mop-up operations. As well for the low severity burns in cured slash protection staff were concerned that smouldering might continue into the summer, posing high risks to adjacent thinning slash, and therefore spent more time and money in ensuring 159 that the fires in these windrows were extinguished. The windrow and burn (WB) treatment costs exceeded the knockdown and broadcast burn (KB) treatment costs because of the generally higher preparation, burning and mop-up costs associated with the WB treatments. Mop-up costs were higher because a longer patrol period was necessary to ensure that the fires were out. The relationship between burning severity and cost must be looked at with caution as cost was influenced by factors other than burn severity. Thus, for example, as a result of rain the day after the moderate severity burns, mop-up costs for these burns were less than for the respective low and high severity burns. Burning costs generally decreased from low severity through to high severity broadcast burns. This was partly due to a change in ignition technique. Both the low severity fresh slash and one of the moderate severity broadcast burn plots were burned using a strip backfire ignition pattern. This ignition technique was 3 times slower than for the flank fire ignition technique which was used for remaining broadcast burn plots. Thus, it may be concluded that for the study area-1. The windrow and burn treatment is more expensive than the knockdown and broadcast burn treatment. 2. Broadcast burning costs can be reduced by using an ignition technique which causes more rapid ignition and burning of an entire burning unit. 160 3. Mop-up costs can be greatly affected by the location and abundance of on-site water, rain immediately after burns and the time of year in which burning takes place. 161 Experimental cost per hectare of the different site preparation and burning treatments for the experimental plots. Treatment Broadcast Burn Windrow Burn (KB) (WB) Low s e v e r i t y burns in f r e s h s l a s h (1986) P r e p a r a t i o n $1218 Burning 1161 Mop-up 604 T o t a l Cost $2985 $1 747 775 1 742 $4264 Low s e v e r i t y burns i n cured s l a s h (1987) P r e p a r a t i o n Burning Mop-up T o t a l Cost $1218 1584 1 136 $3938 $1747 1937 3643 $7327 Moderate s e v e r i t y burns (1986) P r e p a r a t i o n $1218 Burning 1143 Mop-up 538 T o t a l Cost $2899 $1747 1 93 7 3643 $3946 High s e v e r i t y burns (1986) P r e p a r a t i o n $1218 Burning 766 M o p v u p 986 T o t a l Cost $2970 $1 747 1022 3069 $5838 162 Summary of the relative burning costs for the experimental plots. Treatment Broadcast Burn Windrow Burn Low s e v e r i t y burns i n f r e s h s l a s h (1986) P r e p a r a t i o n 2.3 Burning 2.2 Mop-up 1.1 3.2 1 . 4 3 . 2 Low s e v e r i t y burns in cured s l a s h (1987) P r e p a r a t i o n Burning M op - up 2.3 2.9 2 . 1 3 . 2 3.6 6 . 8 Moderate s e v e r i t y burns (1986) P r e p a r a t i o n 2.3 Burning 2.1 Mop-up 1.0 High s e v e r i t y burns (1986) P r e p a r a t i o n Burning M op - up 1 . 8 T o t a l Treatment Costs L o w _ s e v e r i t y burns i n f r e s h s l a s h 1.0 1.5 Low s e v e r i t y burns i n cured s l a s h 1.4 2.5 Moderate s e v e r i t y burns 1.0 1.4 High s e v e r i t y burns 1.0 2.0 Relative costs were determined separately for the individual operation costs and the total treatment costs. The least expensive operation (mop-up in the moderate burns) and the least expensive treatment (broadcast in the moderate severity burns) were assigned relative costs of 1.0. APPENDIX 2-2 Pretreatment lodgepole pine, understory vegetation, and forest floor biomass in the experimental plots 164 Pretreatment biomass loading for lodgepole pine stemwood, stembark, needles, branches, dead branches and roots for the experimental plots. Mass (kg/m ) PLOT STEMWOOD STEMBARK NEEDLE BRANCH DEAD ROOTS TOTAL BRANCHES B I OMASS 1 mean 3.2 0.5 0.4 0.4 0.5 0 . 4 5 . 4 s.d. 0.3 0 . 1 0.0 0.1 0.3 0 . 4 1 . 2 2 mean 4 . 0 0 . 6 0.5 0 . 7 0 . 3 1 . 0 7 . 1 s.d. 0 . 6 0 . 1 0 . 1 0 . 1 0 . 0 0 . 2 1 . 1 3 mean 5.4 0.8 0.6 1 . 0 0.4 1 .3 9.5 s.d. 0 . 5 0 . 1 0 . 1 0 . 1 0 . 0 0 . 1 0 . 9 4 mean 3 . 5 0.5 0.4 0 . 5 0.3 0.8 6 . 0 s.d. 0.2 0 . 0 0.0 0 .0 0.0 0 . 1 0.3 5 mean 3.9 0 . 6 0.5 0 . 7 0.3 1 . 0 7.0 s.d. 1 . 8 0 . 2 0.2 0.4 0 . 1 0 . 5 3.2 6 mean 4.3 0.6 0 . 5 0.7 0.3 1 . 0 7.4 s.d. 1 . 2 0.2 0. 1 0.2 0 . 1 0.3 2 . 1 7 mean 5.4 0.8 0.6 1 . 0 0.4 1 .5 9.7 s.d. 0.7 0 . 1 0. 1 0 . 2 0.0 0 . 2 1 : 3 8 mean 5 . 3 0 . 7 0.6 1 . 0 0 . 4 1 . 4 9 . 4 s.d. 1 .6 0 .2 0 . 2 0.4 0 . 1 0.5 . "3.0 9 mean 6 . 4 1 . 0 0 . 7 1 .3 0 . 4 1 . 8 11.6 s.d. 1 .4 0 . 1 0 . 2 0.3 0 . 1 0 . 5 2 . 6 1 0 mean 4 . 8 0 . 7 0 . 6 0.8 0 . 3 1 . 2 8.4 s.d. 1 . 3 0.2 0 . 2 0 . 2 0 . 1 0.3 2 . 3 1 1 mean 6.6 1 . 0 0.8 1 . 2 0.5 1 .7 11.8 s.d. 0 . 6 0 . 1 0 . 1 0 . 2 0 . 0 0.3 1 . 3 1 2 . mean 6 . 7 1 . 0 0 . 8 1 .2 0 . 5 1 . 7 11.9 s.d. 1 . 7 0.2 0.2 0.4 0. 1 0.5 3 . 1 13 mean 6.0 0.8 0.7 1 . 2 0.4 1 .6 10.7 s.d. 0 . 9 0 . 1 0 . 1 0 . 2 0 . 1 0 . 3 1 . 7 14 mean 5 . 2 0 . 7 0.6 1 .0 0.4 1 .4 9.3 s.d. 1 .4 0.2 0 . 2 0.4 0.1 0.5 2.8 1 5 mean 6 . 8 1 . 0 0.8 1 . 4 0.5 1 . 9 12.4 s.d. 1 .3 0.2 0 . 1 0.3 0 . 1 0 . 5 2.5 1 6 mean 6.2 0 . 9 0 . 7 1 . 2 0 . 4 1 . 6 11.0 s.d. 0 . 6 0 . 1 0.1 0 . 1 0 . 0 0 . 2 1 . 1 1 7 mean 5.6 0.8 0.6 1 . 1 0.4 1 .4 9.9 s.d. 1 . 2 0.2 0 . 1 0.3 0 . 1 0 . 3 2 . 2 1 8 mean 7.8 1 . 1 0 . 9 1 . 7 0 . 5 2 . 4 14.4 s.d. 2 . 5 0.3 0.3 0 . 7 0.2 1 . 2 5 . 2 CONTROL 1 mean 4.3 0 . 6 0 . 5 0 . 7 0.3 1 . 0 7 . 4 s.d. 1 . 2 0.2 0 . 1 0.2 0. 1 0.3 2. 1 CONTROL 2 mean 3.4 0 . 5 0.4 0.7 0 . 2 0.9 6 . 1 s.d. 0.9 0 . 1 0 . 1 0.2 0 . 1 0.3 1 . 7 CONTROL 2 mean 5.4 0 . 7 0.6 1 .3 0.4 1 .8 10.2 s.d. 0 . 3 0 . 0 0 . 0 0 . 1 0 . 0 0 . 2 0 . 6 165 Pretreatment understory vegetation (herbs, shrubs, mosses and lichens) biomass in the experimental plots. Mass kg/m PLOT HERBS SHRUBS MOSSES TOTAL LICHENS B I OMASS 1 mean 0 .02 0.01 0 . 48 0.51 s.d. 0.01 0.01 0.10 0.12 2 mean 0.01 0 . 02 0.37 0.40 s.d. 0.01 0 . 02 0.07 0.10 3 mean 0.01 0.02 0.31 0 .34 s.d. 0.01 0.01 0.11 0.13 4 mean 0.01 0.02 0 . 24 0.27 s.d. 0.01 0.01 0 . 04 0.06 5 mean 0.01 0.01 0 . 26 0 . 28 s.d. 0.00 0.01 0 . 08 0.09 6 mean 0 .02 0.01 0.25 0 . 28 s.d. 0.01 0.00 0.14 0.15 7 mean 0.01 0.10 0.30 0.41 s.d. 0.00 0.11 0.17 0 .• 2 8 8 mean 0.01 0 .06 0.42 0 .49 s.d. 0.01 0.08 0.21 x "0.30 9 mean 0 .02 0.01 0.25 0.28 s.d. 0.01 0.01 0.07 0 . 09 1 0 mean 0.01 0.10 0.38 0.49 s.d. 0.01 0.18 0 . 24 0 .43 1 1 mean 0.01 0.07 0.30 0 .38 s.d. 0.01 0 . 09 0.25 0.35 12 mean 0.02 0.01 0.34 0.37 s.d. 0.01 0 . 00 0.16 0.17 1 3 mean 0.02 0.06 0.34 0.42 s.d. 0.01 0.11 0.15 0.27 14 mean 0 . 02 0 . 03 0.24 0 . 29 s.d. 0 .02 0.01 0.15 0.18 15 mean 0 .04 0.01 0.18 0 . 23 s.d. 0.02 0.01 0.11 0.14 1 6 mean 0.02 0.28 0.14 0 .44 s.d. 0.01 0.35 0 . 09 0.45 1 7 mean 0 . 02 0.12 0.31 0.45 s.d. 0.01 0 . 23 0 . 23 0.47 18 mean 0 . 02 0.13 0.15 0.30 s.d. 0.01 0.18 0.10 0 . 29 CONTROL 1 mean 0.01 0.05 0.41 0.47 s.d. 0.01 0.07 0.31 0.39 CONTROL 2 mean 0.02 0 . 02 0.39 0.43 s.d. 0.01 0.01 0.08 0.10 CONTROL 3 mean 0.02 0.02 0.2 8 0.32 s.d. 0.02 0.02 0.19 0.23 166 Pretreatment forest floor biomass for the experimental plots. 2 Mass (kg/m ) P l o t Mean Standard d e v i a t i o n 1 3.9 0.7 2 5.4 1.1 3 4.6 1.2 4 3.1 1.4 5 4.2 1.2 6 3.9 1.4 7 6.3 3.0 8 7.7 5.3 9 4.5 3.2 10 3.1 1.4 11 3.8 1.7 12 3.4 1.9 13 4.1 2.6 14 4.3 3.1 15 7.3 3.5 16 3.7 1 .9 17 3.0 2.6 18 6.2 3.5 CONTROL 1 5.7 2.6 CONTROL 2 7.5 4.3 CONTROL 3 7.3 2.9 Pretreatment forest floor bulk density (g/cm3) averaged for the experimental plots. Mean Standard E r r o r Sample S i z e Block 1 p l o t s 1-6 0.15 0.05 18 Block 2 p l o t s 7-12 0.15 0.07 18 Block 2 p l o t s 13-18 0.15 0.11 18 168 APPENDIX 2-3 Fuel consumption, pre- and postburn slash fuel loads in the experimental plots 169 Preburn and postburn mass and consumption of slash fuels by sizeclass for the experimental plots. Q u a n t i t y (kg/m ) , < 1 cm 1 - 7 cm S l a s h diameter c l a s s LOW SEVERITY ( f r e s h ) > 7 cm TOTAL SLASH LOAD Broadcast p l o t s P l o t 2 Preburn Postburn Consumption 0 . 0 , 0 10.0 3 . 1 6.9 18.1 5 . 4 12.7 P l o t 17 Preburn P o s t b u r n Consumption 9.0 7.0 2 . 0 16.5 8.6 7.9 Windrow p l o t s P l o t 7 Preburn Postburn Consumpt i on 0 . 0. 0 8.5 0 . 5 8 . 0 15.8 0.6 15.2 24.7 1 . 1 23 . 6 P l o t 10 Preburn Postburn Consumpt i on 8. 1 0 . 5 7.6 17.8 0.8 17.0 26.2 1 . 3 24 . 9 LOW SEVERITY ( c u r e d ) Broadcast p l o t s P l o t 1 Preburn Postburn Consumpt i on 6. 1 , 5 15.8 6.9 8.9 22.4 7 . 9 14.5 P l o t 4 P reburn Postburn Consumpt i on 0 . 0 , 0 6. 0 5 23 . 7 8.0 15.7 30.3 8 . 7 21.6 Windrow p l o t s P l o t 3 Preburn P o s t b u r n Consumpt i on 14.1 0 . 7 13.4 24 . 0 1 . 1 22.9 P l o t 5 Preburn P o s t b u r n Consumption 20 . 5 1 . 4 19.1 26.7 2 . 0 24 . 7 170 Preburn and postburn mass and consumption of slash fuels by sizeclass for the experimental plots. S l a s h diameter c l a s s MODERATE SEVERITY < 1 cm S i z e c l a s s l o a d i n g (kg/m ) 1-7 cm > 7 cm TOTAL SLASH LOAD Broadcast p l o t s P l o t 8 Preburn P o s t b u r n Consumpt i on 0 . 0 , 0 1 5 . 5 , 1 0 . 23 . 9 6 . 5 17.4 P l o t 11 Preburn P o s t b u r n Consumpt i on 21 . 5 . 16. 30.8 5.8 25.0 Windrow p l o t s P l o t 12 Preburn P o s t b u r n Consumpt i on 0. 0 . 0 , 18. 0 . 18.1 28.1 0.9 27.2 P l o t 16 Preburn P o s t b u r n Consumpt i on 0 . 0 . 0 , 8 . 0 , 8 . 1 5 . 0. 14.8 23 . 0 . 23 . HIGH SEVERITY Broadcast p l o t s P I o\ 9 Preburn P l o t 13 Postb u r n Consumption Preburn Postburn Consumption 0.5 0.0 0 . 5 0.4 0 . 0 0.4 18.9 4 . 2 14.7 19.1 8 . 4 10.7 27. 4 . 22 . 27. 9. 18. P l o t 14 Preburn P o s t b u r n Consumpt i on 0.4 0.0 0.4 6 . 8 0 . 7 6.1 22 . 8 5 . 5 17.3 30.0 6 . 2 23 .8 Windrow p l o t s P l o t 15 Preburn Postburn Consumpt i on 0 . 0 . 0 20 . 1 . 19. 29. 1 . 28 , P l o t 18 Preburn P o s t b u r n Consumption 4 . 0 .4 17. 2 . 1 5 , 171 Proportion of area occupied by areas beneath windrows and areas between windrows. Treatment Area beneath Area between Windrows Windrows Low s e v e r i t y burns i n f r e s h s l a s h P l o t 7 17 83 P l o t 10 17 83 Low s e v e r i t y burns in cured s l a s h P l o t 3 25 75 P l o t 5 27 73 Moderate s e v e r i t y burns P l o t 12 17 83 P l o t 16 24 76 High s e v e r i t y burns P l o t 15 .4 0 6 0 P l o t 18 39 62 Proportions are based on three 100 metre transects per windrow plot. APPENDIX 3-1 Pretreatment nutrient concentrations in lodgepole pine components, understory vegetation and dead woody materials. 173 Pretreatment nutrient concentrations (%) in lodgepole pine components in the experimental plots. N Component Stemwood mean 0.109 s.d. 0.046 Stembark mean 0.338 s.d. 0.079 Need Ies mean 0.835 s.d. 0.201 L i v e mean 0.513 Branches s.d. 0.075 Dead mean 0.293 Branches s.d. 0.060 Roots mean 0.128 s.d. 0.033 P K Na 0.019 0.045 0.003 0.017 0.036 0.001 0.037 0.118 0.005 0.017 0.055 0.001 0.113 0.163 0.013 0.014 0.038 0.008 0.067 0.077 0.007 0.012 0.027 0.003 0.005 0.060 0.004 0.007 0.022 0.002 0.007 0.040 0.004 0.001 0.042 0.003 Mg Ca S 0.024 0.059 0.023 0.007 0.020 0.016 0.078 0.221 0.051 0.024 0.134 0.021 0.176 0.395 0.099 0.094 0.159 0.019 0.051 0.183 0.077 0.028 0.054 0.018 0.071 0.098 0.049 0.044 0.060 0.018 0.038 0.070 0.023 0.033 0.016--. 0.019 Means are for 23 samples per component. 174 Pretreatment nutrient concentrations (%) in dead woody materials in the experimental plots. N P K Na Mg Ca S S i z e c l a s s (cm) < 1 mean 0 . 670 0.013 0 .025 0 . 004 0 .025 p. 167 0 .055 s.d. 0 .520 0.011 0 .011 0 .002 0 .010 0 . 059 0 . 032 1-3 mean 0 , .102 0.006 0 .014 0 .003 0 .015 0 . 075 0 .015 s.d. 0 . 038 0.003 0 .010 0 .005 0 .011 0 . 021 0 .015 3-5 mean 0 , . 084 0.005 0 .012 0 .001 0 .012 0 . 069 0 .014 s.d. 0 .021 0 .002 0 .010 0 .001 0 .008 0 . 0 1 6 0 .010 5-7 mean 0 .  074 0.004 0 .008 0 .001 0 .014 0 . 067 0 .007 s.d. 0 . 025 0.001 0 .005 0 .001 0 .003 0 . 011 0 .008 7-1 2 mean 0 , .059 0.003 0 .010 0 . 002 0 .013 0 . 0 66 x 0 .007 s.d. 0 .014 0.001 0 .009 0 .001 0 .004 0 . 013 0 .007 > 1 2 mean 0 . 052 0.002 0 .008 0 .001 0 .013 0 . 066 0 .007 s.d. 0 .012 0.001 0 .010 0 . 001 0 .005 0 . 019 0 .007 Mean nutrient concentrations are for 18 samples for each size class. 175 Pretreatment nutrient concentrations (%) in understory vegetation in the experimental plots. U n d e r s t o r y N p K Na Mg Ca s Component P l o t s Shrubs 1-6 mean 1 .621 0 . 146 0 .521 0 . 009 0 . 199 0 .530 0 . 143 s.d. 0 .214 0 .018 0 . 106 0 . 004 0 . 039 0 . 1 24 0 . 030 7-12 mean 1 .370 0 .179 0 .442 0. 009 0. 204 0 .528 0 .124 s.d. 0 .282 0 .023 0 .064 0. 005 0. 059 0 . 102 0 .022 13-18 mean 1 .469 0 . 123 0 .421 0. 007 0. 128 0 .347 0 . 100 s.d. 0 .208 0 . 037 0 .202 0. 005 0 . 044 0 . 108 0 . 021 Herbs 1-6 mean 0 .954 0 . 174 0 .376 0 . 012 0 . 274 1 .901 ' 0 . 10 2 s.d. 0 .077 0 .049 0 .017 0. 006 0. 083 0 .804 0 .005 7-12 mean 0 .820 0 . 138 0 .354 0 . 006 0 . 235 2 .008 0 .113 s.d. 0 .082 0 .034 0 .012 0. 002 0 . 023 0 .465 0 .015 13-18 mean 1 .028 0 .142 0 .368 0. 013 0 . 199 2 .123 0 . 126 s.d. 0 .141 0 .031 0 .015 0. 005 0. 020 0 .594 0 .018 Hosses 1-6 L i c h e n s mean 2 .665 0 . 1 09 0 . 253 0. 01 1 0. 067 0 .325 0 .138 s.d. 0 .320 0 .008 0 . 064 0 . 004 0. 026 0 .108 0 .014 7-1 2 mean 2 . 084 0 .110 0 . 180 0 . 009 0 . 070 0 .375 0 .130 s.d. 0 .217 0 .009 0 .052 0 . 002 0 . 030 0 .101 0 .017 13-18 mean 2 .376 0 .124 0 .193 0 . 008 0 . 095 0 .476 0 . 1 26 s.d. 0 . 202 0 .008 0 .045 0. 003 0. 014 0 .055 0 .011 Means are for 6 composite samples for each category per treatment block. APPENDIX 3-2 Pre- and postburn nutrient concentrations in forest floor and slash. 177 Forest floor nutrient concentrations (%) in plots subjected to broadcast burning, measured before and after burning. N P K Na Mg Ca S Low s e v e r i t y burns i n f r e s h s t a s h ( p l o t s 2,17) Preburn (Aug. 1985) mean 1.254 0.099 0.097 0.010 0.081 0.265 0.097 s.d. 0.199 0.013 0.024 0.003 0.017 0.050 0.023 Immediately mean 0.746 0.093 0.111 0.014 0.099 0.308 0.049 Postburn (Aug. 1986) s.d. 0.111 0.016 0.012 0.002 0.023 0.046 0.024 1 Year mean 0.792 0.068 0.129 0.009 0.107 0.490 0.086 Postburn (Aug. 1987) s.d. 0.096 0;015 0.027 0.002 0.021 0.148 0.011 Low s e v e r i t y burns i n cured s l a s h ( p l o t s 1,4) Preburn (Aug. 1985) mean 1.254 0.099 0.097 0.010 0.081 0.265 0.097 s.d. 0.199 0.013 0.024 0.003 0.017 0.050 0.023 Immediately mean 0.737 0.114 0.197 0.014 0.132 0.230 0.069 Postburn (June 1987) s.d. 0.118 0.019 0.024 0.002 0.052 0.107 0.010 2 Month mean 0.873 0.094 0.191 0.014 0.112 0.606 0.083 Postburn (Aug. 1987) s.d. 0.172 0.020 0.022 0.004 0.032 0.151 0.008 Moderate s e v e r i t y burns ( p l o t s 8,11) Preburn (Aug. 1985) mean 1.254 0.099 0.097 0.010 0.081 0.265 0.097 s.d. 0.199 0.013 0.024 0.003 0.017 0.050 0.023 Immediately mean 0.772 0.126 0.142 0.029 0.117 0.813 0.048 Postburn (Aug. 1986) s.d. 0.149 0.028 0.016 0.002 0.041 0.118 0.021 1 Year mean 0.741 0.081 0.167 0.014 0.126 0.445 0.082 Postburn (Aug. 1987) s.d. 0.117 0.022 0.053 0.004 0.043 0.293 0.009 High s e v e r i t y burns ( p l o t s 9,13,14) Preburn (Aug. 1985) mean 1.254 0.099 0.097 0.010 0.081 0.265 0.097 s.d. 0.199 0.013 0.024 0.003 0.017 0.050 0.023 Immediately mean 0.767 0.117 0.185 0.029 0.120 0.997 0.065 Postb u r n (Aug. 1986) s.d. 0.144 0.026 0.075 0.006 0.048 0.197 0.015 1 Year mean 0.694 0.078 0.176 0.010 0.120 0.417 0.097 Postb u r n (Aug. 1987) s.d. 0.159 0.029 0.050 0.004 0.042 0.240 0.015 178 Immediate postburn nutrient concentrations (%) in slash in the plots given low severity burns in fresh slash. Na Mg Ca S i z e C l a s s (cm) Broadcast burn p l o t s 2,17 < 1 mean s.d. 1.1-3.0 mean s.d. 3.1-5.0 mean s.d. 5.1-7.0 mean s.d.' 7.1-12.0 mean s.d. > 1 2 mean s.d. 0.319 0. 108 0 .071 0.010 0 . 0 62 0.007 0.056 0.011 0.055 0 . 009 0 . 034 0 . 002 0.031 0.018 0.009 0.004 0.008 0 .003 0 . 006 0 .003 0.006 0.004 0.001 0.001 0. 170 0. 109 0 . 044 0.015 0.040 0.020 046 003 043 022 005 001 0.010 0.006 001 001 001 001 002 001 0.001 0.000 0.001 0.000 0 . 067 0.026 .032 ,011 ,027 ,006 , 025 004 0.024 0 . 003 0.012 0.003 0.425 0.128 0.100 0.015 0 .099 0.022 0 .085 0.019 0.084 0.008 0 .053 0.012 0 .028 0.021 0.025 0 .025 0 . 028 0.013 0.014 0.007 0.019 0.016 0.030 0.017 Windrow burn p l o t s 7,10 < 1 mean s.d. 1.1-3.0 mean s.d. 3.1-5.0 mean s.d. 5.1-7.0 mean s.d. 7.1-12.0 mean s.d. > 12 mean s.d. 0.334 0. 177 0.153 0 . 064 0.102 0.070 0 . 049 0.005 0.051 0.005 0.048 0.010 0 . 039 0.020 0.023 0.010 0.013 0.010 0.005 0.002 0.005 0 . 004 0 .002 0.001 0. 127 0.014 0.058 0.017 046 016 038 008 043 005 0.016 0.001 0 .003 0.001 0.002 0.001 0.012 0.013 001 000 002 001 003 003 0.057 0.016 0.051 0.017 0 . 036 0.008 030 ,006 024 008 018 006 0.401 0 .222 0.127 0.037 0.102 0.012 093 016 085 021 079 011 0.038 0.030 0.027 0.016 0.012 0.004 019 014 015 007 023 041 Means are for 3 samples per size class per plot postburn. 179 Immediate postburn nutrient concentrations (%) in slash in the plots given low severity burns in cured slash. N S i z e C l a s s (cm) Broadcast burn p l o t s 1,4 Na Mg Ca < 1 mean s.d. 1.1-3.0 mean s.d. 3.1-5.0 mean s.d. 5.1-7.0 mean s.d. 7.1-12.0 mean s.d. > 1 2 mean s.d. 0.168 0.019 0 .023 0.011 0.012 0.006 0.012 0.005 0.011 0.003 0.007 0.005 0.040 0.018 0 .009 0.004 0.008 0.004 005 002 003 000 003 001 0.151 0.110 0 .078 0 . 046 065 031 066 023 014 006 016 014 0.009 0.004 .004 ,002 , 002 ,002 ,002 ,001 0.004 0.002 0.001 0.001 0.081 0.028 0 . 038 0.008 0.026 0.007 026 002 020 006 013 005 0.328 0.065 0.212 0.035 0.111 0.019 101 006 101 011 075 019 0.045 0.006 0.032 0.005 0.026 0 . 003 025 003 023 001 022 002 Windrow burn p l o t s 3,5 < 1 mean s.d. 1.1-3.0 mean s.d. 3.1-5.0 mean s.d. 5.1-7.0 mean s.d. 7.1-12.0 mean s.d. > 12 mean s.d. 0 .205 0.040 0.023 0.009 0.013 0.006 0.015 0.004 0.010 0.003 0.010 0.003 0 . 040 0.008 007 002 006 002 006 004 0.004 0 .002 0.002 0.001 0.154 0 . 068 0.045 0.012 049 018 049 026 04 1 028 0.044 0.027 0 . 002 0.001 004 002 002 002 003 002 0.010 0.011 0.000 0.000 0 . 0 . 0 . 0 . o; 0 . 0 . 0 . 0 . 0 . 0 . 0 . 1 24 027 039 009 036 006 029 010 018 004 015 004 0.383 0.123 0 . 1 74 0 . 039 144 037 146 025 1 1 0 015 0.061 0.006 0.032 0 .005 024 002 028 007 023 002 0.081 0.018 0.020 0 .002 Means are for 3 samples per size class per plot postburn. 180 Immediate postburn nutrient concentrations (%) in slash in the plots given moderate severity burns. N S i z e C l a s s (cm) Broadcast burn p l o t s 8,11 Na Mg Ca < 1 mean s.d. 1.1-3.0 mean s.d. 3.1-5.0 mean s.d. 5.1-7.0 mean s.d. 7.1-12.0 mean s.d. > 1 2 mean s.d. 0 .380 0.140 0.052 0.000 0 .046 0 . 008 0 . 044 0.005 0 .043 0.000 0.045 0.002 0 . 065 0.015 0.008 0.001 0.004 0.001 0.002 0.000 0.002 0.000 0 .002 0.003 0.255 0.055 0 . 043 0.004 0.055 0.011 0 . 054 0 . 006 0.052 0.008 0.041 0.027 0.005 0 .002 0.002 0.001 0.005 0.004 0.003 0.001 0 . 002 0.001 0.001 0.001 0.108 0 .026 0.023 0 .005 0.027 0 . 006 .024 ,007 022 , 003 ,022 010 0 .486 0.189 0.140 0.018 142 043 0.133 0.021 134 017 0.136 0.014 0.045 0.009 0.004 0.005 0.007 0.000 0.011 0.015 0.014 0.000 0.014 0.000 Windrow burn p l o t s 12,16 < 1 mean s.d. 1.1-3.0 mean s.d. 3.1-5.0 mean s.d. 5.1-7.0 mean s.d. 7.1-12.0 mean s.d. > 1 2 mean s.d. 0.311 0.017 0.114 0.016 0.063 0.008 0 . 064 0.024 0.052 0 . 006 0.044 0.001 0.042 0 . 005 0.015 0.006 012 007 010 005 010 004 0.117 0 . 049 0 . 065 0.018 .055 .011 .059 , 009 , 045 ,010 0.013 0.006 0.003 0.001 0 .002 0.001 0.005 0.006 0 .025 0 . 007 001 001 003 001 001 000 0.071 0 . 030 0.058 0.015 0.034 0 . 006 033 014 026 007 020 006 0.473 0.099 242 096 0.154 0.032 126 017 1 1 1 009 105 012 0.055 0.007 0.026 0 .025 020 007 034 009 026 005 0.018 0.000 Means are for 3 samples per size class per plot postburn. 181 Immediate postburn nutrient concentrations (%) in slash in the plots given high severity burns. N S i z e C l a s s (cm) Broadcast burn p l o t s 9,13,14 Na Mg Ca < 1 mean s.d. 1.1-3.0 mean s.d. 3.1-5.0 mean s.d. 5.1-7.0 mean s.d. 7.1-12.0 mean s.d. > 1 2 mean s.d. 0.255 0 . 085 0.127 0.014 0 . 068 0.011 0 . 060 0.006 0.042 0.002 0.044 0.009 0 .059 0.013 0.030 0.013 0 . 003 0 . 002 0.002 0.001 0.002 0.002 0.002 0.013 0.300 0 . 088 0.122 0 . 044 0 .066 0.022 062 013 043 009 026 022 0.004 0.002 0 .005 0.002 0.003 0.002 0.002 0.001 0.003 0 . 002 0 . 002 0.001 0.081 0 . 037 0 . 041 0.011 0.030 0 . 003 0 . 026 0.005 0.020 0.003 0.015 0.005 0.353 0 .049 0.215 0.070 0.059 0.007 1 73 055 1 93 115 0.128 0.016 0.112 0 . 044 0 1 6 015 000 000 005 004 0.014 0.004 0.007 0.000 Windrow burn p l o t s 15,18 < 1 mean s.d. 1.1-3.0 mean s.d. 3.1-5.0 mean s.d. 5.1-7.0 mean s.d. 7.1-12.0 mean s.d. > 12 mean s.d. 0.252 0 . 044 0.111 0.016 0.101 0 . 039 0.063 0.006 0.051 0 . 003 0 . 040 0.003 0.025 0.011 0.018 0 . 005 0.012 0.006 0 . 008 0.002 0.008 0.002 0.002 0.001 0 . 089 0.059 0.072 0.035 ,072 ,022 069 028 050 006 0.007 0 .004 0 .003 0.001 0.002 0.001 0.019 0.019 004 003 003 001 002 001 0 . 063 0.017 0.043 0 . 009 033 005 027 007 020 004 0.389 0 . 098 0. 189 0.093 0. 189 0 . 097 0.019 0.009 1 1 1 019 105 012 1 05 026 0 . 044 0.008 0.028 0 . 043 02 1 013 028 032 023 018 0.005 0.008 Means are for 3 samples per size class per plot postburn. APPENDIX 3-3 Pretreatment nutrient quantities in lodgepole pine biomass components. Pretreatment nitrogen content (kg/ha) of lodgepole pine components in the experimental plots. COMPONENT PLOT STEMWOOD STEMBARK NEEDLES L I VE DEAD ROOTS TOTAL BRANCHES BRANCHES TREE 1 35 . 0 16.9 33.4 20 . 5 14.6 5 . 1 125. 5 (16.3) (5.5) (11.6) (5.9) (9.3) (5.3) (53. 8) 2 43.8 20.3 50.1 35.9 8.8 12.8 171. 7 (21.1) (6.1) (14.7) (7.3) (1.8) (4.2) (55 . 2) 3 5 9.1 27.0 66.8 51.3 11.7 16.6 232 . 5 (27.6) (7.4) (18.1) (9.1) (2.4) (4.5) (69. 1 ) 4 38.3 16.9 41.8 25 . 7 8.8 10.2 14 1. 7 (17.6) (4.0) (10.1) (3.8) (1.8) (2.9) (40 . 2) 5 42.7 20 .3 50.1 35.9 8.8 12.8 170 . 6 (27.8) (9.0) (20.6) (21.2) (3.4) (7.2) (89. 2) 6 47. 1 20.3 50.1 35.9 8 . 8 12.8 1 75 . 0 (25.2) (9.0) (20.6) (11.5) (3.4) (5.1) (74. 8) 7 59. 1 27.0 66 . 8 51.3 11.7 19.2 235 . 1 (28.1) (7.4) (18.1) (12.7) (2.4) (5.6) (74. 3) 8 58.0 23 . 7 58.4 5 1.3 11.7 17.9 22 1. 0 (31.8) (9.4) (21.8) (21.8) (3.8) (7.9) (139. 3) 9 70 .1 33.8 83 . 5 66 . 7 11.7 23.0 288 . 8 (35.5) (8.8) (21.8) (18.2) (3.8) (8.7) (96. 8) 1 0 52.5 23 . 7 58.4 41.0 8 . 8 15.4 1 99 . 8 (27.9) (9.4) (21.8) (11.9) (3.4) (5.5) (79. 9) 1 1 72.2 33.8 83 . 5 61.6 14.6 21.8 287. 5 (33.7) (8.8) (21.8) (13.6) (3.0) (6.8) (87. 7) 1 2 - 73.3 33.8 83.5 61.6 14.6 21.8 288. 6 (38.4) (11.0) (26. 1 ) (22.4) (4.2) (8.5) (110. 6) 13 65 . 7 27.0 66 . 8 61 .6 11.7 20 . 5 253 . 3 (31.6) (7.4) (18.1) (13.6) (3.8) (6.5) (81 . 0) 1 4 56.9 23.7 58.4 51.3 11.7 17.9 219. 9 (30.2) (9.4) (21.8) (21.8) (3.8) (7.9) (94 . 9) 15 74.4 33.8 83 . 5 71 .8 14.6 24.3 302 . 4 (36.9) (11.0) (26. 1 ) (18.6) (4.2) (9.0) (105. 8) 16 67.9 30.4 75 . 1 61.6 11.7 20.5 267. 2 (31.7) (8.1) (19.9) (10.4) (2.4) (5.9) (78. 4) 1 7 61 .3 27.0 66.8 56.4 11.7 17.9 24 1 . 1(31.7) (9.9) (23.2) (17.5) (3.8) (6.0) (92 . 1 ) 18 85 . 4 37.2 91 .9 87.2 14.6 30 . 7 347 . 0 (31.0) (14.4) (33.4) (38. 1 ) (6.6) (17.3) (140. 8) CONTROL 1 47. 1 20.3 50.1 35.9 8 . 8 12.8 175. 0 (25.2) (9.0) (20.6) (11.5) (3.4) (5.1) (74 . 8) CONTROL 2 37.2 16.9 41.8 35.9 5.9 11.5 149. 2 (19.7) (5.5) (13.1) (11.5) (3.2) (4.9) (57. 9) CONTROL 3 59.1 23 . 7 58.4 66.7 11.7 23.0 242 . 6, (27.2) (5.5) (14.1) (11.0) (2.4) (6.5) (66. 7) Standard errors are given in parenthesis Pretreatment phosphorus content (kg/ha) of lodgepole pine components in the experimental plots. COMPONENT PLOT STEMWOOD STEMBARK NEEDLES L I VE DEAD ROOTS TOTAL BRANCHES BRANCHES • T REE 1 6.2 1 .9 4.5 2.7 0.3 0.3 15.9 (6.4) (1.0) (1.3) (0.8) (0.4) (0.3) (10.2) 2 7.8 2 . 2 6.8 4 . 7 0 . 2 0.7 22.4 (8.1) (1.1) (1.4) (1.1) (0.2) (0.2) (12.1) 3 10.5 3 . 0 9.0 6.7 0.2 0.9 30.3 (10.8) (1.5) (1 .6) (1.4) (0.3) (0.1) (15.7) 4 6.8 1 .9 5 . 7 3.4 0.2 0.6 18.6 (7.0) (0.9) (0.7) (0.6) (0.2) (0.1) (9.7) 5 7.6 2 . 2 6.8 4 . 7 0.2 0 . 7 22 . 2 (8.6) (1.3) (2.4) (2.8) (0.2) (0.4) (15.7) 6 8.4 2 . 2 6.8 4.7 0.2 0.7 23.0 (8.9) (1.3) (2.4) (1.6) (0.2) (0.2) (14.6) 7 10.5 3 . 0 9 . 0 6.7 0 . 2 1.1 30.5 (10.9) (1.5) (1.6) (1 .8) (0.3) (0.2) (16.3) 8 10.3 2.6 7.9 6.7 0 . 2 .1 . 0 28.7 (11.1) (1.5) (2.5) (2.9) (0.3) (0.4) (18.7) 9 12.5 3 . 7 11.3 8 . 7 0 . 2 1 . 3 37.7 (13.1) (1.8) (1.8) (2.5) (0.3) (0.4) (38.6) 1 0 9.3 2.6 7.9 5 . 4 0 . 2 0 . 8 26.2 (9.9) (1.5) (2.5) (1.6) (0.2) (0.2) (15.9) 1 1 12.8 3 . 7 11.3 8.0 0.3 1 . 2 37.3 (13.3) (1.8) (1.8) (2.0) (0.4) (0.3) (19.6) 1 2- 13.0 3.7 11.3 8.0 0.3 1 . 2 37.5 (13.0) (1.9) (2.7) (3.0) (0.4) (0.4) (21.4) 13 11.7 3.0 9.0 8.0 0 . 2 1 . 1 33.0 (12.1) (1.5) (1.6) (2.0) (0.3) (0.3) (17.8) 14 10.1 2.6 7.9 6.7 0 . 2 1 . 0 28.5 (10.8) (1.5) (2.5) (2.9) (0.3) (0.4) (18.4) 1 5 13.2 3 . 7 11.3 9.4 0 . 3 1 . 3 39.2 (13.8) (1.9) (2.7) (2.6) (0.4) (0.4) (21.8) 16 12.1 3 . 3 10.2 8.0 0 . 2 1 . 1 34.9 (12.5) (1.7) (1.7) (1-6) (0.3) (0.2) (18.0) 1 7 10.9 3.0 9.0 7.4 0 . 2 1 . 0 31.5 (11.5) (1.6) (2.5) (2.4) (0.3) (0.3) (18.6) 18 15.2 4 . 1 12.4 11.4 0.3 1 . 7 45 . 1 (16.4) (2.3) (3.7) (5.1) (0.4) (0.9) (28.8) CONTROL 1 8.4 2 . 2 6.8 4 . 7 0 . 2 0.7 23.0 (8.9) (1.3) (2.4) (1-6) (0.2) (0.2) (14.6) CONTROL 2 6.6 1 .9 5.7 4.7 0 . 1 0 . 6 19.6 (7.0) (1.0) (1.3) (1.6) (0.1) (0.2) (11.2) CONTROL 3 10.5 2.6 7.9 8.7 0 . 2 1 .3 31.2 (10.8) (1.3) (1.0) (1.7) (0.3) (0.2) (15.3) Standard errors are given in parenthesis Pretreatment potassium content (kg/ha) of lodgepole pine components in the experimental plots. COMPONENT PLOT STEMWOOD STEMBARK NEEDLES L I VE DEAD ROOTS TOTAL BRANCHES BRANCHES 'TREE 1 14.3 5.9 6.5 3 . 1 3 . 0 1 .6 34 . 4 (12.9) (3.0) (2.2) (1.3) (2.1) (2.3) (23. 8) 2 17.8 7. 1 9 . 8 5.4 1 . 8 4.0 45 . 9 (16.2) (3.5) (2.8) (2.0) (0.7) (4.3) (29. 5) 3 24 . 1 9.4 13.0 7.7 2.4 5 . 2 61 . 8 (21.7) (4.6) (3.4) (2.8) (0.9) (5.5) (38. 9) 4 15.6 5.9 8.2 3.9 1 .8 3 . 2 38. 6 (14.0) (2.8) (1 .9) (1.4) (0.7) (3.4) (24. 2) 5 17.4 7. 1 9.8 5.4 1 .8 4 . 0 45 . 5 (17.2) (4.1) (4.0) (3.6) (0.9) (4.7) (34. 5) 6 19.2 7. 1 9.8 5.4 1 .8 4 . 0 47. 3 (17.9) (4.1) (4.0) (2.4) (0.9) (4.4) (33 . 7) 7 24 . 1 9.4 13.0 7.7 2.4 6.0 62 . 6 (21.8) (4.6) (3.4) (3.1) (0.9) (6.4) (40. 2) 8 23.6 8.3 11.4 7.7 2.4 5.6 59. 0 (22.1) (4.5) (4.2) (4.1) (1.1) (6.2) (42. 2) 9 28.5 11.8 16.3 10.0 2 . 4 7.2 76 . 2 (26.2) (5.6) (4.1) (4.2) (1.1) (7.8) (49. 0) 1 0 21.4 8.3 11.4 6 . 2 1 .8 4.8 53 . 9 (19.9) (4.5) (4.2) (2.7) (0.9) (5.2) (37. 4) 1 1 29.4 11.8 16.3 9 . 2 3 . 0 6.8 76 . 5 (26.5) (5.6) (4.1) (3.6) (1.1) (7.2) (48. 1 ) 1 2 ' 29.9 11.8 16.3 9.2 3.0 6.8 77. 0 (27.6) (6.0) (5.0) (4.5) (1.3) (7.4) (51 . 8) 13 26.8 9.4 13.0 9.2 2 . 4 6.4 67. 2 (24.3) (4.6) (3.4) (3.6) (1.1) (6.8) (43. 8) 1 4 23 . 2 8.3 11.4 7.7 2 . 4 5 . 6 58 . 6 (21.5) (4.5) (4.2) (4.1 ) (1.1) (6.2) (41 . 6) 15 30.3 11.8 16.3 10.8 3.0 7.6 79. 8 (27.7) (6.0) (5.0) (4.4) (1.3) (8.2) (52. 1 ) 16 27.7 10.6 14.7 9.2 2.4 6.4 71 . 0 (24.9) (5.1) (3.8) (3.3) (0.9) (6.8) (44 . 8) 1 7 25.0 9 . 4 13.0 8.5 2 .4 5.6 63 . 9 (22.9) (5.0) (4.5) (3.8) (1.1) (6.0) (43 . 3 ) 18 34.8 13.0 17.9 13.1 3 . 0 9.6 91 . 4 (32.8) (7.0) (6.4) (7.1) (1.6) (11.2) (66 . 1 ) CONTROL 1 19.2 7. 1 9 . 8 5.4 1 . 8 4 . 0 47. 3 (17.9) (4.1) (4.0) (2.4) (0.9) (4.4) (33 . 7) CONTROL 2 15.2 5.9 8.2 5.4 1 . 2 3.6 39. 5 (14.1) (3.0) (2.5) (2.4) (0.7) (4.0) (26. 7) CONTROL 3 24 . 1 8.3 11.4 10.0 2.4 7.2 63 . 4. (21.6) (3.9) (2.7) (3.6) (0.9) (7.6) (40 . 3) Standard errors are given in parenthesis Pretreatment sodium content (kg/ha) of lodgepole pine components in the experimental plots. COMPONENT PLOT SIEMWOOD STEMBARK NEEDLES L I VE DEAD ROOTS TOTAL BRANCHES BRANCHES TREE 1 1 .0 0.3 0 . 5 0.3 0.2 0 . 2 2.5 (0.3) (0.1) (0.3) (0.1) (0.2) (0.2) (1.2) 2 1 .2 0.3 0.8 0.5 0 . 1 0 . 4 3 . 3 (0.4) (0.1 > (0.5) (0.2) (0.1) (0.3) (1.6) 3 1 .6 0.4 1 .0 0.7 0 . 2 0 . 5 4.4 (0.6) (0.1) (0.7) (0.3) (0.1) (0.4) (2.2) 4 1 . 1 0 . 3 0 . 7 0 . 4 0 . 1 0 . 3 2.9 (0.4) (0.1) (0.4) (0.2) (0.1) (0.2) (1.4) 5 1 .2 0.3 0.8 0 . 5 0 . 1 0.4 3.3 (0.7) (0.1) (0.5) (0.4) (0.1) (0.4) (2.2) 6 1 .3 0.3 0.8 0.5 0 . 1 0.4 3.4 (0.6) (0.1) (0.5) (0.3) (0.1) (0.3) (1.9) 7 1 . 6 0.4 1 . 0 0 . 7 0.2 0 . 6 4 . 5 (0.6) (0.1) (0.7) (0.3) (0.1 ) (0.5) (2.3) 8 1 . 6 0 . 4 0.9 0 . 7 0 . 2 0 . 6 4.4 (0.7) (0.1) (0.6) (0.4) (0.1) (0.5) (2.4) 9 1 .9 0 . 5 1 . 3 0.9 0 . 2 0 . 7 5 . 5 (0.8) (0.1) (0.8) (0.4) (0.1) (0.6) (2.8) 1 0 1 . 4 0 . 4 0 . 9 0.6 0 . 1 0 . 5 3.9 (0.6) (0.1) (0.6) (0.3) (0.1) (0.4) (2.1) 1 1 2 . 0 0.5 1 .3 0.8 0 . 2 0 . 7 5 . 5 (0.7) (0.1) (0.8) (0.4) (0.1) (0.5) (2.6) 1 2 - 2.0 0 . 5 1 .3 0 . 8 0.2 0.7 5 . 5 (0.8) (0.1) (0.8) (0.5) (0.1) (0.5) (2.8) 13 1 .8 0.4 1 . 0 0.8 0 . 2 0 . 6 4.8 (0.7) (0.1) (0.7) (0.4) (0.1) (0.5) (2.5) 14 1 . 6 0.4 0.9 0 . 7 0 . 2 0 . 6 4 . 4 (0.7) (0.1) (0.6) (0.4) (0.1) (0.5) (2.4) 1 5 2.0 0 . 5 1 .3 1 . 0 0.2 0 . 8 5.8 (0.8) (0.1) (0.8) (0.5) (0.1) (0.6) (2.9) 16 1 .9 0.5 1 .2 0.8 0 . 2 0.6 5 . 2 (0.6) (0.1) (0.7) (0.4) (0.1) (0.5) (2.4) 1 7 1 . 7 0 . 4 1 . 0 0.8 0 . 2 0 . 6 4 . 7 (0.7) (0.1) (0.7) (0.4) (0.1) (0.4) (2.4) 1 8 2.3 0.6 1 . 4 1 . 2 0.2 1 . 0 6.7 (1.1) (0.1) (1.0) (0.7) (0.1) (0.9) (3.9) CONTROL 1 1 .3 0.3 0.8 0 . 5 0. 1 0.4 3.4 (0.6) (0.1) (0.5) (0.3) (0.1) (0.3) (1.9) CONTROL 2 1 . 0 0.3 0.7 0 . 5 0. 1 0.4 3 . 0 (0.4) (0.1) (0.4) (0.3) (0.1) (0.3) (1.6) CONTROL 3 1 .6 0.4 0.9 0.9 0.2 0.7 4.7 (0.5) (0.1) (0.6) (0.4) (0.1) (0.5) (2.2) Standard errors are given in parenthesis Pretreatment magnesium content (kg/ha) of lodgepole pine components in the experimental plots. COMPONENT PLOT STEMWOOD STEMBARK NEEDLES LIVE DEAD ROOTS TOTAL BRANCHES BRANCHES TREE 1 7.7 3 . 9 7.0 2 . 0 3.6 1 . 5 25.7 (2.4) (1.4) (4.2) (1.2) (3.1) (2.0) (14.3) 2 9.6 4 . 7 10.6 3.6 2. 1 3.8 34 . 4 (3.1) (1.6) (5.9) (2.0) (1.3) (3.4) (17.3) 3 13.0 6.2 14.1 5 . 1 2.8 4.9 46 . 1 (4.0) (2.1) (7.7) (2.8) (1.8) (4.3) (22.7) 4 8.4 3.9 8.8 2.6 2 . 1 3 . 0 28 . 8 (2.5) (1.2) (4.7) (1.4) (1.3) (2.7) (13.8) 5 9 . 4 4 . 7 1 0 .6 3.6 2 . 1 3.8 34 . 2 (5.1) (2.1) (6.6) (2.8) (1.5) (3.8) (21.9) 6 10.3 4 . 7 10.6 3 . 6 2 . 1 3 . 8 35 . 1 (4.2) (2.1) (6.6) (2.2) (1.5) (3.5) (20.1) 7 13.0 6.2 14.1 5 . 1 2.8 5 . 7 46.9 (4.1) (2.1) (7.7) (3.0) (1.8) (5.0) (42.6) 8 12.7 5.5 12.3 5 . 1 2.8 5.3 43.7 (5.3) (2.3) (7.5) (3.5) (1.9) (5.0) (25.5) 9 15.4 7.8 17.6 6.6 2.8 6 . 8 57.0 (5.6) (2.5) (9.6) (3.9) (1.9) (6.2) (29.7) 1 0 11.5 5 . 5 12.3 4 . 1 2 . 1 4 . 6 40.1 (4.6) (2.3) (7.5) (2.5) (1.5) (4.1) (22.5) 1 1 15.9 7.8 17.6 6 . 1 3.6 6.5 57.5 (4.8) (2.5) (9.6) (3.5) (2.2) (5.7) (26.3) 1 2 * 16.1 7.8 17.6 6. 1 3.6 6 . 5 57.7 (6.2) (2.9) (10.0) (3.9) (2.3) (5.9) (31.2) 13 14.4 6 . 2 14.1 6 . 1 2 . 8 6 . 1 49 . 7 (4.7) (2.1) (7.7) (3.5) (1.9) (5.4) (25.3) 14 12.5 5 . 5 12.3 5 . 1 2.8 5.3 43 . 5 (5.0) (2.3) (7.5) (3.5) (1.9) (5.0) (25.2) 15 16.3 7.8 17.6 7. 1 3 . 6 7.2 59.6 (5.7) (2.9) (10.0) (4.2) (2.3) (6.6) (31.7) 16 14.9 7.0 15.8 6. 1 2.8 6 . 1 52.7 (4.6) (2.3) (8.6) (3.4) (1.8) (5.3) (26.0) 17 13.5 6 . 2 14.1 5.6 2 . 8 5 . 3 47.5 (4.9) (2.5) (8.3) (3.4) (1.9) (4.8) (25.8) 18 18.7 8.6 19.4 8 . 7 3.6 9. 1 68. 1 (8.1) (3.5) (11.6) (6.0) (2.6) (9.1) (40.5) CONTROL 1 10.3 4 . 7 10.6 3 . 6 2. 1 3.8 35.1 (4.2) (2.1) (6.6) (2.2) (1.5) (3.5) (20.1) CONTROL 2 8 . 2 3.9 8 . 8 3.6 1 .4 3.4 29.3 (3.2) (1.4) (5.0) (2.2) (1.1) (3.2) (16.1) CONTROL 3 13.0 5 . 5 12.3 6.6 2.8 6.8 4 7.0. (3.8) (1.7) (6.6) (3.7) (1.8) (6.0) (23.6) Standard errors are given in parenthesis Pretreatment calcium content (kg/ha) of lodgepole pine components in the experimental plots. COMPONENT PLOT STEMWOOD STEMBARK NEEDLES L I VE DEAD ROOTS TOTAL BRANCHES BRANCHES TREE 1 19.0 11.0 15.8 7.3 4.9 2.8 60 . 8 (6.6) (7.1) (7.5) (2.8) (0.8) (2.9) (27. 7) 2 23 . 7 13.3 23 . 7 12.8 2.9 7.0 83 . 4 (8.7) (8.3) (10.3) (4.2) (1.8) (2.1) (35 . 4) 3 32.0 17.7 31.6 18.3 3.9 9.1 112. 6 (11.2) (10.9) (13.3) (5.7) (2.4) (2.2) (45 . 7) 4 20.8 11.0 19.8 9 . 2 2.9 5.6 69. 3 (7.1) (6.7) (8.0) (2.7) (1.8) (1.5) (27. 8) 5 23 . 1 13.3 23 . 7 12.8 2.9 7.0 82 . 8 (13.2) (9.2) (12.4) (8.2) (0.4) (3.8) (47. 2) 6 25.5 13.3 23 . 7 12.8 2.9 7.0 85 . 2 (11.1) (9.2) (12.4) (5.3) (0.4) (2.6) (41 . 0) 7 32 . 0 17.7 31.6 18.3 3.9 10.5 114. 0 (11.6) (10.9) (13.3) (6.5) (2.4) (2.8) (47. 5) 8 31.4 15.5 27.7 18.3 3.9 9.8 1 06 . 6 (14.2) (10.4) (13.6) (9.1) (0.4) (4.2) (52. 9) 9 38.0 22.1 39 . 5 23 . 8 3 . 9 12.6 139. 9 (15.2) (13.6) (16.4) (8.9) (0.4) (4.5) ( 5 9 . 0) 1 0 28 . 5 15.5 27.7 14.6 2 . 9 8.4 97. 6 (12.3) (10.4) (13.6) (5.7) (0.4) (2.8) (45 . 2) 1 1 39. 1 22 . 1 39.5 22.0 4.9 11.9 139. 5 (13.7) (13.6) (16.4) (7.4) (3.0) (3.4) (57. 5) 12 - 39.7 22 . 1 39.5 22.0 4 . 9 11.9 140 . 1 (16.7) (14.1) (17.8) (9.8) (0.5) (4.4) (63. 3) 13 35.6 17.7 31.6 22 . 0 3.9 11.2 1 22 . 0 (13.1) (10.9) (13.3) (7.4) (0.4) (3.3) (48. 4) 1 4 30.8 15.5 27.7 18.3 3.9 9.8 1 06 . 0 (13.3) (10.4) (13.6) (9.1) (0.4) (4.2) (51 . 0) 1 5 40.3 22 . 1 39.5 25.6 4 . 9 13.3 145 . 7 (15.6) (14.1) (17.8) (9.3) (0.5) (4.6) (61 . 9) 1 6 36 . 8 19.9 35.6 22.0 3.9 11.2 129. 4 (12.9) (12.3) (14.8) (6.7) (2.4) (2.9) (52. 0) 1 7 33 . 2 17.7 31.6 20.1 3.9 9.8 116. 3 (13.3) (11.6) (15.0) (8.1) (0.4) (3.1) (51 . 5 ) 18 46.3 24.3 43.5 31.1 4.9 16.8 166. 9 (21.1) (16.2) (21.1) (15.8) (0.6) (9.2) (84 . 0) CONTROL 1 25 . 5 13.3 23 . 7 12.8 2.9 7.0 85 . 2 (11.1) (9.2) (12.4) (5.3) (0.4) (2.6) (41 . 0) CONTROL 2 20 . 2 11.0 19.8 12.8 2.0 6.3 72 . 1 (8.2) (7.1) (8.9) (5.3) (0.3) (2.5) (32. 3) CONTROL 3 32 . 0 15.5 27.7 23.8 3.9 12.6 1 1 5 . 5(10.9) (9.4) (11.1) (7.3) (2.4) (3.2) (44 . 3) Standard errors are given in parenthesis Pretreatment sulphur content (kg/ha) of lodgepole pine components in the experimental plots. COMPONENT PLOT STEMWOOD STEMBARK NEEDLES L I VE DEAD ROOTS TOTAL BRANCHES BRANCHES TREE 1 6.4 2.3 4 . 0 2.2 2.4 0 . 9 18. 2 (4.9) (1.5) (1.6) (0.8) (1.7) (1.2) (11. 7) 2 8 . 0 2 . 8 6. 1 3.9 0 . 7 2 . 3 23 . 8 (6.2) (1.8) (2.2) (1.1) (0.6) (2.0) ( 13 . 9) 3 10.8 3.7 8. 1 5.6 0.9 3 . 0 32 . 1 (8.2) (2.4) (2.8) (1.5) (0.8) (2.5) (18. 2) 4 7.0 2.3 5 . 1 2.8 0.7 1 . 8 1 9 . 7 (5.3) (1.5) (1.6) (0.7) (0.6) (1.5) (11. 2) 5 7.8 2.8 6. 1 3.9 0 . 7 2.3 23 . 6 (7.3) (1.9) (2.8) (2.4) (0.7) (2.2) (17. 3) 6 8.6 2.8 6. 1 3.9 0 . 7 2.3 24 . 4 (7.1) (1.9) (2.8) (1.5) (0.7) (2.0) (16. 0) 7 10.8 3.7 8. 1 5.6 0.9 3.4 32 . 5 (8.3) (2.4) (2.8) (1.8) (0.8) (2.9) (19. 0) 8 10.6 3.2 7.1 5.6 0 . 9 3 - 2 30. 6 (8.8) (2.2) (3.0) (2.6) (0.9) (2.9) ( 20 . 4) 9 12.8 4 . 6 10.1 7.3 0 . 9 4 . 1 39 . 8 (10.2) (2.9) (3.4) (2.5) (0.9) (3.6) (23. 5 ) 1 0 9.6 3 . 2 7. 1 4.5 0 . 7 2 . 8 27. 9 (7.8) (2.2) (3.0) (1.6) (0.7) (2.4) (17. 7) 1 1 13.2 4.6 10.1 6 . 7 1 .2 3.9 39 . 7 (10.0) (2.9) (3.4) (2.0) (1.0) (3.3) ( 22 . 6) 12 •-- 13.4 4.6 10.1 6.7 1 .2 3.9 39. 9 (10.8) (3.0) (3.8) (2.8) (1.1) (3.4) (24. 9) 1 3 12.0 3.7 8. 1 6.7 0.9 3 . 7 35 . 1 (9.3) (2.4) (2.8) (2.0) (0.9) (3.1) (20. 5) 14 10.4 3 . 2 7. 1 5.6 0.9 3 . 2 30 . 4 (8.5) (2.2) (3.0) (2.6) (0.9) (2.9) ( 20 . 1 ) 15 13.6 4 . 6 10.1 7.8 1 . 2 4 . 4 41 . 7 (10.7) (3.0) (3.8) (2.6) (0.1 ) (3.8) (24. 0) 1 6 12.4 4 . 1 9 . 1 6.7 0.9 3 . 7 36 . 9 (9.4) (2.6) (3.1) (1.8) (0.8) (3.1) ( 20 . 8) 1 7 11.2 3 . 7 8 . 1 6 . 2 0 . 9 3 . 2 33 . 3 (8.9) (2.5) (3.3) (2.3) (0.9) (2.7) (20. 6) 18 15.6 5 . 1 11.1 9.5 1 . 2 5 . 5 48 . 0 (13.1) (3.5) (4.6) (4.6) (1.4) (5.3) (32. 5) CONTROL 1 8.6 2.8 6. 1 3.9 0 . 7 2.3 24 . 4 (7.1) (1.9) (2.8) (1.5) (0.7) (2.0) (16. 0) CONTROL 2 6.8 2.3 5 . 1 3.9 0 . 5 2 . 1 20 . 7 (5.5) (1.5) (1.9) (1.5) (0.6) (1.8) (12. 8) CONTROL 3 10.8 3.2 7.1 7.3 0.9 4 . 1 33 . 4 (8.1) (2.0) (2.2) (1.9) (0.8) (3.5) (18. 5) Standard errors are given in parenthesis Pretreatment biomass and nutrient quantities (kg/ha) of lodgepole pine averaged over all the experimental plots. COMPONENT B I OMASS N P K Na Mg . Ca S STEMWOOD -mean 51000 57.4 10.2 23.4 1 .6 12.6 31.1 1 0 . 5 s.d. 1 6000 13.8 2 . 5 5.6 0.4 3 . 0 3 . 0 2 . 5 STEMBARK mean 8000 25.6 2.8 8.9 0.4 5.9 16.7 3 . 5 s.d. 2000 6.3 0.7 2.2 0. 1 1 .4 4 . 1 0 . 9 NEEDLES mean 6000 62.8 8.5 12.3 1 .0 13.2 29.7 7. 6 s.d. 1000 16.2 2 . 2 3.2 0 . 2 3.4 7.7 2 . 0 LIVE BRANCHES mean 1 0000 50.8 6 . 6 7.6 0.7 5 . 1 18.1 5 . 5 s.d. 3000 16.6 2 . 2 2 . 5 0.2 1 . 6 5.9 1 . 8DEAD BRANCHES mean 4000 11.3 0 . 2 3.3 0.2 2 . 7 3 . 8 1 . 0s.d. 1000 2 . 5 0 . 1 0.5 0 . 0 0 . 6 0.8 0 . 4 ROOTS mean 1 4000 17.5 1 . 0 5 . 5 0.6 5 . 2 9.6 3 . 2 s.d. 5000 5 . 8 0.3 1 . 8 0 . 2 1 . 7 3 . 2 1 . 0 TOTAL BIOMASS mean 94000 225 . 5 29.3 60 . 0 4.4 44 . 7 109.1 31 . 2 s.d. 24000 54.3 7.7 15.4 1 . 1 11.5 28 . 4 8. 1 Means are for 21 samples. APPENDIX 3-4 Pretreatment biomass and nutrient quantities understory vegetation in the experimental plots. 192 Pretreatment biomass and nutrient quantities (kg/ha) in shrubs in the experimental plots. P l o t Biomass N P K Na Mg Ca S 1 100 1 . 6 0 . 1 0 . 5 0.0 0 . 2 0 . 5 0 . 1 (100) ( 1 .6) (0.1) (0.5) (0.0) (0.2) -(0.5) (0.1) 2 200 3 .2 0.3 1 . 0 0.0 0 . 4 1 . 1 0 . 3 (200 ) (3 .3) (0.3) (1.1) (0.0) (0.4) (1.1) (0.3) 3 200 3 . 2 0.3 1 . 0 0 . 0 0.4 1 . 1 0 . 3 (100) ( 1 .7) (0.2) (0.6) (0.0) (0.2) (0.6) (0.2) 4 200 3 . 2 0.3 1 . 0 0 . 0 0 . 4 1 . 1 0.3 (100) ( 1 .7) (0.2) (0.6) (0.0) (0.2) (0.6) (0.2) 5 1 00 1 .6 0 . 1 0.5 0.0 0 . 2 0.5 0 . 1 (100) ( 1 .6) (0.1) (0.5) (0.0) (0.2) (0.5) (0.1) 6 100 1 . 6 0 . 1 0 . 5 0 . 0 0 . 2 0 . 5 0 . 1 (0) (0 .2) (0.0) (0.1) (0.6) (0.0) (0.1) ( 0 .'0 ) 7 1000 13 . 7 1 .8 4.4 0 . 1 2 . 0 5.3 1 .2 (1100) (15 .3) (2.0) (4.9) (0.1) (2-3) (5.9) (1-4) 8 600 8 . 2 1 . 1 2.7 0 . 1 1 . 2 3.2 0 . 7 (800 ) ( 1 1 . 1 ) (1.4) (3.6) (0.1) (1.7) (4.3) (1.0) 9 100 1 .4 0 . 2 0.4 0.0 0 . 2 0.5 0. 1 (100) ( 1 .4) (0.2) (0.4) (0.0) (0.2) (0.5) (0.1) 1 0 1000 1 .8 1 .8 4.4 0 . 1 2 . 0 5 . 3 1.2 ( 1 800 ) (24 .8) (3.2) (8.0) (0.2) (3.7) (9.6) (2.2) 1 1 700 9 . 6 1 . 3 3 . 1 0. 1 1 .4 3 . 7 0 . 9 (900 ) (12 .5) (1.6) (4.0) (0.1) (1.9) (4.8) (1.1) 12 100 1 .4 0 . 2 0.4 0.0 0 . 2 0 . 5 0 . 1 (0) (0 .3) (0.0) (0.1) (0.0) (0.1) (0.1) (0.0) 13 600 8 . 8 0 .7 2.5 0 . 0 0.8 2 . 1 0 . 6 ( 1 100) (16 .2) (1.4) (4.8) (0.1) (4.6) (3.9) (1.1) 1 4 300 4 . 4 0 . 4 1 . 3 0 . 0 0 . 4 1 . 0 0 . 3 (100) (1 .6) (0.2) (0.7) (0.0) (3.0) (0.5) (0.1) 1 5 100 1 . 5 0 . 1 0.4 0 . 0 0 . 1 0 . 3 0 . 1 (100) ( 1 .5) (0.1) (0.5) (0.0) (2.4) (0.4) (0.1) 16 2800 41 . 0 3.4 11.8 0 . 2 3.6 9.7 2 . 8 (3500) (51 .7) (4.4) (15.8) (0.3) (4.6) (12.5) (3.5) 17 1200 17 .6 1 . 5 5 . 1 0 . 1 1 . 5 4 . 2 1 . 2 ( 2300 ) (33 .9) (2.9) (10.0) (0.2) (3.0) (8.1) (2.3) 18 1300 19 . 0 1 . 6 5 . 5 0 . 1 1 . 7 4 . 5 1 . 3 (1800) (26 .6) (2.3) (8.0) (0.1) (2.4) (6.4) (1.8) CONTROL 1 500 8 . 1 0 . 7 2 . 6 0 . 0 1 . 0 2 . 7 0 . 7 ( 700 ) ( 1 1 .4) (1.0) (3.7) (0.1) (1.4) (3.8) (1.0) CONTROL 2 200 2 . 7 0 . 4 0.9 0 . 0 0 . 4 1 . 1 0 . 2 (100) ( 1 .5) (0.2) (0.5) (0.0) (0.2) (0.6) (0.1) CONTROL 3 200 2 . 9 0 . 2 0 . 8 0.0 0.3 0 . 7 0 . 2 ( 200) (3 .0) (0.3) (0.9) (0.0) (0.3) (0.7] (0.2) Standard errors are given in parenthesis. Shrub nutrient quantities were estimated from measurements of 5 samples per plot for mass, and their average nutrient concentrations from 6 composite samples per treatment block. 193 Pretreatment biomass and nutrient quantities (kg/ha) in mosses and lichens in the experimental plots. P l o t B i omass N P K Na Mg Ca S 1 4800 127 . 9 5 . 2 12.1 0 . 5 3.2 15.6 6.6 (1000) (30 .8) ( 1 .2) (4.0) (0.2) (1.4) (6.1) (1.5) 2 3700 98 .6 4 .0 9.4 0 . 4 2.5 12.0 5 . 1 ( 700 ) (22 . 1 ) (0 .8) (3.0) (0.2) (1.1) (4.6) (1.1) 3 3100 82 .6 3 . 4 7.8 0.3 2 . 1 10.1 4.3 (1100) (30 .9) ( 1 .2) (3.4) (0.2) (1.1) (4.9) (1.6) 4 2400 64 . 0 2 .6 6 . 1 0.3 1 .6 7.8 3.3 (400 ) (13 . 1 ) (0 .5) (1.8) (0.1) (0.7) (2.9) (0.6) 5 2600 69 .3 2 .8 6.6 0.3 1 . 7 8 . 5 3.6 (800 ) (22 .9) (0 .9) (2.6) (0.1) (0.9) (3.8) (1.2) 6 2500 66 . 6 2 .7 6.3 0.3 1 . 7 8.1 3 . 5 (1400) (38 .2) ( 1 .5) (3.9) (0.2) (1.1) (5.3) (2.0) 7 3000 62 . 5 3 .3 5.4 0.3 2 . 1 11.3 3 . 9 (1700) (36 .0) ( 1 .9) (3.4) (0.2) (1.5) (7.1) (2.3) 8 4200 87 . 5 4 .6 7.6 0.4 2.9 15.8 5 . 5 (2100) (44 .7) (2 .3) (4.4) (0.2) (1.9) (8.9) (2.8) 9 2500 52 . 1 2 . 8 4.5 0 . 2 1 . 8 9.4 , 3.3 ( 700 ) (15 .6) (0 .8) (1.8) (0.1) (0.9) (3.6) (1.0) 1 0 3800 79 .2 4 .2 6 . 8 0.3 2 . 7 1 4 . 3- 4.9 ( 2400 ) (50 .7) (2 .7) (4.8) (0.2) (2.0) (9.8) (3.2) 1 1 3000 62 . 5 3 .3 5.4 0.3 2 . 1 11.3 3.9 (2500) (52 .5) (2 .8) (4.8) (0.2) (2.0) (9.9) (3.3) 12 3400 70 .9 3 . 7 6 . 1 0 . 3 2.4 12.8 4 . 4 (1600) (34 .2) (1 .8) (3.4) (0.2) (1.5) (6.9) (2.2) 13 3400 80 .8 4 . 2 6.6 0.3 3 . 2 16.2 4.3 (1500) (36 .2) (1 .9) (3.3) (0.2) (1.5) (7.4) (1.9) 14 2400 57 . 0 3 . 0 4 . 6 0.2 2.3 11.4 3 . 0 ( 1 500 ) (36 .0) (1 .9) (3.1) (0.1) (1.5) (7.3) (1.9) 15 1800 42 .8 2 .2 3 . 5 0. 1 1 .7 8 . 6 2.3 (1100) (26 .4) ( 1 .4) (2.3) (0.1) (1.1) (5.3) (1.4) 16 1400 33 .3 1 . 7 2.7 0 . 1 1 . 3 6.7 1 . 8 (900 ) (21 .6) ( 1 . 1 ) (1.8) (0.1) (0.9) (4.4) (1.1) 1 7 3100 73 . 7 3 . 8 6 . 0 0 . 2 2 . 9 14.8 3 . 9 (2300) (55 -0) (2 .9) (4.7) (0.2) (2.2) (11.1) (2.9) 1 8 1500 35 .6 1 .9 2 . 9 0.1 1 . 4 7. 1 1 . 9 (1000) (24 .0) ( 1 .2) (2.0) (0.1) (1.0) (4.8) (1.3) CONTROL 1 4100 109 . 3 4 . 5 10.4 0 . 5 2 . 7 13.3 5 . 7 (3100) (83 .7) (3 .4) (8.3) (0.4) (2.3) (11.0) (4.3) CONTROL 2 3900 81 . 3 4 .3 7.0 0 . 4 2 . 7 14.6 5 . 1 (800 ) (18 .7) (0 .9) (2.5) (0.1) (1.3) (5.0) (1.2) CONTROL 3 2800 66 .5 3 .5 5.4 0.2 2.7 13.3 3.5 ( 1 900 ) (45 .5) (2 .4) (3.9) (0.2) (1 .8) (9.2) (2.4) Standard errors are given in parenthesis. Moss and lichen nutrient quantities were estimated from measurements of 5 samples per plot for mass, and their average nutrient concentrations from 6 composite samples per treatment block. 194 Pretreatment biomass and nutrient quantities (kg/ha) in herbs in the experimental plots. P l o t Biomass N P K Na Mg Ca S 1 200 1 . 9 0 . 3 0 . 8 0 . 0 0.5 3.8 0 . 2 (100) ( 1 .0) (0.2) ( 0 . 4) (0.0) (0.3) (2.5) (0.1) 2 100 1 . 0 0 . 2 0 . 4 0.0 0.3 1 . 9 0 . 1 (100) ( 1 . 0) (0.2) ( 0 . 4) (0.0) (0.3) (2.1) (0.1) 3 100 1 . 0 0 . 2 0 . 4 0 . 0 0.3 1 . 9 0 . 1 (100) ( 1 .0) (0.2) ( 0 . 4) (0.0) (0.3) (2.1) (0.1) 4 100 1 . 0 0 . 2 0 . 4 0 . 0 0 . 3 1 . 9 0 . 1 (100) ( 1 . 0 ) (0.2) ( 0 . 4 ) (0.0) (0.3) (2.1) (0.1) 5 100 1 . 0 0 . 2 0 . 4 0 . 0 0.3 1 . 9 0 . 1 (0) (0 . 1) (0.0) (0 . 0) (0.0) (0.1 ) (0.8) (0.0) 6 200 1 .9 0.3 0 . 8 0 . 0 0.5 3.8 0 . 2 (100) ( 1 .0) (0.2) ( 0 . 4) (0.0) (0.3) (2.5) (0.1) 7 100 0 . 8 0 . 1 0 . 4 0 . 0 0 . 2 2 . 0 0 . 1 (0) (0 . 1 ) (0.0) ( 0 . 0) (0.0) (0.0) (0.5) (0.0) 8 100 0 . 8 0 . 1 0 .4 0 . 0 0 . 2 2.0 0.1 (100) (0 .8) (0.1) ( 0 . 4) (0.0) (0.2) (2.1 ) (0.1) 9 200 1 . 6 0 . 3 0 . 7 0 . 0 0 . 5 4.0 0 . 2 (100) (0 .8) (0.2) ( 0 . 4) (0.0) (0.2) (2.2 X (0.1) 1 0 100 0 .8 0 . 1 0 .4 0 . 0 0 . 2 2.0 0 . 1 (100) ( o .8) (0.1) ( 0 . 4 ) (0.0) (0.2) (2.1) (0.1) 1 1 100 0 . 8 0 . 1 0 . 4 0 . 0 0 . 2 2 . 0 0 . 1 "(100) (0 .8) (0.1) ( 0 . 4) (0.0) (0.2) (2.1) (0.1) 1 2 200 1 . 6 0.3 0 . 7 0 . 0 0.5 4 . 0 0 . 2 (100) (0 .8) (0.2) ( 0 . 4) (0.0) (0.4) (2.2) (0.1) 13 200 2 . 1 0.3 0 . 7 0.0 0.4 4.2 0.3 (100) (1 . 1 ) (0.2) ( 0 . 7) (0.0) (0.4) (2.4) (0.1 ) 14 200 2 . 1 0.3 0 .7 0 . 0 0.4 4 . 2 0.3 (200 ) (2 . 1 ) (0.3) ( 0 . 7) (0.0) (0.2) (4.4) (0.3) 15 400 4 . 1 0.6 1 .5 0 . 1 0.8 8.5 0.5 ( 200 ) (2 . 1 ) (0.3) ( 0 . 7) (0.0) (0.4) (4.9) (0.3) 1 6 200 2 . 1 0 . 3 0 . 7 0 . 0 0 . 4 4 . 2 0 . 3 (100) ( 1 . 1 ) (0.2) ( 0 . 4) (0.0) (0.2) (2.4) (0.1) 1 7 200 2 . 1 0 . 3 0 . 7 0 . 0 0 . 4 4 . 2 0.3 (100) ( 1 . 1 ) (0.2) ( 0 . 4) (0.0) (0.2) (2.4) (0.1) 18 200 2 . 1 0 . 3 0 . 7 0 . 0 0.4 4 . 2 0.3 (100) ( 1 - 1 ) (0.2) ( 0 . 4) (0.0) (0.2) (2.4) (0.1) CONTROL 1 100 1 . 0 0 . 2 0 . 4 0 . 0 0 . 3 1 . 9 0 . 1 (100) ( 1 .0) (0.2) ( 0 . 4) (0.0) (0.3) (2.1) (0.1) CONTROL 2 200 1 . 6 0.3 0 .7 0 . 0 0 . 4 4 . 0 0.2 (100) (0 .8) (0.2) ( 0 . 4) (0.0) (0.2) (2.2) (0.1) CONTROL 3 200 2 . 1 0 . 3 0 . 7 0 . 0 0.5 4 . 2 0.3 ( 200 ) (2 . 1 ) (0.2) ( 0 . 7) (0.0) (0.4) (4.4) (0.3) Standard errors are given in parenthesis. Herb nutrient quantities were estimated from measurements of 5 samples per plot for mass, and their average nutrient concentrations from 6 composite samples per treatment block. Pretreatment biomass and nutrient quantities (kg/ha) in understory averaged over all the experimental plots. 195 Biomass Na Mg Ca SHRUBS mean s.d. 552 647 7.5 9.4 0.8 0.8 2.4 2.7 0 . 0 0.0 2.4 2.4 0 . 6 0 . 7 HERBS mean s.d. 167 73 1 .6 0.8 0.3 0 . 1 0.6 0.3 0 . 0 0.0 0.4 0 . 1 3 . 5 1 . 6 0.2 0 . 1 MOSSES AND LICHENS mean s.d. 3019 890 71 .6 22.8 3.4 0.9 6.3 2.3 0 . 3 0 . 1 2 . 3 0.6 11.6 3 . 0 4 . 0 1 . 2 TOTAL UNDERSTORY mean 3740 80.7 4.5 9.3 0.3 3.6 17.5 4.8 s.d. 1610 33.0 1.8 5.3 0.2 1.6 7.0 2.0 APPENDIX 3-5 Pretreatment biomass and nutrient quantities in forest floor and dead woody material in the experimental plots. 197 Pretreatment biomass and nutrient quantities (kg/ha) in the forest floors of the experimental plots. P l o t Biomass N P K Na Mg Ca S 1 39000 489 . 1 38 . 6 37 . 8 3 . 9 31 . 6 103.3 37.8 ( 7000 ) (87. 8) (6 .9) ( 6 . 8) ( 0 . 7) (5 . 7) (18.6) (6.8) 2 54000 677. 2 53 . 5 52 .4 5 . 4 43 . 7 143.1 52.4 (11000) (137. 9) (10 .9) (10. 7) ( 1 . 1 ) (8 . 9) (29.2) (10.7) 3 46000 576 . 8 45 .5 44, .6 ' 4 .6 37 .3 121.9 44.6 (12000) (150. 5) ( 1 1 .9) (11. 6) (1 . 2) ( 9 . 7) (31.8) (11.6) 4 31000 388 . 7 30 . 7 30 , . 1 3 . 1 25 . 1 82 . 2 30.1 (14000) (175. 6) (13 .9) (13. 6) (1 . 4) (11. 3) (37.1) (13.6) 5 42000 526. 7 41 .6 40 , . 7 4 . 2 34 . 0 111.3 40.7 (12000) (150. 5) (11 .9) (11. 6) ( 1 . 2) ( 9 . 7) (31.8) (11.6) 6 39000 489. 1 38 .6 37, . 8 3 .9 31 .6 103.4 37.8 (14000) (175. 6) (13 .9) (13. 6) ( 1 . 4) (11. 3) (37.1) (13.6) 7 63000 790 . 0 62 .4 61 . . 1 6 .3 5 1 . 0 167. 0 61.1 (30000 ) (376. 2) (29 .7) (29. 1 ) ( 3 . 0) (24. 3) (79.5) (29.1) 8 77000 965 . 6 76 . 2 74, . 7 7 .7 62 . 4 204 . 1 74.7 ( 53000 ) (664. 6) (52 .5) (51 . 4) ( 5 . 3) (42. 9) (140.5) (51.4) 9 45000 564 . 3 44 . 6 43 , . 7 4 . 5 36 . 5 119.3 ' 43.7 (32000) (401 . 3) (31 .7) (31 . 0) ( 3 . 2) (25 . 9) (84.8) (31.0) 1 0 31000 388. 7 30 .7 30 , . 1 3 . 1 25 . 1 8 2 . 2 30.1 (14000) ( 175 . 6) (13 .9) (13. 6) ( 1 . 4) (11. 3) (37.1) (13.6) 1 1 38000 476 . 5 37 .6 36. . 9 3 .8 30 . 8 100.7 36.9 (17000) (213. 2) (16 .8) (16. 5) ( 1 . 7) (13. 8) (45.1) (16.5) 12 34000 426 . 4 33 . 7 33. . 0 3 .4 27 . 5 90 . 1 33 . 0 (19000) ( 238. 3) (18 .8) (18. 4) ( 1 . 9) (15. 4) (50.4) (18.4) 13 41000 514. 1 40 . 6 39. .8 4 . 1 33 . 2 108.7 39.8 --- (26000) (326. 0) (25 .7) (25. 2) ( 2 . 6) (21 . 1 ) (68.9) (25.2) 14 43000 539. 2 42 . 6 41 . . 7 4 .3 34 .8 114.0 41.7 (31000) (388. 7) (30 .7) (30. 1 ) ( 3 . 1 ) (25 . 1 ) (82.2) (30.1) 1 5 73000 915. 4 72 .3 70 . 8 7 . 3 59 . 1 193.5 70 . 8 (35000) (438. 9) (34 .7) (34. 0) ( 3 . 5) ( 28 . 4) (92.8) (34.0) 16 37000 464 . 0 36 .6 35 , . 9 3 . 7 30 . 0 98 . 1 35.9 (35000 ) (326. 0) (34 .7) (34. 0) ( 3 . 5) (28. 4) (92.8) (34.0) 1 7 31000 388. 7 30 . 7 30. . 1 3 . 1 25 . 1 82 . 2 30 . 1 ( 26000 ) (326. 0) (25 .7) (25. 2) ( 2 . 6) (21 . 1 ) (68.9) (25.2) 18 62000 777. 5 61 . 4 60 . , 1 6 . 2 50 .2 164.3 60 . 1 (35000) (438. 9) (34 .7) (34. 0) ( 3 . 5) ( 28 . 4) (92.8) (34.0) CONTROL 1 57000 714 . 8 56 . 4 55 . 3 5 . 7 46 . 2 15 1.1 55 .3 (26000) (326 . 0) (25 .7) (25 . 2) (2 . 6) (21 . 1 ) (68.9) (25.2) CONTROL 2 59000 739. 9 . 58 . 4 57. 2 5 .9 47 . 8 156.4 57.2 (34000) (426. 43 (33 .7) (33. 0) ( 3 . 4) (27. 5) (90. 1 ) (33.0) CONTROL 3 56000 702 . 2 55 .4 54. 3 5 .6 45 .4 148.4 54.3 (26000) (326. 0) (25 .7) (25 . 2) (2 . 6) (21 . 1 ) (68.9) (25.2) Standard errors are given in parenthesis. Forest floor nutrient quantities were estimated from measurements of 16 samples per plot for mass, and their average nutrient concentrations from 4 composite samples per plot. 198 Pretreatment biomass and nutrient quantities (kg/ha) in < 1 cm diameter dead woody materials in the experimental plots. P l o t Biomass N P K Na Mg Ca S (kg/ha) 1 2000 6.6 0 .3 0 . 5 0 . 1 0 . 4 2.7 - 1 . 2 (4.0) (0 .2) (0.4) (0.1) (0.2) (1.4) (0 .7) 2 0 0.0 0 . 0 0.0 0.0 0 . 0 0 . 0 0 . 0 (0.0) (0 .0) (0.0) (0.0) (0.0) (0.0) (0 .0) 3 2000 6 . 6 0 .3 0.5 0 . 1 0 . 4 2 . 7 1 . 2 (7.0) (0 .3) (0.6) (0.1) (0.4) (2.8) (1 .2) 4 3000 10.0 0 . 4 0 . 8 0.2 0.6 4 . 1 1 . 8 (10.5) (0 .5) (0.8) (0.2) (0.6) (4.1) (1 .9) 5 1000 3.3 0 . 1 0.3 0 . 1 0 . 2 1 .4 0 .6 (1.1) (0 . 1 ) (0.1) (0.0) (0.0) (0.3) (0 .2) 6 1 000 3.3 0 . 1 0.3 0 . 1 0 . 2 1 . 4 0 .6 (3.5) (0 .2) (0.3) (0.1) (0.2) (1.4) (0 .6) 7 1000 7.7 0 . 2 0 . 2 0 . 0 0 . 2 1 . 8 0 . 6 (8.4) (0 -2) (0.3) (0.0) (0.2) (2.0) (0 .6) 8 0 0.0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 (0.0) (0 .0) (0.0) (0.0) (0.0) (0.0) (0 .0) 9 1000 7.7 0 .2 0 . 2 0 . 0 0 . 2 1.8 0 .6 (3.4) (0 . 1 ) (0.1) (0.0) (0.1) (0.9) (0 .2) 1 0 0 0 . 0 0 . 0 0.0 0.0 0 . 0 0 . 0 0 . 0 (0.0) (0 .0) (0.0) (0.0) (0.0) (0.0) (0 .0) 1 1 1000 7.7 0 . 2 0 . 2 0 . 0 0 . 2 1 . 8 0 . 6 (8.4) (0 .2) (0.2) (0.0) (0.2) (2.0) (0 .6) 1 2 1 000 7.7 0 . 2 0 . 2 0 . 0 0 . 2 1 . 8 0 . 6 (3.4) (0 . 1 ) (0.1) (0.0) (0.1) (0.9) (0 .2) 13 - 1000 10.7 0 .3 0.3 0.0 0.3 1 . 9 0 . 7 (5.1) (0 . 1 ) (0.1) (0.0) (0.1) (0.4) (0 . 1 ) 14 1 000 10.7 0 .3 0.3 0.0 0 . 3 1.9 0 . 7 (11.8) (0 .3) (0.3) (0.0) (0.4) (1.9) (0 .7) 1 5 0 0 . 0 0 . 0 0.3 0 . 0 0 . 0 0 . 0 0 . 7 (0.0) (0 .0) (0.3) (0.0) (0.0) (0.0) (0 .7) 16 1 000 10.7 0 .3 0.3 0 . 0 0 . 3 1 . 9 0 . 7 (11.8) (0 .3) (0.3) (0.0) (0.4) (1.9) (0 .7) 1 7 1 000 10.7 0 .3 0.3 0 . 0 0 . 3 1 . 9 0 . 7 (11.8) (0 .3) (0.3) (0.0) (0.4) (1.9) (0 .7) 1 8 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 (0.0) (0 . 0) (0.0) (0.0) (0.0) (0.0) (0 . 0 ) CONTROL 2 0 0 . 0 0 . 0 0 . 3 0 . 1 0 . 2 1 . 4 0 . 6 (0.0) (0 .0) (0.3) (0.1) (0.2) (1.4) (0 .6) CONTROL 3 1000 10.7 0 .3 0.3 0 . 0 0.3 1 . 9 0 . 7 (11.8) (0 .3) (0.3) (0.0) (0.4) (1.9) (0 .6) Note 1. Control plot No. l was mistakenly spaced and was not measured before treatment. 2. Standard errors are given in parenthesis. 3. < 1 cm woody material nutrient quantities were estimated from measurements of 5 samples per plot for mass, and their average nutrient concentrations from 6 composite samples per treatment block. 199 Pretreatment biomass and nutrient quantities (kg/ha) in 1-7 cm diameter dead woody materials in the experimental plots. P l o t Biomass N P K Na Mg Ca S (kg/ha) 1 1 3400 10.4 0 .05 1 . 2 0.2 1 . 6 - 8.9 1 . 5 (3.4) (0.01 ) (0.8) (0.1 ) (1.0) (1.8) (1.4) 2 22500 18.0 0.19 2.2 0.3 2.8 15.1 3 . 0 (5.7) (0.06) (1.5) (0.3) (1.7) (3.2) (3.0) 3 21 700 17.4 0.14 2 . 1 0.3 2 . 7 14.6 2.8 (5.6) (0.05) (1.4) (0.3) (1.7) (3.1) (2.8) 4 6900 5.8 0.01 0 . 7 0 . 1 0 . 9 4 . 7 0 . 9 (1.9) (0.00) (0.5) (0.1) (0.6) (1.1) (0.9) 5 5400 4 . 7 0.01 0.6 0 . 1 0 . 7 3 . 8 0 . 7 (1.6) (0.00) (0.4) (0.1) (0.5) (0.9) (0.7) 6 1 0600 9.2 0 . 03 1 . 2 0 . 2 1 .4 7.4 1 . 5 (3.1) (0.01 ) (0.8) (0.2) (0.9) (1.7) (1.5) 7 16700 13.4 0 . 08 1 .7 0 . 2 2.1 11.3 2 . 3 (4.3) (0.03) (1.1) (0.2) (1.3) (2.4) (2.3) 8 1 5300 12.5 0.07 1 .6 0.2 1 .9 10.4 2 . 2 (4.0) (0.03) (1.1) (0.3) (1.2) (2.3) (2.-2) 9 6800 5.5 0.01 0.7 0 . 1 0 . 9 4.6 , 0 . 9 (1.8) (0.00) (0.4) (0.1) (0.5) (1.0 ) (0.9) 1 0 1 3500 11.0 0 .05 1 . 4 0 . 2 1 . 7 9.1 1 . 8 (3.5) (0.02) (0.9) (0.2) (1.1) (2.0) (1.8) 1 1 9000 7.7 0 . 02 1 . 0 0 . 2 1 . 2 6 . 2 1 . 4 (2.5) (0.01 ) (0.7) (0.2) (0.8) (1.4) (1.4) 1 2 3900 3.2 0.00 0 . 4 0 . 1 0 . 5 2 . 6 0 . 5 (1-0) (0.00) (0.2) (0.1) (0.3) (0.6) (0.5) 1 3 _ 6500 5 . 2 0 . 01 0 . 6 0. 1 0 . 8 4 . 4 0 . 9 (1.7) (0.00) (0.4) (0.1) (0.5) (0.9) (0.9) 14 5400 4.4 0.01 0.5 0.1 0 . 7 3.7 0 . 8 (1.4) (0.00) (0.3) (0.1) (0.4) (0.8) (0.8) 15 6200 4.9 0.01 0.6 0 . 1 0.8 4.2 0 . 8 (1.6) (0.00) (0.4) (0.1) (0.5) (0.9) (0.8) 1 6 4900 4 . 0 0.01 0.5 0. 1 0.6 3.3 0 . 7 (1.3) (0.00) (0.3) (0.1) (0.4) (0.7) (0.8) 1 7 3300 2.8 0.01 0 . 4 0 . 1 0 . 4 2 . 3 0 . 6 (0.9) (0.00) (0.2) 0.1) (0.3) (0.5) (0.6) 1 8 7400 6 . 5 0.07 0 . 9 0 . 1 1 . 0 5 - 2 1 . 3 (2.1) (0.03) (0.6) (0.2) (0.7) (0.2) (1.3) CONTROL 2 7930 6.3 0 . 03 0.8 0 . 1 1 . 0 5.3 1 . 0 (2.0) (0.01 ) (0.5) (0.1) (0.6) (1.1) (1.0) CONTROL 3 8206 6 . 4 0 .02 0 . 8 0 . 1 1 . 0 5.3 1 . 0 (2.1) (0.01 ) (0.5) (0.1) (0.6) (1.1) (1.0) Note 1. Control plot No. l was mistakenly spaced and was not measured before treatment. 2. Standard errors are given in parenthesis. 3. 1-7 cm woody material nutrient quantities were estimated from measurements of mass of these materials (from the line intersect), and their average nutrient concentrations from 18 samples for each size class. 200 Pretreatment biomass and nutrient quantities (kg/ha) in > 7 cm diameter dead woody materials in the experimental plots. P l o t Biomass N P K Na Hg Ca S (kg/ha ) 1 156900 85 . 6 3 . 8 9 . 7 2 . 1 21.4 -115.2 11.0 (20 .0) ( 1 .6) (7 .5) (1.6) (14.0) (29.5) (11.0) 2 95100 53 . 9 2 .3 7 .9 1 . 6 12.7 77.9 6 . 7 (12 .7) (0 .9) (5 .4) (1.0) (7.6) (17.4) (6.7) 3 127500 71 . 1 3 .2 9 . 7 2 . 0 17.2 101.5 8.9 (16 .7) ( 1 .5) (7 .2) (1.3) (10.7) (26.0) (8.9) 4 235700 125 . 1 5 .3 12 .0 2 . 7 32.6 164.4 16.5 (29 .0) (2 .8) (10 .7) (2.4) (22.5) (47.8) (16.5) 5 197100 103 . 8 4 . 1 9 .4 2.2 27.4 135.3 13.8 (24 .0) (2 .0) (8 .4) (2.0) (19.1 ) (37.5) (13.8) 6 181400 96 . 4 3 .8 9 .7 2. 1 25.1 128.5 12.7 (22 .4) ( 1 .9) (8 .5) (1 -8) (17.2) (35.8) (12.7) 7 138100 76 . 1 3 .3 9 .3 2 .0 18.7 104.2 9.7 (17 .8) ( 1 .4) (7 .0) (1.4) (12.0) (26.9) (9.7) 8 135100 74 . 5 3 . 1 8 .8 2 . 0 18.3 99 . 6 9 . 5 (17 .4) ( 1 .2) (6 .5) (1.4) (11.7) (24.3) (9/5) 9 - 159300 85 , .3 3 . 6 8 .3 1 . 9 22.0 111.5 11.2 (19 .8) ( 1 .6) (7 .0) (1.6) (14.9) ( 3 8 . 2 )x (11.2) 1 0 168500 91 . 1 3 . 7 9 . 6 2.2 23 . 1 120.3 11.8 (21 .2) ( 1 .6) (7 .7) (1.7) (15.4) (31.0) (11.8) 1 1 189100 100, .9 4 . 2 9 .9 2.3 26 . 1 132.8 13.2 (23 .4) (2 .0) (8 .5) (1.9) (17.8) (37.2) (13.2) 1 2 165800 87, . 6 3 .6 7 .8 1 . 9 23 . 0 113.8 11.6 (20 .3) ( 1 .7) (7 .0) (1.7) (16.0) (31.9) (11.6) 13.- 166800 88 , . 4 3 . 7 8 .3 1 . 9 23 . 1 116.4 11.7 (20 .5) ( 1 .7) (7 .3) (1.7) (16.0) (31.6) (11.7) 14 206600 1 09 , . 7 4 . 6 10 . 1 2 . 4 28 . 6 142.0 14.5 (25 .5) (2 .3) (9 .0) (2.1) (19.7) (40.0) (14.5) 1 5 172000 91 , . 1 3 .6 8 .5 2.0 23.8 117.7 12.0 (21 . 1 ) (2 .0) (7 .6) (1.7) (16.5) (34. 1 ) (12.0) 16 129800 69, . 2 3 . 0 6 . 7 1 . 5 17.9 90.9 9.1 (16 . 1 ) ( 1 .6) (5 .9) (1.3) (12.3) (25.8) (9.1) 1 7 68700 36, .3 1 . 7 3 . 7 0 . 8 9.5 49 . 5 4 . 8 (8 .4) (1 .0) (3 • 3) (0.7) (6.6) (15.0) (4.8) 18 30600 16, .2 0 .6 2 . 3 0.4 4 . 2 25 . 4 2 . 1 (3 .8) (0 -2) ( 1 .8) (0.3) (2.9) (5.7) (2.1) CONTROL 2 103866 57 . 0 2 .3 6 . 5 1 . 5 14.1 75 .3 7.3 (13 .3) ( 1 .2) (5 .0) (1.0) (9.1) (19.7) (7.9) CONTROL 3 1 14247 61 . 4 2 . 7 6 . 5 1 . 4 15.7 82 . 6 8 . 0 (14 .3) ( 1 .4) (5 .4) (1.1) (10.6) (23.0) (8.0) Note 1. Control plot No. l was mistakenly spaced and was not measured before treatment. 2. Standard errors are given in parenthesis. 3. > 7 cm woody material nutrient quantities were estimated from measurements of mass of these materials (from the line intersect), and their average nutrient concentrations from 18 samples for each size class. 201 Pretreatment biomass and nutrient quantities (kg/ha) of all dead woody materials in the experimental plots. P l o t Biomass N P K Na Mg Ca S (kg/ha ) 1 172300 102 . 6 3 . 8 9. 7 2.4 23.4 '115.2 13.1 (27 .4) (1 .6) ( 7 . 5) (1.9) (15.2) (29.5) (13.1) 2 117600 71 .9 2 .3 7. 9 1 .9 15.5 77.9 9 . 7 (18 .4) (0 .9) ( 5 . 4) (1.3) (9.3) (17.4) (9.7) 3 15 1200 95 . 1 3 . 2 9. 7 2 . 4 20.3 101.5 12.9 (29 -3) ( 1 .5) ( 7 . 2) (1.7) (12.8) (26.0) (12.9) 4 245600 140 . 9 5 .3 1 2 . 0 3.0 34 . 1 164.4 19.2 (41 .4) (2 .8) (10. 7) (2.8) (23.7) (47.8) (19.3) 5 203500 111 . 8 4 . 1 9. 4 2.4 28.3 135.3 15.1 (26 .7) (2 .0) ( 8 . 4) (2.1 ) (19.6) (37.5) (14.7) 6 193000 108 . 9 3 .8 9 . 7 2.4 26.7 128.5 14.8 (29 . 0) ( 1 .9) ( 8 . 5) (2.2) (18.3) (35.8) (14.7) 7 155800 97 . 2 3 .3 9. 3 2 . 2 21.0 104.2 12.6 (30 .5) ( 1 .4) ( 7 . 0) (1.7) (13.5) (26.9) (12.6) 8 150400 87 . 0 3 . 1 8 . 8 2 . 2 20.2 99 . 6 11.7 (21 .4) ( 1 .2) ( 6 . 5) (1.7) (12.9) (24.3) (11.7) 9 167100 98 , . 5 3 . 6 8. 3 2 . 0 23 . 1 111. 5. -12.7 (25 .0) ( 1 .6) ( 7 . 0) (1.7) (15.5) (38.2) (12.3) 1 0 182000 102 . 1 3 . 7 9 . 6 2.4 24 . 8 120.3 13.6 (24 .7) ( 1 .6) ( 7 . 7) (1.9) (16.5) (31.0) (12.7) 1 1 199100 116 .3 4 . 2 9 . 9 2.4 27.5 132.8 15.2 (34 .3) (2 .0) ( 8 . 5) (2.1) (18.8) (37.2) (15.2) 1 2 170700 98 , . 5 3 .6 7. 8 2 . 0 23 . 7 113.8 12.7 (24 .7) ( 1 .7) ( 7 . 0) (1.8) (16.4) (31.9) (12.3) 1 3 174300 1 04 , .3 3 . 7 8 . 3 2 . 0 24.2 116.4 13.3 (27 .3) (1 .7) ( 7 . 3) (1.8) (16.6) (31.6) (12.7) 14 213000 1 24 . 8 4 .6 10. 1 2.5 29.6 142.0 16.0 (38 .7) (2 .3) ( 9 . 0) (2.2) (20.5) (40.0) (16.0) 1 5 178200 96 , . 0 3 .6 8. 5 2 . 1 24.6 117.7 13.5 (34 .5) (2 -0) ( 7 . 6) (1.8) (37.9) (34. 1 ) (13.5) 16 135700 83 . 9 3 . 0 6 . 7 1 .6 18.8 90.9 10.5 (29 .2) ( 1 .6) ( 5 . 9) (1.4) (13.1) (25.8) (10.6) 1 7 73000 49, • 8 1 . 7 3 . 7 0.9 10.2 49.5 6. 1 (21 . 1 ) (1 .0) ( 3 . 3) (0.8) (7.3) (15.0) (6.1) 18 38000 22 .7 0 . 6 2 . 3 0.5 5 . 2 25 . 4 3 . 4 (5 .9) (0 .2) (1 . 8) (0.5) (3.6) (5.7) (3.4) CONTROL 2 111796 63 .3 2 .3 6. 5 1 .7 15.3 75 .3 8.9 (18 .8) ( 1 .2) (5 . 0) (1.2) (9.9) (19.7) (9.5) CONTROL 3 123453 78 .5 2 . 7 6 . 5 1 . 5 17.0 82.6 9 . 7 (28 .2) ( 1 .4) (5 . 4) (1.2) (11.6) (23.0) (9.6) Note 1. Control plot No. l was mistakenly spaced and was not measured before treatment. 2. Standard errors are given in parenthesis. 202 Pretreatment biomass and nutrient quantities (kg/ha) in dead woody materials averaged over all experimental plots. Biomass N P K Na Mg Ca S SIZE CLASS (cm) < 1 mean 850 6.4 0.2 0.3 0.0 0.2 1.6 0.6 s.d. 813 4.1 0.1 0.2 0.1 0.2 1.0 0.4 1-7 mean 9800 8.0 0.0 1.0 0.1 1.2 6.6 1.3 s.d. 5773 4.5 0.1 0.0 0.1 0.7 3.8 0.7 > 7cm mean 147200 79.9 3.1 7.0 1.9 20.2 97.1 10.3 s.d. 48727 25.5 1.0 2.1 0.5 6.8 32.2 3.4 TOTAL mean 157700 93.4 3.3 8.2 2.0 21.7 105.3 12.2 s.d. 48381 26.5 1.0 2.2 0.6 6.8 32.2 3.5 APPENDIX 3-6 Postburn biomass and nutrient quantities in forest floor and dead woody materials in the experimental plots. 204 Postburn biomass and nutrient quantities (kg/ha) in forest floors in the experimental plots by treatment. Treatment Biomass N P K Na Mg Ca S / p l o t BROADCAST BURNS Low s e v e r i t y burns in f r e s h s l a s h P l o t 2 38000 283 . 5 35 . 3 42 .2 5 . 3 37 . 6 1 1 7 . 0 18.6 (71.1) ( 9 . 4) (9 .7) (1 - 3) (1 1 . 6) (29. 4) (9.9) P l o t 17 21000 156.7 19. 5 23 .3 2 . 9 20 . 8 64 . 7 10.3 (137.9) (17. 3) (20 .4) ( 2 . 6) (18. 7) (57. 0) (10.3) Low s e v e r i t y burns in cured s l a s h P l o t 1 26000 191.6 29. 6 51 . 2 3 .6 34 .3 59 . 8 17.9 (45.8) ( 7 . 2) ( 1 1 .0) ( 0 . 8) ( 14 . 8) ( 29 . 8) (4.3) P l o t 4 18000 132.7 20 . 5 35 .5 2 .5 23 . 8 41 .4 12.4 (64.2) (10. 0) (16 .8) ( 1 . 2) (14. 3) (27. 0) (6.0) Moderate s e v e r i t y burns P l o t 8 52000 401 .4 48. 4 73 .8 1 5 . 1 60 .8 1 83 . 6 25 . 0 (289.0) (47. 7) (51 .9) (10. 5) (47. 3) (154. 1 ) (20.5) P l o t 11 24000 185 .3 22. 3 34 . 1 7 . 0 28 . 1 84 . 7 1 1.. 5 (91.8) (15. 3) (16 .0) ( 3 . 2) (16. 2) (55 . 7) (7.3) High s e v e r i t y burns -P l o t 9 31000 237.8 36. 3 57 .4 9 . 0 37 . 2 158 . 7 20.2 (154.5) (24. 0) (42 .6) (5 . 9) (27. 5) ( 105 . 0) (13.4) P l o t 13 23000 176.4 26. 9 42 .6 6 . 7 27 .6 1 1 7 . 8 15.0 (118.7) (18. 4) (32 .5 ) ( 4 . 5) (21 . 0) (80 . 6) (10.3) P l o t 14 25000 191.8 29. 3 46 .3 7 .3 30 . 0 1 28 . 0 16.3 (143.8) ( 22 . 2) (38 .4) (5 . 5) (24. 9) (97. 2) (12.4) WINDROW BURNS Low s e v e r i t y burns in f r e s h s l a s h P l o t 7 7000 86.5 11 . 2 9 .7 0 .7 6 . 5 24 .3 6.8 (10.3) ( 0 . 9) (3 .9) ( 0 . 0) ( 3 . 2) ( 8 . 3) (1.6) Low s e v e r i t y burns in cured s l a s h P l o t 3 1000 15.8 1 . 2 1 . 1 0 . 1 0 . 8 2 . 5 1 .0 (6.5) ( 0 . 1 ) (0 .3) ( 0 . 0) ( 0 . 2) ( 0 . 4) (0.2) P l o t 5 5000 71 . 7 5 . 4 5 . 1 0 . 3 4 . 0 9 . 1 4 . 9 (11.9) ( 0 . 7) (0 .9) ( 0 . 2) ( 1 . 5) ( 1 . 5) (1.2) Moderate s e v e r i t y burns P I ot 12 0 0.0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 (0.0) ( 0 . 0) (0 .0) (0 . 0) ( 0 . 0) ( 0 . 0) (0.0) PIot 16 0 0 . 0 0. 0 0 . 0 0 . 0 0 . 0 0 . 0 0.0 (0.0) ( 0 . 0) (0 .0) ( 0 . 0) ( 0 . 0) ( 0 . 0) (0.0) High s e v e r i t y burns P l o t 15 2 0 00 21.3 2. 0 1 .9 0 .3 2 . 1 7 .3 1 .9 (4.6) ( 0 . 4) (0 .4) ( 0 . 1 ) ( 1 . 1) (1 . 5) (0.5) P l o t 18 1000 13.2 0 . 8 0 . 7 0 . 1 1 . 0 3 . 9 1 . 0 (2.5) ( 0 . 3) (0 . 1 ) ( 0 . 1 ) ( 0 . 1) ( 0 . 4) - (0.2) Standard errors are given in parenthesis. 205 Postburn biomass and nutrient quantities (kg/ha) in forest floors averaged for treatments. T reatment Biomass N P K Na Mg Ca S Low sever i ty burns in f r e s h s l a s h b r o a d c a s t 29500 220 . 1 27 . 4 32 . 8 4 . 1 29 . 2 90 . 9 14 . 5 (104. 5) (13 .4) (15 . 1 ) (2 .0) ( 15 . 2) (43. 2) ( 1 0 . 1 ) windrow 7000 86. 5 1 1 . 2 9 . 7 0 . 7 6 . 5 24 . 3 6 . 8 (10. 3) (0 .9) (3 .9) (0 .0) ( 3 . 2) ( 8 . 3) ( 1 .6) Low s e v e r i t y burns i n cured s l a s h b r o a d c a s t 22000 162. 1 25 . 1 43 .4 3 . 1 29. 1 50 . 6 1 5 . 1 (55 . 0) (8 .6) (13 .9) (1 .0) (14. 6) (28. 4) (10 .3) windrow 3000 43 . 8 3 .3 3 . 1 0 . 2 2 . 4 5 . 8 3 . 0 ( 9 . 2) (0 .4) (0 .6) (0 . 1 ) ( 0 . 9) ( 1 . 0) (0 .7) Moderate s e v e r i t y burns b r o a d c a s t 38000 293 . 4 35 . 4 54 . 0 1 1 . 1 44 . 5 134 . 2 1 8 . 3 (190. 4) (31 .5) (34 .0) (6 .9) (31 . 8)( 1 04 . 9) (13 .9) windrow 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 0 . 0 ( 0 . 0) (0 .0) (0 .0) (0 .0) ( 0 . 0) ( 0 . 0) (0 .0) High s e v e r i t y burns b r o a d c a s t 26333 202 . 0 30 . 8 48 . 8 7 . 7 31 . 6 134 . 8 1 7 . 2 (139. 0) (21 .5) (37 .8) (5 .3) (24. 5 ) (94 . 3) (12 .0) windrow 1500 17. 3 1 . 4 1 . 3 0 . 2 1 . 6 5 . 6 1 . 5 ( 3 . 6) (0 .4) (0 .3) (0 - 1 ) ( 0 . 6) ( 1 . 0) (0 .4) For the moderate severity burn in windrows no forest floor was present postburn. Standard errors are given in parenthesis. Forest floor nutrient quantities were estimated from measurements of forest floor mass, 16 samples per treatment and their average nutrient concentrations from 4 composite samples per plot. 206 Postburn biomass and nutrient quantities (kg/ha) in < 1 cm dead woody materials in the experimental plots. Treatment Biomass N P K Na Mg Ca S Low s e v e r i t y burns in f r e s h s l a s h P l o t 2 Broadcast 140 0.4 0 . 0 0. 2 0 . 0 0 . 1 0 . 6 0 . 0 (0.7) ( 0 . 0) ( 0 . 2) ( 0 . 0) (0.2) ( 1 . 0) (0.0) P l o t 17 Broadcast 1 70 0.5 0 . 1 0 . 3 0 . 0 0 . 1 0 . 7 0 . 0 (0.8) ( 0 . 1) ( 0 . 2) ( 0 . 0) (0.2) ( 1 . 1 ) (0.0) P l o t 7 Windrow 81 0.9 0 . 1 0. 5 0 .0 0.2 1 .3 0.0 (1.5) ( 0 . 2) ( 0 . 3) ( 0 . 0) (0.3) ( 2 . 0) (0.0) P l o t 10 Windrow 1 03 1 .4 0 . 1 0 . 8 0 . 1 0.3 2 . 0 0 . 0 (2.3) ( 0 . 3) ( 0 . 5) ( 0 . 0) (0.4) ( 3 . 1 ) (0.0) Low s e v e r i t y burns in cured s l a s h P l o t 1 Broadcast 20 0.1 0. 0 0 . 0 0 . 0 0 . 0 0 . 1 0.0 (0.0) ( 0 . 0) ( 0 . 0) ( 0 . 0) (0.0) ( 0 . 1 ) (0.0) P l o t 4 Broadcast 20 0 . 1 0 . 0 0. 0 0 . 0 0 . 0 0 . 1 0 . 0 (0.0) ( 0 . 0) ( 0 . 0) ( 0 . 0) (0.0) ( 0 . 1 ) (0.0) P l o t 3 Windrow 156 0.2 0 . 0 0 . 1 0 . 0 0 . 0 0 . 1 0 . 0 (0.2) ( 0 . 0) (0 . 1) ( 0 . 0) (0.0) ( 0 . 3 1 (0.0) P l o t 5 Windrow 239 0 . 1 0 . 0 0 . 1 0 .0 0 . 0 0 .2" 0 . 0 (0.0) ( 0 . 0) ( 0 . 2) ( 0 . 0) (0.0) ( 0 . 4) (0.0) Moderate s e v e r i t y burns P l o t 8 Broadcast 50 0 . 2 0 . 0 0. 1 0 . 0 0 . 1 0 . 2 0 . 0 (0.3) ( 0 . 0) ( 0 . 2) ( 0 . 0) (0.1) ( 0 . 4) (0.0) P I o f 11 Broadcast 1 0 0 . 0 0 . 0 0 . 0 0 .0 0.0 0 . 1 0 . 0 (0.1) ( 0 . 0) ( 0 . 0) ( 0 . 0) (0.0) ( 0 . 2) (0.0) P l o t 12 Windrow 122 0 . 2 0. 0 0 . 2 0 . 0 0 . 1 0 .3 0.0 (0.4) ( 0 . 0) ( 0 . 3) ( 0 . 0) (0.1) ( 0 . 5) (0.0) P l o t 16 Windrow 90 0.3 0 . 1 0 . 2 0 . 0 0 . 1 0 .3 0 . 0 (0.5) ( 0 . 1) ( 0 . 3) ( 0 . 0) (0.1) ( 0 . 7) (0.0) High s e v e r i t y burns P l o t 9 Broadcast 10 0.0 0 . 0 0 . 0 0 .0 0 . 0 0 . 0 0 . 0 (0.0) ( 0 . 0) ( 0 . 0) ( 0 . 0) (0.0) (0 . 0) (0.0) P l o t 13 Broadcast 1 0 0 . 0 0. 0 0 . 0 0 , . 0 0 . 0 0 . 0 0 . 0 (0.0) ( 0 . 0) ( 0 . 0) ( 0 . 0) (0.0) ( 0 . 0) (0.0) P l o t 14 Broadcast 1 0 0 . 0 0 . 0 0. 0 0 . 0 0 . 0 0 . 0 0 . 0 (0.0) ( 0 . 0) ( 0 . 0) ( 0 . 0) (0.0) ( 0 . 0) (0.0) P l o t 15 Windrow 1 94 0 . 1 0 . 0 0 . 1 0 , . 0 0.0 0 . 1 0 . 0 (0.3) ( 0 . 0) ( 0 . 3) ( 0 . 0) (0.0) ( 0 . 4) - (0.0) P l o t 18 Windrow 403 0 . 1 0 . 0 0 . 1 0 . 1 0 . 0 0 . 1 0 . 0 (0.4) ( 0 . 0) ( 0 . 4) ( 0 . 1) (0.0) ( 0 . 5) (0.0) Standard errors are given in parenthesis. < 1 cm nutrient quantities were estimated from measurements of mass, 20 samples per plot, and their nutrient concentrations 6 composite samples per treatment block. 207 Postburn biomass and nutrient quantities (kg/ha) in 1-7 cm dead woody materials in the experimental plots. Treatment Biomass N P K Na Mg Ca S Low s e v e r i t y burns in f r e s h s l a s h P l o t 2 Broadcast 22935 5 . 9 0 . 7 4 . 2 0 . 1 2 . 6 9 . 1 2 . 1 (0.9) ( 0 . 3) ( 1 . 2) (0 . 1) ( 0 . 6) ( 1 . 9) (1.2) P l o t 17 Broadcast 1 6581 1 . 9 0. 2 1. 4 0 . 0 0 . 8 2 . 9 0 . 6 (0.3) ( 0 . 1 ) ( 0 . 3) ( 0 . 0) (0 . 2) ( 0 . 6) (0.3) P l o t 7 Windrow 4958 2 . 0 0 . 2 0 . 3 0 . 0 0 . 3 1 . 7 0 . 2 (0.6) ( 0 . 0) ( 0 . 2) ( 0 . 0) ( 0 . 2) ( 0 . 3) (0.2) P l o t 10 Windrow 4022 1 . 5 0 . 1 0 . 3 0 .0 0 .3 1 . 4 0 . 2 (0.4) ( 0 . 0) ( 0 . 2) ( 0 . 0) ( 0 . 1 ) ( 0 . 3) (0.2) Low s e v e r i t y burns in cured s l a s h P l o t 1 Broadcast 1 054 1 0 . 3 0. 1 0 . 8 0 . 0 0 . 4 1 . 5 0 . 4 (0.2) ( 0 . 0) ( 0 . 4) ( 0 . 0) ( 0 . 1 ) ( 0 . 2) (0.0) P l o t 4 Broadcast 7724 0.2 0. 0 0 . 4 0 . 0 0 . 2 0 . 8 0 . 2 (0.1) ( 0 . 0) ( 0 . 2) ( 0 . 0) ( 0 . 0) ( 0 . 1 ) (0.0) P l o t 3 Windrow 3762 1 . 1 0 . 0 0 . 3 0 . 0 0 . 2 1 .3 0 . 2 (0.3) ( 0 . 0) ( 0 . 2) ( 0 . 0) ( 0 . 1 ) ( 0 . 2) (0.1) P l o t 5 Windrow 6194 2.2 0 . 1 0 . 3 0 . 0 0 .3 1 . 6' 0.3 (0.5) ( 0 . 0) ( 0 . 2) ( 0 . 0) ( 0 . 2) ( 0 . 4) (0.2) Moderate s e v e r i t y burns P l o t 8 Broadcast 1 5602 2.3 0 . 1 2 . 0 0 . 1 0 . 9 5 . 3 0.4 (0.2) ( 0 . 0) ( 0 . 3) ( 0 . 1) ( 0 . 2) ( 1 . 0) (0.4) P I o V 11 Broadcast 8640 0.6 0 . 0 0 . 7 0 . 0 0 .3 1 . 8 0 . 1 (0.1) ( 0 . 0) ( 0 . 1 ) ( 0 . 0) ( 0 . 1 ) ( 0 . 4) (0.1) P l o t 12 Windrow 3154 1 . 1 0 . 1 0 . 1 0 . 0 0 . 2 0 . 9 0 . 1 (0.3) ( 0 . 0) ( 0 . 2) ( 0 . 0) ( 0 . 1 ) ( 0 . 2) (0.1) P l o t 16 Windrow 1 949 0 . 5 0 . 0 0. 1 0 . 0 0 . 1 0 . 5 0 . 1 (0.1) ( 0 . 0) ( 0 . 0) ( 0 . 0) ( 0 . 0) ( 0 . 1 ) (0.1) High s e v e r i t y burns P l o t 9 Broadcast 7427 0.7 0 . 0 0 . 7 0 . 0 0 . 3 2 . 1 0 . 0 (0.1 ) ( 0 . 0) ( 0 . 2) ( 0 . 0) ( 0 . 1 ) ( 1 . 1 ) (0.0) P l o t 13 Broadcast 7342 0.4 0. 0 0 . 4 0 . 0 0 .2 1 . 1 0 . 0 (0.0) ( 0 . 0) ( 0 . 1 ) ( 0 . 0) ( 0 . 0) ( 0 . 6) (0.0) P l o t 14 Broadcast 7471 0 . 6 0 . 0 0 . 6 0 , .0 0 . 2 1 . 7 0.0 (0.1) ( 0 . 0) ( 0 . 1 ) ( 0 . 0) ( 0 . 0) ( 0 . 9) (0.0) P l o t 15 Windrow 2254 0.6 0 . 0 0. 2 0 , . 0 0 . 1 0 . 5 0 . 1 (0.1) ( 0 . 0) ( 0 . 0) ( 0 . 0) ( 0 . 0) ( 0 . 1 ) r (0.1) P l o t 18 Windrow 3401 0.4 0 . 0 0. 2 0 , . 0 0 . 1 0 . 6 0 . 1 (0.1) ( 0 . 0) ( 0 . 1 ) ( 0 . 0) ( 0 . 0) ( 0 . 1 ) (0.1) Standard errors are given in parenthesis. 1-7 cm nutrient quantities were estimated from measurements of mass (from line intersects) and their mean weighted nutrient concentrations from 3 samples for each size class per plot. 208 Postburn biomass and nutrient quantities (kg/ha) in > 7 cm dead woody materials in the experimental plots. T reatment Biomass N P K Na Mg Ca S Low s e v e r i t y burns in f r e s h s l a s h P l o t 2 Broadcast 30720 8 .2 0 . 7 4 . 9 0 . 2 3 .4 12 . 6 4 . 1 (1 - 1 ) ( 0 . 5) (2 . 4) ( 0 . 0) ( 0 . 5) (1 . 7) (2.9) P l o t 17 Broadcast 70835 22 . 9 1 . 4 9 . 0 0 . 6 8 . 8 35 . 4 15.4 (2 .3) ( 1 . 1 ) (4. 0) ( 0 . 0) ( 1 . 7) ( 6 . 2) (9.6) P l o t 7 Windrow 6516 2 . 1 0. 1 1 . 0 0 . 1 0 .8 3 . 1 0 . 6 (0 .6) ( 0 . 1 ) ( 0 . 4) ( 0 . 0) ( 0 . 3) ( 0 . 6) (0.7) P l o t 10 Windrow 75 1 9 2 .7 0 . 1 1 . 2 0 . 1 1 . 1 4 . 2 0 . 9 (0 .3) ( 0 . 1 ) ( 0 . 5) ( 0 . i ) ( 0 . 4) ( 0 . 9) (0.3) Low s e v e r i t y burns i n cured I s l a s h P l o t 1 Broadcast 69138 1 0 .2 1. 8 9 . 2 1 .3 9 .4 51 . 0 13.5 (4 .8) ( 0 . 4) ( 6 . 7) ( 0 . 8) ( 3 . 2) ( 9 . 7) (1.0) P l o t 4 Broadcast 80 1 78 1 2 . 1 2. 2 1 1 . 4 1 . 4 1 1 . 0 60 . 5 16.4 (6 .0) ( 0 . 5) ( 8 . 6) ( 0 . 9) ( 3 . 9) (12. 3) (1.3) P l o t 3 Windrow 6576 1 .9 0 . 2 1 . 1 0 . 0 0 . 6 3 .4 • 0.6 (0 .3) ( 0 . 0) ( 0 . 7) ( 0 . 0) ( 0 . 2) ( 0 . (0.2) P l o t 5 Windrow 13968 3 . 4 0 . 3 2 . 9 0 . 2 1 . 5 8 . r- 1.5 (0 .6) ( 0 . 1 ) ( 1 -5) ( 0 . 0) ( 0 . 4) ( 1 . 6) (0.4) Moderate s e v e r i t y burns P l o t 8 Broadcast 49694 1 6 . 5 0. 3 18. 2 0 . 6 8 .3 51 . 0 5.3 (0 .3) ( 0 . 4) (5 . 6) ( 0 . 4) ( 2 . 1 ) (6 . 0) (0.0) P I ofr 1 1 Broadcast 49634 18 . 7 0. 5 19. 3 0 .6 9 .3 57 . 1 5.9 (0 .5) ( 0 . 7) ( 8 . 0) ( 0 . 4) ( 3 . 0) ( 6 . 5) (0.0) P l o t 12 Windrow 5704 2 . 0 0 . 1 0. 9 0 . 0 0 .8 3 .5 0 . 5 (0 .2) ( 0 . 1 ) ( 0 . 4) (0 . 0) ( 0 . 2) ( 0 . 5) (0.1) P l o t 16 Windrow 4901 1 , . 8 0 . 1 0. 9 0 . 0 0 .6 3 .2 0 . 5 (0 .2) ( 0 . 1 ) ( 0 . 4 ) ( 0 . 0) ( 0 . 2) ( 0 . 5) (0.1) High s e v e r i t y burns P l o t 9 Broadcast 41577 1 5 . 2 0 . 4 1 2 . 3 0 . 9 6 . 2 42 . 5 3.8 (1 .9) ( 0 . 4) (5 . 3) ( 0 . 5) ( 1 . 4) (10. 3) (0.7) P l o t 13 B ro a d c a s t 83983 33 .5 0 . 5 24 . 0 1 . 8 1 2 .7 90 . 2 7.0 (5 .3) ( 0 . 5) 1 4 . 0) ( 1 . 0) ( 3 . 4) (27. 5 ) (0.9) P l o t 14 Broadcast 55404 21 . 1 0 . 4 1 6 . 3 1 . 2 8 .4 58 . 1 4 . 9 (2 .9) ( 0 . 4) (8 . 0) ( 0 . 7) ( 2 . 0) (15. 5) (0.9) P l o t 15 Windrow 11175 4 . 3 0 . 3 2 . 5 0 . 2 1 . 8 9 .6 1 . 0 (0 .4) ( 0 . 1 ) ( 1 . 3) ( 0 . 1 ) ( 0 . 7) (2 . 0) (1.0) P l o t 18 Windrow 18131 7 . 1 0 . 6 3 . 9 0 .3 2 . 7 14 . 7 1 . 5 (0 .6) ( 0 . 2) (2 . 2) ( 0 . 1 ) ( 1 . 1 ) ( 3 . 1 ) (1.6) Standard errors are given in parenthesis. >7 cm nutrient quantities were estimated from measurements of mass (from line intersects) and their mean weighted nutrient concentrations from 3 samples for each size class per plot. 209 Postburn biomass and nutrient quantities (kg/ha) of all dead woody materials in the experimental plots. T reatment Biomass N P K Na Mg Ca S Lou s e v e r i t y burns i n f r e s h > s l a s h P l o t 2 Broadcast 53795 14 . 5 1 . 4 9 . 3 0 .3 6 . 1 22 .3 6 .2 (2. 7) ( 0 . 8) ( 3 . 8) (2. .7) ( 1 • 3) ( 4 . 6) (4. 1 ) P l o t 1 7 Broadcast 87586 25 . 3 1 . 7 1 0 . 7 0 . 6 9 . 7 3 9 . 0 1 6 . 1 ( 3 . 4) ( 1 . 3) ( 4 . 5) (3. .4) ( 2 . 1 ) ( 7 . 9) ( 9 . 9) P l o t 7 Windrow 115 5 5 5 . 0 0 . 4 1 . 8 0 . 1 1 .3 6 . 1 0 . 9 (2 . 7) ( 0 . 3) ( 0 . 9) (2. 7) ( 0 . 8) ( 2 . 9) ( 0 . 9) P l o t 1 0 Windrow 1 1644 5 . 6 0. 3 2 . 3 0 . 2 1 . 7 7 .6 1 . 1 ( 3 . 0) ( 0 . 4) (1 . 2) (3. .0) ( 0 . 9) (4 . 3) ( 0 . 5) Low s e v e r i t y burns i n curec I s l a s h P l o t 1 Broadcast 79699 1 0 . 6 1. 9 10. 0 1 .3 9 .8 52 . 6 13 .9 (5 . 0) ( 0 . 4) ( 7 . 0) (2. 7) ( 3 . 3) (10. 0) ( 1 . 0) P l o t 4 Broadcast 87922 12. 3 2 . 2 1 1 . 8 '1 .4 1 1 . 2 61 . 4 1 6 . 6 (6 . 1 ) ( 0 . 5) ( 8 . 8) ( 3 . 3) ( 3 . 9) (12. 5) (1 . 3) P l o t 3 Windrow 1 0494 3 . 2 0 . 2 1 . 5 0 . 0 0 .8 4 .8 0 . 5 (0. 8) ( 0 . 0) ( 1 . 0) (0. .8) ( 0 . 3) ( 1 . 1 >:, ( 0 . 0) P l o t 5 W i ndrow 20401 5 . 7 0 . 4 3 . 3 0 .2 1 . 8 9 . 9 1 . 4 ( 1 . , 1 ) ( 0 . 1 ) (1 • 9) (1. 3) ( 0 . 6) ( 2 . 4) (0 . 2) Moderate s s e v e r i t y burns P l o t 8 Broadcast 65346 19. 0 0 . 4 20 . 3 0 . 7 9 .3 56 . 5 5 . 7 (0. 8) ( 0 . 4) ( 6 . 1 > (0. .8) ( 2 . 4 ) ( 7 . 4) ( 0 . 4 ) P I o f 1 1 Broadcast 58284 19. 3 0. 5 20. 0 0 .6 9 .6 59 . 0 6 . 0 ( 0 . 7) ( 0 . 7) ( 8 . 1 ) (0. 7) ( 3 . 1 ) ( 7 . 1 ) ( 0 . 1 ) P l o t 12 Windrow 8980 3. 3 0 . 2 1 . 2 0 . 0 1 . 1 4 .7 0 . 7 ( 0 . 9) ( 0 . 1 ) <0. 9) (0. 9) ( 0 . 4 ) ( 1 . 2) ( 0 . 3) P l o t 1 6 Windrow 6940 2 . 6 0 . 2 1 . 2 0 . 0 0 . 8 4 . 0 0 .6 (0. 8) ( 0 . 2) ( 0 . 7) (0. .8) ( 0 . 3) ( 1 . 3) ( 0 . 3) High sever i ty burns P l o t 9 Broadcast 49014 1 5 . 9 0 . 4 1 3 . 0 0 . 9 6 . 5 44 . 6 3 . 8 (2 . 0) ( 0 . 4) (5 . 5) (2 . 0) ( 1 . 5) (11. 4) (0. 8) P l o t 1 3 Broadcast 94335 33 . 9 0. 5 24 . 4 1 . 8 12 . 9 91 . 3 7 . 0 (5 . 3) ( 0 . 5) (14. 1 ) (5 . 3) ( 3 . 4) (28. 1 ) ( 0 . 9) P l o t 1 4 Broadcast 62885 21 . 7 0. 4 16. 9 1 . 2 8 .6 59 . 8 4 . 9 ( 3 . 0) ( 0 . 4) ( 8 . 1 ) ( 3 . 0} ( 2 . 0) (16. 4) ( 0 . 9) P l o t 1 5 Windrow 13623 5 . 0 0 . 3 2 . 8 0 . 2 1 .9 1 0 . 2 1 . 1 ( 0 . 8) ( 0 . 1 ) ( 1 . 6) (0. .8) ( 0 . 7) ( 2 . 5)- ( 1 . 1 ) P l o t 18 Windrow 21935 7. 6 0 . 6 4 . 2 0 . 4 2 . 8 1 5 . 4 1 . 7 (1 . . 1 ) ( 0 . 2) ( 2 . 7) (1. . 1 ) (1 . 1 ) ( 3 . 7) (1 . 7) Standard errors are given in parenthesis. Postburn biomass and nutrient quantities (kg/ha) in dead woody material averaged over each treatment. Biomass N p K Na Mg Ca S (kg/ha) Low s e v e r i t y burns i n f r e s h s l a s h b r o a d c a s t 70690 1 9 .9 1 .6 1 0 . 0 0 . 5 7. 9 30 . 7 1 1 . 2 (3 . 1 ) ( 1 .0) (4 .2) (3 . 1 ) ( 1 . 7) (4 .3) (7 .0) windrow 1 1600 5 . 3 0 . 4 2 . 1 0 . 2 1 . 5 6 . 9 1 . 0 (2 .9) (0 .4) ( 1 . 1 ) (2 .9) ( 0 . 9) (3 .6) (0 .7) Low sever i ty burns i n cured s l a s h b r o a d c a s t 8381 1 22 .9 2 . 1 27 .8 1 . 4 1 0 . 5 57 . 0 1 5 . 3 (5 .6) (0 .5) (8 .0) (3 .0) ( 3 . 6) ( 1 1 .3) ( 1 .2) w indrow 1 5448 4 . 5 0 . 3 2 .4 0 . 1 1 . 3 7 .4 1 . 0 ( 1 -0) (0 . 1 ) ( 1 .5) (1 . 1 ) ( 0 . 5) (1 .8) (0 . 1 ) Moderate s e v e r i t y burns b r o a d c a s t 61815 1 9 . 2 0 . 5 20 . 2 0 . 7 9 . 5 57 . 8 5 • ? (0 .8) (0 .6) (7 . 1 ) (0 .8) (2 . 8) (7 .3) (0 .3) windrow 7960 3 . 0 0 . 2 1 . 2 0 . 0 1 . 0 4 .4 0 . 7 (0 .9) (0 .2) (0 .8) (0 .0) ( 0 . 4) (4 .4) (0 .3) High s e v e r i t y burns b r o a d c a s t 67745 23 .8 0 . 4 1 8 . 1 1 .3 9. 3 65 .2 5 . 2 (3 .4) (0 .4) (9 .2) (3 .4) ( 2 . 3) (18 .6) (0 .9) windrow 1 7779 6 . 3 0 . 5 3 . 5 0 . 3 2 . 4 1 2 . 8 1 . 4 ( 1 .0) (0 .2) (2 .3) (1 .0) ( 0 . 9) (3 . 1 ) (1 .4) Standard errors are given in parenthesis. APPENDIX 3-7 Pre and postburn nutrient quantity summary for the experimental plots. 212 Biomass and nutrient quantities (kg/ha) in forest floors in plots subjected to broadcast burning, measured before and after burning. Biomass N P < Na Mg Ca S Lou s e v e r i t y burns i n f r e s h s l a s h Preburn (Aug. 1985) P l o t 2 54000 677. 2 53 . 5 52 . 4 5 . 4 43 . 7 143 . 1 52.4 (137.9) (10. 9) (10. 7) (1 . 1 ) ( 8 . 9) (29. 2) (10.7) P l o t 17 3100 0 388.7 30. 7 30 . 1 3 . 1 25 . 1 82 . 2 30 . 1 (326.0) (25 . 7) (25. 2) ( 2 . 6) (21 . 1 > (68 . 9) (25 .2) Immediately p o s t b u r n (May 1986) P l o t 2 38000 283 .5 35 . 3 42 . 2 5 . 3 37 .6 1 1 7 . 0 18.6 (71.1) ( 9 . 4) ( 9 . 7) ( 1 . 3) (11. 6) (29. 4) (9.9) P l o t 17 21000 156.7 19. 5 23. 3 2 .9 20 .8 64 . 7 10.3 (137.9) (17. 3) (20. 4) ( 2 . 6) (18. 7) (57. 0) (10.3) 1 Year p o s t b u r n (Aug. 1987) P l o t 2 38000 301 .0 25 . 8 49. 0 3 .4 40 .7 1 86 .2 3 2.7 (47.5) ( 7 . 7) (14. 3) ( 1 -0) (11. 4) (67. 6 V, (7.8) P l o t 17 21000 166.3 1 4 . 3 27. 1 1 .9 22 . 5 1 02 . 9 18.1 (74.9) (12. 8) (24. 2) ( 1 . 7) (20 . 0) (94. 6) (15.8) Low s e v e r i t y burns i n cured s l a s h Preburn (Aug.1985 ) P l o t 1 39000 489. 1 38. 6 37. 8 3 .9 31 . 6 1 03 . 3 37.8 (87.8) ( 6 . 9) ( 6 . 8) ( 0 . 7) (5 . 7) (18. 6) (6.8) P l o t 4 31000 388 . 7 30. 7 30 . 1 3 . 1 25 . 1 82 . 2 30. 1 (175.6) (13. 9) (13. 6) ( 1 . 4) (1 1 . 3) (37. 1 ) (13.6) Immediately p o s t b u r n (May 1987) P l o t 1 26000 191.6 29. 6 51 . 2 3 .6 34 . 3 59 . 8 17.9 (45.8) ( 7 . 2) (11 . 0) ( 0 . 8) (14. 8) (29. 8) (4.3) P l o t 4 18000 132.7 20 . 5 35 . 5 2 . 5 23 . 8 41 . 4 12.4 (64.2) (10. 0) (16. 8) ( 1 -2) (14. 3) (27. 0) (6.0) Postburn (Aug. 1987) P l o t 1 26000 227.0 24 . 4 49 . 7 3 . 6 29 . 1 157 . 6 21.6 (49.0) ( 6 . 8) (10. 5) ( 1 . 7) ( 9 . 8) (48. 2) (4.4) P l o t 4 18000 157.1 16. 9 34 . 4 2 . 5 20 . 2 1 09 . 1 14.9 (47.4) ( 8 . 5) (16. 2) (1 . 6) (10. 9) (56. 7) (7.0) Means are for 16 measurements. Standard errors are given in parenthesis. Note that accurate estimates of forest floor biomass were not made during 1987.' Consequently, 1 year postburn biomass was assumed to be the same as that measured immediately postburn. 213 Biomass and nutrient quantities (kg/ha) in forest floors in plots subjected to broadcast burning, measured before and after burning. Biomass N P K Na Mg Ca S Moderate s e v e r i t y burns Preburn (Aug. 1985) P l o t 8 77000 965.6 76 . 2 74 . 7 7 . 7 62 . 4 204 . 1 74 . 7 (664.6) (52. 5) (51 . 4) ( 5 . 3) (42. 9) (14 0. 5) (51 . 4) P l o t 11 38000 4 76.5 37. 6 36. 9 3 . 8 30 .8 100 . 7 36 .9 (213.2) (16. 8) (16. 5) (1 . 7) (13. 8) (45 . 1 ) (16. 5) Immediat e l y p o s t b u r n (June 1986) P l o t 8 52000 401.4 48. 4 73 . 8 1 5 . 1 60 . 8 422 .8 25 . 0 ( 289.0 ) (47. 7) (51 . 9) (10. 5) (47. 3) ( 299 . 5) (20. 5) P l o t 11 24000 185.3 22 . 3 34. 1 7 . 0 28 . 1 195 . 1 1 1 . 5 (91.8) (15. 3) (16. 0) ( 3 . 2) (16. 2) (93. 4) ( 7 . 3) 1 Year p o s t b u r n (Aug. 1987) P l o t 8 52000 385 .3 42 . 1 86. 8 5 .2 65 .5 231 .4 29 . 9 (147.0) (31 . 4) (66. 2) ( 4 . 2) (50. 6) (221 . 3) (19. 3) P l o t 11 24000 177.8 19. 4 40 . 1 2 .4 30 . 2 106 . 8 19 .7 (49.4) (10. 3) (22. 3) ( 1 . 5) (17. 2) (85 . 6) (9 . 2) High s e v e r i t y burns Preburn (Aug. 1985) P l o t 9 45000 564.3 44 . 6 43. 7 4 . 5 36 . 5 1 1 9 . 2 43 . 7 (401.3) (31 . 7) (31 . 0) ( 3 . 2) (25. 9) (84 . 8) (31 . 0) P l o t 13 41000 5 14.1 40 . 6 39. 8 4 . 1 33 . 2 1 08 . 7 39 . 8 (326.0) (25 . 7) (25 . 2) ( 2 . 6) (21 . 1 ) (68. 9) (25. 2) P l o t 14 43000 539.2 42 . 6 41 . 7 4 . 3 34 .8 1 14 . 0 41 . 7 (388.7) (30. 7) (30. 1 ) ( 3 . 1 ) (25 . 1 ) (82 . 2) (30. 1 ) Immediately p o s t b u r n ( J u l y 1986) P l o t 9 31000 237.8 36. 3 57. 4 9 . 0 37 . 2 309 . 1 20 .2 (154.5) (24. 0) (42. 6) (5 . 9) (27. 5) (201 . 8) (13. 4) P l o t 13 23000 176.4 26. 9 42 . 6 6 . 7 27 . 6 229 . 3 1 5 . 0 (118.7) (18. 4 ) (32. 5) (4 . 5 ) (21 . 0) (155. 0 ) (10. 3) P l o t 14 25000 191.8 29 . 3 46 . 3 7 .3 30 . 0 249 .3 1 6 .3 (143.8) (22. 2) (38. 4) (5 . 5) (24. 9) (187. 5) (12. 4) 1 Year po s t b u r n (Aug. 1987) P l o t 9 31000 215.1 24 . 2 54 . 6 4 . 3 37 . 2 1 29 . 3 30 . 1 (83. 1) (17. 5) (37. 3) ( 3 . 0) (26. 6) (109. 6) (19. 3) P l o t 13 23000 159.6 17. 9 40 . 5 3 . 2 27 . 6 95 . 9 22 . 3 (63.2) (13. 4) (28. 6) (2 . 3) ( 20 . 3) (83 . 0) (14. 3) P l o t 14 25000 1 73 . 5 1 9 . 5 44 . 0 3 . 5 30 . 0 104 . 3 24 . 3 (74.5) (15. 9) (34. 3) (2 . 7) (24 . 2) (96. 6) (18. 0) Means are for 16 measurements. Standard errors are given in parenthesis. Note that accurate estimates of forest floor biomass were not made during 1987. Consequently, 1 year postburn biomass was assumed to be the same as that measured immediately postburn. 214 Preburn and postburn nitrogen quantities (kg/ha) in the experimental plots. 1) Low Severity Burns (fresh slash - 1986) Plot No. 02 17 07 10 Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 125.5 241.1 235.1 199.8 Dead woody materials 71.9 49.8 97.2 102.1 Total slash 197.4 14.5 290.9 25.3 332.3 5.3 301.9 6.1 2. Understory 102.8 93.4 77.0 81.8 3. Forest floor 677.2 283.5 388.7 156.7 790.0 86.5 388.7 0.0 Windrow ash 25.6 26.0 4. Total biomass 977.4 298.0 773.0 182.0 1199.3 117.4 772.4 32.1 2) Low Severity Burns (cured slash - 1987) Plot No. 01 04 03 05 Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 125.5 141.7 232.5 170.6 Dead woody materials 102.6 140.9 95.1 111.8 Total slash 228.1 10.6 282.6 12.3 327.6 3.2 282.4 5.7 2. Understory 131.4 68.2 86.8 73.5 3. Forest floor 489.1 191.6 388.7 132.7 576.8 15.8 526.7 71.7 Windrow ash 37.7 40.7 4. Total biomass 848.6 202.2 739.5 145.0 991.2 56.7 882.6 118.1 3) Moderate Severity Burns Plot No. 08 11 12 16 Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 221.0 287.5 288.6 267.2 Dead woody materials 87.0 116.3 98.5 83.9 Total slash 308.0 19.0 403.8 19.3 387.1 3.3 351.1 2.6 2. Understory 96.5 72.9 73.9 76.4 3. Forest floor 965.6 401.4 476.5 185.3 426.4 0.0 464.0 0.0 Windrow ash 25.6 36.1 4. Total biomass 1370.1 420.4 953.2 204.6 887.4 28.9 891.5 38.7 4) High Severity Burns Plot No. 09 13 14 15 18 Pre Post Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 288.8 253.3 219.9 302.2 347.0 Dead woody materials 98.5 104.3 124.8 106.7 22.7 Total slash 387.3 15.9 357.6 33.9 344.7 21.7 408.9 5.0 369.7 7.6 2. Understory 55.1 91.7 53.5 48.4 56.7 3. Forest floor 564.3 237.8 514.1 176.4 539.2 191.8 915.4 21.3 777.5 13.2 Windrow ash 60.2 58.7 4. Total biomass 1006.7 253.7 963.4 210.3 937.4 213.5 1372.7 86.5 1203.9 79.5 5) Control plots 6) Mistakenly burned (Fall 1986) 'lot : No. 02 03 Plot No. I Pre Post Pre Post Pre 1. Slash 1. Slash Lodgepole pine 149.2 242.6 Lodgepole pine 175.0 Dead woody materials 66.6 78.5 Dead woody materials 108.9 Total slash 215.8 321.1 Total slash 283.9 2. Understory 85.6 71.5 2. Understory 70.1 3. Forest floor 739.9 702.2 3. Forest floor 611.9 4. Total biomass 1041.3 1094.8 4. Total biomass 965.9 215 Preburn and postburn phosphorus quantities (kg/ha) in the experimental plots. 1) Low Severity Burns (fresh slash - 1986) Plot No. 02 17 07 10 Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 22.4 31.5 30.5 26.2 Dead woody materials 2.3 1.7 3.3 3.7 Total slash 24.7 1.4 33.2 1.7 33.8 0.4 29.9 0.3 2. Understory 4.5 5.6 5.2 6.1 3. Forest floor 53.5 35.3 30.7 19.5 62.4 11.2 30.7 0.0 Windrow ash 2.8 2.9 4. Total biomass 82.7 36.7 69.5 21.2 101.4 14.4 66.7 3.2 2) Low Severity Burns (cured slash - 1987) Plot No. 01 04 03 05 Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 15.9 18.6 30.3 22.2 Dead woody materials 3.8 5.3 3.2 4.1 Total slash 19.7 1.9 23.9 2.2 33.5 0.2 26.3 0.4 2. Understory 5.6 3.1 3.9 3.1 3. Forest floor 38.6 29.6 30.7 20.5 45.5 1.2 41.6 5.4 Windrow ash 4.2 4.5 4. Total biomass 63.9 31.5 57.7 22.7 82.9 5.6 71.0 10.3 3) Moderate Severity Burns >lot No. 08 11 12 16 Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 28.7 37.7 37.5 34.9 Dead woody materials 3.1 4.2 3.6 3.0 Total slash 31.8 0.4 41.9 0.5 41.1 0.2 37.9 0.2 2. Understory 5.8 4.7 4.2 5.4 3. Forest floor 76.2 48.4 37.6 22.3 33.7 0.0 36.6 0.0 Windrow ash 2.8 4 4. Total biomass 113.8 48.8 84.2 22.8 79.0 3.0 79.9 4.2 4) High Severity Burns Plot No. 09 13 14 15 18 Pre Post Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 37.7 33.0 28.5 39.2 45.1 Dead woody materials 3.6 3.7 4.6 3.9 0.6 Total slash 41.3 0.4 36.7 0.5 33.1 0.4 43.1 0.3 45.7 0.6 2. Understory 3.3 5.2 3.7 2.9 3.8 3. Forest floor 44.6 36.3 40.6 26.9 42.6 29.3 72.3 2.0 61.4 0.8 Windrow ash 6.7 6.5 4. Total biomass 89.2 36.7 82.5 27.4 79.4 29.7 118.3 9.0 110.9 7.9 5) Control Plot No. plots 02 Pre Post Slash Lodgepole pine Dead woody materials Total slash Understory Forest floor 4. Total biomass 86.7 03 Pre Post 31.2 2.7 33.9 4.0 55.4 93.3 6) Mistakenly burned (Fall Plot No. 2. 3. Slash Lodgepole pine Dead woody material Total slash Understory Forest floor 1986) 06 Pre Post 4. Total biomass 23.0 3.8 26.8 3.1 38.6 68.5 216 Preburn and postburn potassium quantities (kg/ha) in the experimental plots. 1) Low Severity Burns (fresh slash - 1986) Hot No. 02 17 07 10 Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 45.9 63.9 62.6 53.9 Dead woody materials 7.9 3.7 9.3 9.6 Total slash 53.8 9.3 67.6 10.7 71.9 1.8 63.5 2.3 2. Understory 10.8 11.8 10.2 11.6 3. Forest floor 52.4 42.2 30.1 23.3 61.1 9.7 30.1 0.0 Windrow ash 0.6 0.6 4. Total biomass 117.0 51.5 109.5 34.0 143.2 12.1 105.2 2.9 2) Low Severity Burns (cured slash - 1987) >lot No. 01 04 03 05 Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 34.4 38.6 61.8 45.5 Dead woody materials 9.7 12.0 9.7 9.4 Total slash 44.1 10.0 50.6 11.8 71.5 1.5 54.9 3.3 2. Understory 13.4 7.5 9.2 7.5 3. Forest floor 37.8 51.2 30.1 35.5 44.6 1.1 40.7 5.1 Windrow ash 0.8 0.9 4. Total biomass 95.3 61.2 88.2 47.3 125.3 3.4 103.1 9.2 3) Moderate Severity Burns Hot No. 08 11 12 16 Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 59.0 76.5 77.0 71.0 Dead woody materials 8.8 9.9 7.8 6.7 Total slash 67.8 20.3 86.4 20.0 84.8 1.2 77.7 1.2 2. Understory 10.7 8.9 7.2 14.5 3. Forest floor 74.7 73.8 36.9 34.1 33.0 0.0 35.9 0.0 Windrow ash 0.6 0.8 4. Total biomass 153.2 94.1 132.2 54.1 125.0 1.8 128.1 1.8 4) High Severity Burns •lot No. 09 13 14 15 18 Pre Post Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 76.2 67.2 58.6 79.8 91.4 Dead woody materials 8.3 8.3 10.1 8.5 2.3 Total slash 84.5 13.0 75.5 24.4 68.7 16.9 88.3 2.8 93.7 4.2 2. Understory 5.6 9.8 6.6 5.4 9.1 3. Forest floor 43.7 57.4 39.8 42.6 41.7 46.3 70.8 1.9 60.1 0.7 Windrow ash 1.3 1.3 4. Total biomass 133.8 70.4 125.1 67.0 117.0 63.2 164.5 6.0 162.9 6.2 5) Control plots 6) Mistakenly burned (Fall 1986) 'lot No. 02 03 Plot No. 06 Pre Post Pre Post Pre Post 1. Slash 1. Slash Lodgepole pine 39.5 63.4 Lodgepole pine 47.3 Dead woody materials 6.5 6.5 Dead woody materials 9.7 Total slash 46.0 69.9 Total slash 57.0 2. Understory 6.3 4.0 2. Understory 7.6 3. Forest floor 57.2 54.3 3. Forest floor 37.8 4. Total biomass 109.5 128.2 4. Total biomass 102.4 217 Preburn and postburn sodium quantities (kg/ha) in the experimental plots. 1) Low Severity Burns (fresh slash - 1986) Plot No. 02 17 07 10 Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 3.3 4.7 4.5 .3.9 Dead woody materials 1.9 0.9 2.2 2.4 Total slash 5.2 0.3 5.6 0.6 6.7 0.1 6.3 0.2 2. Understory 0.4 0.3 0.4 0.4 3. Forest floor 5.4 5.3 3.1 2.9 6.3 0.7 3.1 0.0 Windrow ash 0.1 0.1 4. Total biomass 11.0 5.6 9.0 3.5 13.4 0.9 9.8 0.3 2) Low Severity Burns (cured slash - 1987) Plot No. 2. 3. 4. Slash Lodgepole pine Dead woody materials Total slash Understory Forest floor Windrow ash Total biomass 01 Pre Post 2.5 2.4 4.9 0.5 3.9 1.3 3.6 04 Pre Post 9.3 4.9 2.9 3.0 5.9 0.3 3.1 9.3 1.4 2.5 3.9 03 Pre Post 4.4 2.4 6.8 0.3 4.6 11.7 05 Pre Post 0.0 0.1 0.2 0.3 10.2 0.2 0.3 0.2 0.7 3) Moderate Severity Burns Plot No. 08 11 12 16 Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 4.4 5.5 5.5 5.2 Dead woody materials 2.2 2.4 2.0 1.6 Total slash 6.6 0.7 7.9 0.6 7.5 0.0 6.8 0.0 2. Understory 0.5 0.4 0.3 0.3 3. Forest floor 7.7 15.1 3.8 7.0 3.4 0.0 3.7 0.0 Windrow ash 0.1 0.2 4. Total biomass 14.8 15.8 12.1 7.6 11.2 0.1 10.8 0.2 4) High Severity Burns Plot No. 09 13 14 15 18 Pre Post Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 5.5 4.8 4.4 5.8 6.7 Dead woody materials 2.0 2.0 2.5 2.1 0.5 Total slash 7.5 0.9 6.8 1.8 6.9 1.2 7.9 0.2 7.2 0.4 2. Understory 0.2 0.3 0.2 0.2 0.2 3. Forest floor 4.5 9.0 4.1 6.7 4.3 7.3 7.3 0.3 6.2 0.1 Windrow ash 0.3 0.3 4. Total biomass 19.5 9.9 11.2 8.5 11.4 8.5 15.4 0.8 13.6 0.8 5) Control plots Plot No. 02 03 Pre Post Pre 1. Slash Lodgepole pine 3.0 4.7 Dead woody materials 1.7 1.5 Total slash 4.7 6.2 2. Understory 0.4 0.2 3. Forest floor 5.9 5.6 4. Total biomass 11.0 12.0 6) Mistakenly burned (Fall 1986) Plot No. 06 Post Pre Post 1. Slash Lodgepole pine 3.4 Dead woody materials 2.4 Total slash 5.8 2. Understory 0.3 3. Forest floor 3.9 4. Total biomass 10.0 218 Preburn and postburn magnesium quantities (kg/ha) in the experimental plots. 1) Low Severity Burns (fresh slash - 1986) Plot No. 02 17 07 10 Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 34.4 47.5 46.9 40.1 Dead woody materials 23.4 10.2 21.0 24.8 Total slash 57.8 6.1 57.7 9.7 67.9 1.3 64.9 1.7 2. Understory 3.2 4.8 4.3 4.9 3. Forest floor 43.7 37.6 25.1 20.8 51.0 6.5 25.1 0.0 Windrow ash 0.7 0.7 4. Total biomass 104.7 43.7 87.6 30.5 123.2 8.5 94.9 2.4 2) Low Severity Burns (cured slash - 1987) Plot No. 01 04 03 05 Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 25.7 28.8 46.1 34.2 Dead woody materials 23.4 34.1 20.3 28.3 Total slash 49.1 9.8 62.9 11.2 66.4 0.8 62.5 1.8 2. Understory 3.9 2.3 2.8 2.2 3. Forest floor 31.6 34.3 25.1 23.8 37.3 0.8 34.0 4.0 Windrow ash 1.0 1.1 4. Total biomass 84.6 44.1 90.3 35.0 106.5 2.6 98.7 6.9 3) Moderate Severity Burns Hot No. 08 11 12 16 Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 43.7 57.5 57.7 52.7 Dead woody materials 20.2 27.5 23.7 18.8 Total slash 63.9 9.3 85.0 9.6 81.4 1.1 71.5 0.8 2. Understory 4.3 3.7 3.1 5.3 3. Forest floor 62.4 60.8 30.8 28.1 27.5 0.0 30.0 0.0 Windrow ash 0.7 1.0 4. Total biomass 130.6 70.1 119.5 37.7 112.0 1.8 106.8 1.8 4) High Severity Burns Plot No. 09 13 14 15 18 Pre Post Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 57.0 49.7 43.5 59.6 68.1 Dead woody materials 23.1 24.2 29.6 24.9 5.2 Total slash 80.1 6.5 73.9 12.9 73.1 8.6 84.5 1.9 73.3 2.8 2. Understory 3.3 5.2 3.7 2.9 3.8 3. Forest floor 36.5 37.2 33.2 27.6 34.8 30.0 59.1 2.1 50.2 1.0 Windrow ash 1.6 1.6 4. Total biomass 119.9 43.7 112.3 40.5 111.6 38.6 146.5 5.6 127.3 5.4 5) Control plots 6) Mistakenly burned (Fall 1986) Plot No. 02 03 Plot No. 06 Pre Post Pre Post Pre Post 1. Slash 1. Slash fuel Lodgepole pine 29.3 47.0 Lodgepole pine 35.1 Dead woody materials 15.3 17.0 Dead woody materials 26.7 Total slash 48.1 64.0 Total slash 61.8 2. Understory 3.5 3.5 2. Understory 2.4 3. Forest floor 47.8 45.4 3. Forest floor 31.6 4. Total biomass 95.9 112.9 4. Total biomass 95.8 Preburn and postburn calcium quantities (kg/ha) in the experimental plots. 219 1) Low Severity Burns (fresh slash - 1986) Plot No. 02 17 07 10 Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 83.4 116.3 114.0 97.6 Dead woody materials 77.9 49.5 104.2 111.2 Total slash 161.3 22.3 165.8 39.0 218.2 6.1 208.8 7.6 2. Understory 15.0 23.2 18.6 21.6 3. Forest floor 143.1 117.0 82.2 64.7 167.0 24.3 82.2 0.0 Windrow ash 4.4 4.5 4. Total biomass 319.4 139.3 271.2 103.7 403.8 34.8 312.6 12.1 2) Low Severity Burns (cured slash - 1987) Plot No. 01 04 03 05 Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 60.8 69.3 112.6 82.8 Dead woody materials 115.2 164.4 101.5 135.3 Total slash 176.0 52.6 233.7 61.4 214.1 4.8 218.1 9.9 2. Understory 19.9 10.8 13.1 10.9 3. Forest floor 103.3 59.8 82.2 41.4 121.9 2.5 111.3 9.1 Windrow ash 6.5 7.0 4. Total biomass 299.2 112.4 326.7 102.8 349.1 13.8 340.3 26.0 3) Moderate Severity Burns Plot No. 08 11 12 16 Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 106.6 139.5 140.1 129.4 Dead woody materials 99.6 132.8 113.8 90.9 Total slash 206.2 56.5 272.3 59.0 253.9 4.7 220.3 4.0 2. Understory 21.0 17.0 17.3 20.6 3. Forest floor 204.1 183.6 100.7 84.7 90.1 0.0 98.1 0.0 Windrow ash 4.4 6.2 4. Total biomass 431.3 240.1 390.0 143.7 361.3 9.1 339.0 10.2 4) High Severity Burns Plot No. 09 13 14 15 18 Pre Post Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 139.9 122.0 106.0 145.7 166.9 Dead woody materials 111.5 116.4 142.0 119.6 25.4 Total slash 251.4 44.6 238.4 91.3 248.0 59.8 265.3 10.2 192.3 15.4 2. Understory 13.9 22.5 16.6 17.4 15.9 3. Forest floor 119.3 158.7 108.7 117.8 114.0 128.0 193.5 7.3 164.3 3.9 Windrow ash 10.3 10.3 4. Total biomass 384.6 203.3 369.6 209.1 378.6 187.8 476.2 27.8 372.5 29.6 5) Control plots 6) Mistakenly burned (Fall 1986) Plot No. 02 03 Plot No. 06 Pre Post Pre Post Pre Post 1. Slash 1. Slash Lodgepole pine 72.1 115.5 Lodgepole pine 85.2 Dead woody materials 75.3 82.6 Dead woody materials 128.5 Total slash 147.4 198.1 Total slash 213.7 2. Understory 19.7 18.2 2. Understory 15.1 3. Forest floor 156.4 148.4 3. Forest floor 103.4 4. Total biomass 323.5 364.7 4. Total biomass 332.2 220 Preburn and postburn sulphur quantities (kg/ha) in the experimental plots. 1) Low Severity Burns (fresh slash - 1986) Hot No. 02 17 07 10 Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 23.8 33.3 32.5 27.9 Dead woody materials 9.7 6.1 12.6 13.6 Total slash 33.5 6.2 39.4 16.1 45.1 0.9 41.5 1.1 2. Understory 5.5 5.4 5.2 6.2 3. Forest floor 52.4 18.6 30.1 10.3 61.1 6.8 30.1 0.0 Windrow ash 2.7 2.7 4. Total biomass 91.4 24.8 74.9 26.4 111.4 10.4 77.8 3.8 2) Low Severity Burns (cured slash - 1987) Hot No. 01 04 03 05 Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 18.2 19.7 32.1 23.6 Dead woody materials 13.1 19.2 12.9 15.1 Total slash 31.3 13.9 38.9 16.6 45.0 0.5 38.7 1.4 2. Understory 6.9 3.7 4.7 3.8 3. Forest floor 37.8 17.9 30.1 12.4 44.6 1.0 40.7 4.9 Windrow ash 4.0 4.3 4. Total biomass 76.0 31.8 72.7 29.0 94.3 5.5 83.2 10.6 3) Moderate Severity Burns Hot No. 08 11 12 16 Pre Post Pre Post Pre Post Pre Po"st 1. Slash Lodgepole pine 30.6 39.7 39.9 36.9 Dead woody materials 11.7 15.2 12.7 10.5 Total slash 42.3 5.7 54.9 6.0 52.6 0.7 47.4 0.6 2. Understory 6.3 4.9 4.7 4.9 3. Forest floor 74.7 25.0 36.9 11.5 33.0 0.0 35.9 0.0 Windrow ash 2.7 3.8 4. Total biomass 123.3 30.7 96.7 17.5 90.3 3.4 88.2 4.4 4) High Severity Burns 'lot No. 09 13 14 15 18 Pre Post Pre Post Pre Post Pre Post Pre Post 1. Slash Lodgepole pine 39.8 35.1 30.4 41.7 48.0 Dead woody materials 12.7 13.3 16.0 13.5 3.4 Total slash 52.5 3.8 48.4 7.0 46.4 4.9 55.2 1.1 51.4 1.7 2. Understory 3.6 5.2 3.6 2.9 6.4 3. Forest floor 43.7 20.2 39.8 15.0 41.7 16.3 70.8 1.9 60.1 1.0 Windrow ash 6.4 6.2 4. Total biomass 99.8 24.0 93.4 22.0 91.7 21.2 128.9 9.4 117.9 8.9 5) Control plots 6) Mistakenly burned (Fall 1986) Hot No. 02 03 Plot No. 06 Pre Post Pre Post Pre Post 1. Slash 1. Slash Lodgepole pine 20.7 33.4 Lodgepole pine 24.4 Dead woody materials 8.9 9.7 Dead woody materials 14.8 Total slash 29.6 43.1 Total slash 39.2 2. Understory 5.5 4.0 2. Understory 3.8 3. Forest floor 52.4 44.6 3. Forest floor 37.8 4. Total biomass 87.5 91.7 4. Total biomass 80.8 APPENDIX 3-8 Preburn and one year postburn nutrient concentrations the surface 15 cm of rriineral soil in the experimental plots. 222 Pretreatment values for selected chemical properties of the surface 15 cm of mineral soils in the experimental plots pH H20 T o t a l N (%) P E x t r a c t a b l e K Mg (Dom) Ca M i n e r a l -i z a b l e N T o t a l S < % > P l o t 1 mean 4 . 0 0.145 49 192 82 414 3 . 3 0.007 s.d. 0.2 0 .022 15 8 43 212 3.4 0.007 P l o t 2 mean 4 . 0 0.192 49 211 1 17 513 2.6 0.014 s.d. 0.1 0.035 28 14 54 250 0.6 0.021 P l o t 3 mean 4 . 1 0.159 39 197 1 09 499 3.4 0.021 s.d. 0 . 1 0 . 032 1 1 22 31 130 1 . 2 0.021 P l o t 4 mean 4 . 1 0.121 40 181 72 355 2 . 7 0.014 s.d. 0.1 0.049 18 9 26 96 0.2 , 0.007 P l o t 5 -mean 4 . 0 0.116 32 193 1 15 509 2.8 0.014 s.d. 0 . 1 0.014 5 8 22 75 0 . 6 0.000 P l o t 6 mean 4.2 0.117 36 180 1 06 401 3 . 5 0.007 s.d. 0 . 2 0.041 23 29 5 1 45 1 . 7 0.007 P l o t 7 mean 4 . 1 0.076 41 168 82 532 3.9 0.014 s.d. 0 . 1 0.022 17 14 45 332 1 . 9 0.021 P l o t 8 mean 4 . 0 0 . 083 42 164 46 259 2 . 1 0.007 s.d. 0.2 0.021 17 1 1 13 55 0.7 0.014 P l o t 9 mean 4 . 1 0.073 51 177 79 500 1 .9 0.007 s.d. 0 . 2 0.013 1 9 1 0 38 214 0 . 2 0.007 Treatment plot means are for 4 measurements. 223 Pretreatment values for selected chemical properties of the surface 15 cm of mineral soils in the experimental plots. p H T o t a l E x t r a c t a b l e M i n e r a l - T o t a l N P K Mg C a i z a b l e N S H20 (%) (ppm) (%) P l o t 10 mean s.d. 4.1 0.087 31 182 83 472 2.3 0.005 0.2 0.011 13 4 33 150 0.6 0.000 P l o t 11 mean s.d. 4.1 0.086 30 155 85 429 1.7 0.005 0.1 0.014 9 8 15 103 0.4 0.000 P l o t 12 mean s.d. 4.0 0.101 37 153 81 489 2.6 0.005 0.0 0.013 11 16 42 259 0.7 0.000 P l o t 13 mean s.d. 4.1 0.101 51 165 56 436 2.6 0.005 0.1 0.002 27 8 2 71 1 . 1 0 . 0 0 0 P l o t 14 mean s.d. 4 . 1 0 . 1 0 .092 0.016 66 169 25 24 62 272 1.4 0.007 50 69 0.3 0.014 P l o t mean s.d. 1 5 0.159 0 31 152 28 213 2.6 0.014 0 0 0 0 0.0 0.000 P l o t 16 mean s.d. 4.0 0.100 61 176 53 383 1.9 0.007 0.2 0.022 5 24 23 160 0.4 0.007 P l o t mean s.d. 1 7 4.2 0.106 62 155 67 389 2.0 0.014 0.1 0.014 31 7 42 84 0.2 0.021 P l o t 18 mean s.d. 4.1 0.109 47 168 109 657 3.8 0.005 0.2 0.029 5 23 30 39 2.5 0.000 C o n t r o l 1 mean s.d. 4 . 1 0 . 1 0.081 0.014 72 211 77 328 2.8 0.005 24 56 18 71 2.8 0.000 C o n t r o l 2 mean s.d. 4.0 0.119 54 242 98 564 2.9 0.014 0.2 0.068 34 83 67 523 1.8 0.021 C o n t r o l 3 mean s.d. 3.9 0.094 78 198 120 695 2.4 " 0.007 0.3 0.028 54 45 65 518 0.9 0.007 Treatment plot means are for 4 measurements. Control plot means are for 16 measurements. 224 One year post-treatment values of selected chemical properties of the surface 15 cm of mineral soil in the experimental plots. pH T o t a l Ex t r a c t a b l e M i n e r a l - T o t a l N P K Mg C a i z a b l e N S H20 (%) (ppm) (%) 1) BROADCAST BURN PLOTS a) Low s e v e r i t y burns in f r e s h s l a s h ( p l o t s 2,17) mean 4.4 0.104 35 136 95 479 0.5 0.007 s.d. 0.1 0.014 12 47 39 190 0.8 0.001 Low s e v e r i t y burns in cured s l a s h ( p l o t s 1,4) mean 4.2 0.088 19 97 104 424 1.3 0.007 s.d. 0.1 0.005 7 20 43 165 0.9 0.002 Moderate s e v e r i t y burns ( p l o t s 8,11) mean 4.4 0.104 29 130 97 517 1.8 0.008 s.d. 0.2 0.005 10 21 38 192 1.5 0.002 High s e v e r i t y burns ( p l o t s 9,13,14) mean 4.4 0.112 30 163 125 626 2.7 0.008 s.d. 0.2 0.014 12 40 42 177 1.4 0.002 2) WINDROW BURNED PLOTS a) areas between windrows Low s e v e r i t y burns in f r e s h s l a s h ( p l o t s 7,10) mean 4.4 0.054 20 125 121 664 1.0- 6.007 s.d. 0.1 0.010 8 32 27 120 0.7 0.001 Low s e v e r i t y burns i n cured s l a s h ( p l o t s 3,5) mean 4.4 0.112 28 111 114 514 1.8 0.012 s.d. 0.2 0.054 23 21 23 69 1.8 0.003 Moderate s e v e r i t y burns ( p l o t s 12,16) mean 4.4 0.076 31 146 99 684 1.8 0.011 s.d... 0 . 2 0.018 21 45 22 253 2.9 0.001 High s e v e r i t y burns ( p l o t s 15,18) mean 5.0 0.112 28 156 199 1168 1.8 0.012 s.d. 0.4 0.054 23 14 128 473 1.8 0.003 b) areas beneath windrows Low s e v e r i t y burns i n f r e s h s l a s h ( p l o t s 7,10) mean 5.4 0.104 31 218 165 1024 2.6 0.013 s.d. 0.8 0.038 14 43 57 439 2.7 0.005 Low s e v e r i t y burns i n cured s l a s h ( p l o t s 3,5) mean 5.7 0.100 39 276 303 1562 1.8 0.014 s.d. 0.9 0.026 28 54 81 316 3.5 0.003 Moderate s e v e r i t y burns ( p l o t s 12,16) mean 5.7 0.112 13 223 290 1985 1.4 0.012 s.d. 0.4 0.058 20 53 153 1247 1.9 0.006 High s e v e r i t y burns ( p l o t s 15,18) mean 5.8 0.134 39 264 353 1372 1.2 0.013 s.d. .0 .9 0 . 028 27 60 195 307 2.2 0.001 Means are for 8 samples 225 One year post-treatment values for selected chemical properties of the surface 15 cm of mineral soils in the experimental plots. pH T o t a l E x t r a c t a b l e M i n e r a l - T o t a l N P K Mg C a i z a b l e N S H20 <%> (ppm) (%) 3) CONTROL PLOTS CONTROL 2 mean 4.4 0.092 25 331 240 609 0.0 0.008 s.d. 0.2 0.024 21 47 96 311 0.0 0.005 CONTROL 3 mean 4.3 0.104 21 454 290 745 0.0 0.008 s.d. 0.2 0.030 18 112 114 301 0.0 0.002 Means are for 16 samples 226 APPENDIX 3-9 Preburn and one year postburn mineral soil mass of the < 2 mm fraction and nutrient quantities of the surface 15 cm of mineral soil in the experimental plots. Preburn mass and nutrient quantities (kg/ha) in the surface 15 cm of mineral soil in the experimental plots. M i n e r a l s o i l T o t a l E x t r a c t a b l e M i n e r a l - " T o t a l < 2 mm N P K Mg Ca i z a b l e N S f r a c t i o n P l o t 1 mean s . e. 1035000 270000 1501 453 51 21 1 99 52 85 50 428 246 72 75 P l o t mean s . e. 1 035000 270000 1987 632 50 31 218 59 121 64 531 293 145 221 P l o t mean s . e . 1 035000 270000 1 646 542 40 15 204 58 113 43 516 1 90 217 225 P l o t mean s . e . 1035000 270000 1 252 603 42 22 1 88 50 74 33 367 138 145 82 P l o t mean s . e . 1035000 270000 1201 345 33 1 0 200 5 3 1 19 38 527 158 145 38 P l o t mean s . e . 1035000 270000 1211 529 37 26 186 57 1 1 0 60 415 118 72 75 P l o t mean s . e . 1035000 270000 787 307 43 21 1 74 48 84 52 551 372 145 221 P l o t 8 mean s . e . 1035000 270000 859 312 44 21 1 70 46 48 19 268 90 72 146 P l o t mean s . e. 1035000 270000 756 239 53 24 183 49 81 4 5 517 259 72 75 228 Preburn mass and nutrient quantities (kg/ha) in the surface 15 cm of mineral soil in the experimental plots. M i n e r a l s o i l T o t a l E x t r a c t a b l e M i n e r a l - T o t a l < 2 mm N P K Mg Ca i z a b l e N S f r a c t i o n P l o t 10 mean s . e. 1035000 270000 900 261 32 16 1 88 49 86 489 41 201 52 0 P l o t 11 mean s . e . 1035000 270000 890 274 32 1 2 160 43 88 28 443 157 52 0 P l o t 12 mean s . e . 1035000 270000 1 045 304 38 15 158 44 84 506 49 299 52 0 P l o t 13 mean s . e . 1035000 270000 1045 273 53 31 1 70 45 58 1 5 452 139 52 0 P l o t 14 mean s . e . 1035000 270000 952 299 68 3 1 1 75 52 65 282 55 103 72 146 P l o t 15 mean s . e . 1035000 270000 1646 429 32 8 158 41 29 220 7 57 145 38 P l o t 16 mean s . e. 1035000 270000 1035 353 63 1 7 182 54 55 396 28 195 72 75 P l o t 17 mean s . e. 1035000 270000 1 097 321 64 37 161 42 69 402 47 136 145 221 P l o t 18 mean s . e . 1035000 270000 1 1 28 420 49 174 113 680 14 51 43 182 52 0 C o n t r o l 1 mean 1035000 s . e . 270000 838 262 74 32 219 81 79 340 28 115 5 2 0 C o n t r o l 2 mean 1035000 s . e , 270000 1 232 774 56 250 101 584 38 107 74 563 14 5 221 C o n t r o l 3 mean 1035000 s . e . 270000 973 385 81 60 205 71 124 720 75 568 72 75 One year postburn mass and nutrient quantities (kg/ha) in the surface 15 cm of mineral soil in the experimental plots. M i n e r a l s o i l T o t a l E x t r a c t a b l e M i n e r a l - T o t a l < 2 mm N P K Mg Ca i z a b l e N S f r a c t i o n 1) BROADCAST BURN PLOTS Low s e v e r i t y burns i n f r e s h 1035000 270000 Low s e v e r i t y burns 1035000 270000 Moderate s e v e r i t y 1035000 270000 High s e v e r i t y burns ( p l o t s 1035000 1159 270000 335 1 076 316 in cured 91 1 243 burns 1 076 286 s l a s h 36 1 6 s l a s h 20 9 ( p l o t s 8 30 13 9.13, 31 1 5 ( p l o t s 141 61 ( p l o t s 100 33 1 1 ) 135 41 14) 169 60 2.17) 98 48 1 ,o 108 53 100 47 129 55 496 235 439 206 535 243 648 249 72 22 72 28 83 30 83 30 2) WINDROW BURNED PLOTS a) Areas between windrows Low s e v e r i t y burns i n f r e s h s l a s h ( p l o t s 1350000 729 27 169 270000 199 12 55 Low s e v e r i t y burns i n cured s l a s h ( p l o t s 1350000 1512 38 150 270000 789 32 41 Mod.e,rate s e v e r i t y burns ( p l o t s 12,16) 1350000 1026 42 197 270000 318 30 72 High s e v e r i t y burns ( p l o t s 15,18) 1350000 1512 38 211 270000 789 32 46 7, 3, 10) 163 49 5) 154 44 134 40 269 181 896 242 694 167 923 388 15 77 712 95 23 162 52 149 33 162 52 b) Areas beneath windrows Low s e v e r i t y burns i n f r e s h s l a s h ( p l o t s 1320000 1373 41 288 360000 626 22 97 Low s e v e r i t y burns i n cured s l a s h ( p l o t s 1320000 1320 51 364 360000 497 40 122 Moderate s e v e r i t y burns ( p l o t s 12,16) 1320000 1478 17 294 360000 865 27 106 High s e v e r i t y burns ( p l o t s 15,18) 1320000 1769 51 348 360000 608 38 124 7,10) 218 96 3,5) 400 153 383 227 466 287 1352 687 2062 700 2620 1794 1811 639 1 72 81 185 64 158 90 172 4 9 230 One year postburn mass and nutrient quantities (kg/ha) in the surface 15 cm of mineral soil in the experimental plots. M i n e r a l s o i l T o t a l E x t r a c t a b l e M i n e r a l - T o t a l < 2 mm N P K Mg Ca i z a b l e N S f r a c t i o n 3) CONTROL PLOTS CONTROL 2 1035000 952 26 343 248 630 0 83 270000 176 23 102 119 361 0 56 CONTROL 3 1035000 1284 22 470 300 770 0 83 270000 353 19 169 142 371 0 30 231 APPENDIX 3-10 Analysis of variance to test the significance of the effects of treatment type (windrow burn vs knockdown and broadcast burn) and fire severity on nutrient changes, both absolute and relative, in slash, forest floor and slash and forest floor combined. 232 ONE WAY ANALYSIS OF VARIANCE FOR NITROGEN DIFFERENCES IN PREBURN FOREST FLOOR IN BROADCAST BURN EXPERIMENTAL PLOTS. DEP VAR: N N SOURCE SUM-OF-SQUARES IMPACT 84083.500 9 MULT IPLE R: .578 ANALYSIS OF VARIANCE D F MEAN-SQUARE 3 28027.833 SQUARED MULTIPLE R .335 F - RAT I 0 0.838 P 0.528 ERROR 167282.500 33456.500 DURBIN-WATSON D STATISTIC FIRST ORDER AUTOCORRELATION 3.181 - .653 ONE WAY ANALYSIS OF VARIANCE FOR PHOSPHORUS DIFFERENCES IN PREBURN FOREST FLOOR IN BROADCAST BURN EXPERIMENTAL PLOTS. DEP VAR: MULTIPLE R: 575 SQUARED MULTIPLE R: .331 SOURCE SUM-OF-SQUARES IMPACT 507.056 ERROR 1026.500 DURBIN-WATSON D STATISTIC FIRST ORDER AUTOCORRELATION ANALYSIS OF VARIANCE DF MEAN-SQUARE 3 169.019 5 205.300 3 . 183 - .656 F - RAT I 0 0.823 P 0 .535 ONE WAY ANALYSIS OF VARIANCE FOR POTASSIUM DIFFERENCES IN PREBURN FOREST FLOOR IN BROADCAST BURN EXPERIMENTAL PLOTS. DEP VAR: MULTIPLE R: .569 SQUARED MULTIPLE R: .324 SOURCE SUM-OF-SQUARES IMPACT 504.000 ERROR 1050.000 ANALYSIS OF VARIANCE DF MEAN-SQUARE F-RATIO 3 168.000 0.800 5 210.000 P 0.545 DURBIN-WAT SON D STATISTIC 3.171 FIRST ORDER AUTOCORRELATION -.654 233 ONE WAY ANALYSIS OF VARIANCE FOR SODIUM DIFFERENCES IN PREBURN FOREST FLOOR IN BROADCAST BURN EXPERIMENTAL PLOTS. DEP VAR: NA N: 9 MULTIPLE R: .622 SQUARED MULTIPLE R: .387 ANALYSIS OF VARIANCE SOURCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO P IMPACT 7.056 3 2.352 1.053 0.446 ERROR 11.167 5 2.233 DURB I N - WATSON D STATISTIC 3.368 FIRST ORDER AUTOCORRELATION -.734 ONE WAY ANALYSIS OF VARIANCE FOR MAGNESIUM DIFFERENCES IN PREBURN FOREST FLOOR IN BROADCAST BURN EXPERIMENTAL PLOTS. DEP VAR: MG N: 9 MULTIPLE R: .574 SQUARED MULTIPLE R: .329 SOURCE SUM-OF-SQUARES IMPACT 340.500 ERROR 693.500 ANALYSIS OF VARIANCE DF MEAN-SQUARE 3 113.500 5 138.700 F-RATIO 0.818 P 0.537 DURB I N - WATSON D STATISTIC 3.212 FIRST ORDER AUTOCORRELATION -.671 ONE WAY ANALYSIS OF VARIANCE FOR CALCIUM DIFFERENCES IN PREBURN FOREST FLOOR IN BROADCAST BURN EXPERIMENTAL PLOTS. DEP VAR: CA N : MULTIPLE R: , 581 SQUARED MULTIPLE R: ,337 ANALYSIS OF VARIANCE SOURCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO P IMPACT 3786.722 3 1262.241 0.849 0.524 ERROR 7435.500 5 1487.100 DURBIN-WATSON D STATISTIC 3.176 FIRST ORDER AUTOCORRELATION -.650 234 ONE WAY ANALYSIS OF VARIANCE FOR SULPHUR DIFFERENCES IN PREBURN FOREST FLOOR IN BROADCAST BURN EXPERIMENTAL PLOTS. DEP VAR: MULT I PLE R: ,581 SQUARED MULTIPLE R ,337 SOURCE SUM-OF-SQUARES IMPACT ERROR 510.889 1004.000 ANALYSIS OF VARIANCE DF MEAN-SQUARE 170.296 200.800 F-RATIO 0 . 848 P 0.524 DURBIN-WAT SON D STATISTIC 3.194 FIRST ORDER AUTOCORRELATION -.657 ONE WAY ANALYSIS OF VARIANCE FOR IMMEDIATE POSTBURN FOREST FLOOR NITROGEN CHANGES IN BROADCAST BURN EXPERIMENTAL PLOTS. DEP VAR: MULTIPLE R: 574 SQUARED MULTIPLE R : ,330 SOURCE SUM-OF-SQUARES IMPACT 27627.056 -ERROR 56157.167 ANALYSIS OF VARIANCE DF MEAN-SQUARE F-RATIO 3 9209.019 0.820 5 11231.433 0 .536 DURBIN-WATSON D STATISTIC 3.052 FIRST ORDER AUTOCORRELATION -.613 ONE WAY ANALYSIS OF VARIANCE FOR IMMEDIATE POSTBURN FOREST FLOOR PHOSPHORUS CHANGES IN BROADCAST BURN EXPERIMENTAL PLOTS. DEP VAR: N : MULTIPLE R; , 745 SQUARED MULTIPLE R: ,554 SOURCE SUM-OF-SQUARES IMPACT 171.222 ERROR 137.667 DURBIN-WATSON D STATISTIC FIRST ORDER AUTOCORRELATION ANALYSIS OF VARIANCE DF MEAN-SQUARE 3 57.074 5 27.533 2.377 - .253 F-RATIO 2 .073 P 0 .223 235 ONE WAY ANALYSIS OF VARIANCE FOR IMMEDIATE POSTBURN FOREST FLOOR POTASSIUM CHANGES IN BROADCAST BURN EXPERIMENTAL PLOTS. DEP VAR MULTIPLE R: , 896 SQUARED MULTIPLE R ,803 SOURCE SUM-OF-SQUARES IMPACT 435.722 ERROR 107.167 ANALYSIS OF VARIANCE DF MEAN-SQUARE 3 145.241 5 21.433 F - RAT I 0 6 . 776 P 0 . 033 DURBIN-WATSON D STATISTIC 2.725 FIRST ORDER AUTOCORRELATION -.398 ONE WAY ANALYSIS OF VARIANCE FOR IMMEDIATE POSTBURN FOREST FLOOR SODIUM CHANGES IN BROADCAST BURN EXPERIMENTAL PLOTS. DEP VAR: NA N : MULTIPLE R: .898 SQUARED MULTIPLE R: 806 SOURCE SUM-OF-SQUARES IMPACT 46.389 ERROR 11.167 DURBIN-WATSON D STATISTIC FIRST ORDER AUTOCORRELATION ANALYSIS OF VARIANCE DF MEAN-SQUARE F-RATIO 3 15.463 6.924 5 2.233 3.458 - .749 P 0.031 ONE WAY ANALYSIS OF VARIANCE FOR IMMEDIATE POSTBURN FOREST FLOOR MAGNESIUM CHANGES IN BROADCAST BURN EXPERIMENTAL PLOTS. DEP VAR: MG MULTIPLE R: .798 SQUARED MULTIPLE R: , 637 ANALYSIS OF VARIANCE SOURCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO P IMPACT 43.056 3 14.352 2.929 0.139 ERROR 24.500 5 4.900 DURBIN-WATSON D STATISTIC FIRST ORDER AUTOCORRELATION 2 .714 - .398 236 ONE WAY ANALYSIS OF VARIANCE FOR IMMEDIATE POSTBURN FOREST FLOOR CALCIUM CHANGES IN BROADCAST BURN EXPERIMENTAL PLOTS. DEP VAR: CA N: 9 MULTIPLE R: .938 SQUARED MULTIPLE R: .880 ANALYSIS OF VARIANCE SOURCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO P IMPACT 75943.722 3 25314.574 12.188 0.010 ERROR 10385.167 5 2077.033 DURBIN-WATSON D STATISTIC 3.348 FIRST ORDER AUTOCORRELATION -.684 ONE WAY ANALYSIS OF VARIANCE FOR IMMEDIATE POSTBURN FOREST FLOOR SULPHUR CHANGES IN BROADCAST BURN EXPERIMENTAL PLOTS. DEP VAR: S N: 9 MULTIPLE R: .685 SQUARED MULTIPLE R,: .469 SOURCE SUM-OF-SQUARES IMPACT 364.389 ... ERROR 413. 167 DURBIN-WATSON D STATISTIC FIRST ORDER AUTOCORRELATION ANALYSIS OF VARIANCE DF MEAN-SQUARE F-RATIO 3 1 21 .463 1 .470 5 82.633 2.934 - . 526 P 0.329 ONE WAY ANALYSIS OF VARIANCE FOR ONE YEAR POSTBURN FOREST FLOOR NITROGEN CHANGES IN BROADCAST BURN EXPERIMENTAL PLOTS. DEP VAR: MULTIPLE R: ,665 SQUARED MULTIPLE R: .442 ANALYSIS OF VARIANCE SOURCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO P IMPACT 41306.389 3 13768.796 1.323 0.365 ERROR 52050.500 5 10410.100 DURBIN-WATSON D STATISTIC 2.971 FIRST ORDER AUTOCORRELATION -.543 237 ONE WAY A N A L Y S I S OF V A R I A N C E FOR ONE YEAR POSTBURN F O R E S T FLOOR PHOSPHORUS CHANGES IN B R O A D C A S T BURN E X P E R I M E N T A L P L O T S . SQUARED M U L T I P L E R: DEP VAR: P N: 9 M U L T I P L E R: . 6 5 3 A N A L Y S I S OF V A R I A N C E S OURCE S U M - O F - S Q U A R E S DF MEAN-SQUARE F - R A T I O P I M P A C T 1 5 2 . 8 8 9 3 5 0 . 9 6 3 1 . 2 3 7 0 . 3 8 9 ERROR 2 0 6 . 0 0 0 5 4 1 . 2 0 0 ,426 D URBIN-WATSON D S T A T I S T I C 2 . 6 4 6 F I R S T ORDER A U T O C O R R E L A T I O N - . 4 1 3 ONE WAY A N A L Y S I S OF V A R I A N C E FOR ONE YEAR POSTBURN F O R E S T FLOOR P O T A S S I U M C H A N G E S IN B R O A D C A S T BURN E X P E R I M E N T A L P L O T S . DEP VAR: M U L T I P L E R: , 7 3 3 SQUARED M U L T I P L E R ,538 S OURCE S U M - O F - S Q U A R E S I M P A C T 1 5 4 . 8 3 3 ERROR 1 3 3 . 1 6 7 D URBIN-WATSON D S T A T I S T I C F I R S T ORDER A U T O C O R R E L A T I O N A N A L Y S I S OF V A R I A N C E D F MEAN - SQUARE 3 5 1.611 5 2 6 . 6 3 3 3 . 3 9 1 - . 7 2 2 F - R A T I O 1 . 9 3 8 P 0 . 2 4 2 ONE WAY A N A L Y S I S OF V A R I A N C E FOR ONE YEAR POSTBURN F O R E S T FLOOR M A G N E S I U M CHANGES IN B R O A D C A S T BURN E X P E R I M E N T A L P L O T S . DEP VAR; MG M U L T I P L E R: .670 SQUARED M U L T I P L E R: .449 A N A L Y S I S OF V A R I A N C E S O U R C E S U M - O F - S Q U A R E S DF MEAN-SQUARE F - R A T I O P I M P A C T 3 1 . 5 5 6 3 1 0 . 5 1 9 1 . 3 6 0 0 . 3 5 5 ERROR 3 8 . 6 6 7 5 7 . 7 3 3 D U R BIN-WATSON D S T A T I S T I C F I R S T ORDER A U T O C O R R E L A T I O N 3 . 1 0 6 - . 5 8 9 238 ONE WAY ANALYSIS OF VARIANCE FOR ONE YEAR POSTBURN FOREST FLOOR CALCIUM CHANGES IN BROADCAST BURN EXPERIMENTAL PLOTS. DEP VAR: CA N: 9 MULTIPLE R: .847 SQUARED MULTIPLE R: .718 ANALYSIS OF VARIANCE SOURCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO P IMPACT 2904.333 3 968.111 4.247 0.077 ERROR 1139.667 5 227.933 DURBIN-WATSON D STATISTIC 3.497 FIRST ORDER AUTOCORRELATION -.815 ONE WAY ANALYSIS OF VARIANCE FOR ONE YEAR POSTBURN FOREST FLOOR SODIUM CHANGES IN BROADCAST BURN EXPERIMENTAL PLOTS. DEP VAR: NA N: 9 MULTIPLE R: .684 SQUARED MULTIPLE R: .468 ANALYSIS OF VARIANCE SOURCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO P IMPACT 3.222 3 1.074 1.465 0.330 ERROR 3.667 5 0.733 DURBIN-WATSON D STATISTIC 2.008 FIRST ORDER AUTOCORRELATION - . 053-ONE WAY ANALYSIS OF VARIANCE FOR ONE YEAR POSTBURN FOREST FLOOR SULPHUR CHANGES IN BROADCAST BURN EXPERIMENTAL PLOTS. DEP VAR: S N: 9 MULTIPLE R: .669 SQUARED MULTIPLE R: .447 ANALYSIS OF VARIANCE SOURCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO P IMPACT 350.833 3 116.944 1.350 0.358 ERROR 433.167 5 86.633 DURBIN-WATSON D STATISTIC 2.846 FIRST ORDER AUTOCORRELATION -.442 239 TWO WAY ANALYSIS OF VARIANCE FOR NITROGEN CHANGES IN FOREST FLOOR DEP VAR: F FL N : 17 MULTIPLE R: .893 SQUARED MULTIPLE R: . 798 ANALYSIS OF VARIANCE SOURCE SUM - OF - SQUARES DF MEAN-SQUARE F-RATIO P IMPACT 78689.068 3 26229.689 1 .963 0.190 TRT 264762 . 240 1 264762.240 19.810 0.002 IMPACT* TRT 144681 .959 3 48227.320 3.608 0.059 ERROR 120288.357 9 13365.373 TWO WAY ANALYSIS OF VARIANCE FOR RELATIVE NITROGEN CHANGES IN FOREST FLOOR DEP VAR: PFFL N : 17 MULTIPLE R: .966 SQUARED MULTIPLE R: . 933 ANALYSIS OF VARIANCE SOURCE SUM- OF - SQUARES DF MEAN-SQUARE F-RATIO P IMPACT 204 . 243 3 68.081 1 . 146 0.382 TRT 6813.197 1 6813.197 114. 702 0.000 IMPACT* TRT 321.060 3 107.020 1 .802 0.217 ERROR 534.591 9 59.399 TWO WAY ANALYSIS OF VARIANCE FOR PHOSPHORUS CHANGES IN FOREST FLOOR DEP VAR: FFL N : 17 MULTIPLE R: .964 SQUARED MULTIPLE R: .929 ANALYSIS OF VARIANCE SOURCE SUM - OF - SQUARES DF MEAN-SQUARE F-RATIO P IMPACT 486.584 3 162.195 3.512 0 . 062 TRT 4023.000 1 4023.000 87.113 0.000 IMPACT* TRT 937.581 3 312.527 6.767 0.011 ERROR 415 .632 9 46.181 240 TUO WAY ANALYSIS OF VARIANCE FOR RELATIVE PHOSPHORUS CHANGES IN FOREST FLOOR DEP VAR: PFFL N: 17 MULTIPLE R: .973 SQUARED MULTIPLE R: .946 SOURCE IMPACT TRT IMPACT* TRT ERROR SUM-OF-SQUARES 536.456 14811.278 139.028 904.961 ANALYSIS OF VARIANCE DF MEAN-SQUARE 178.819 14811.278 46.343 100.551 F- RAT I 0 1 . 778 147.301 0.461 0.221 0.000 0.716 TWO WAY ANALYSIS OF VARIANCE FOR P0TASS I UM CHANGES IN FOREST FLOOR DEP VAR: FFL N: 17 MULTIPLE R: .981 SQUARED MULTIPLE R: ,963 SOURCE IMPACT TRT IMPACT* TRT ERROR ANALYSIS OF VARIANCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO 478.401 3 8883.274 1 1143.241 3 417.367 9 159.467 8883.274 381 .080 46.374 3 .439 191.557 8.218 0 .065 0.000 0 . 006 TWO WAY ANALYSIS OF VARIANCE FOR RELATIVE POTASSIUM CHANGES IN FOREST FLOOR DEP VAR: PFFL N: 17 MULTIPLE R: .992 SQUARED MULTIPLE R: .985 SOURCE IMPACT TRT IMPACT* TRT ERROR ANALYSIS OF VARIANCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO 1435.262 3 41392.029 1 1461.595 3 712.667 9 478.421 41392 . 029 487. 198 79.185 6.042 522.724 6. 153 0.015 0.000 0.015 241 TWO WAY ANALYSIS OF VARIANCE FOR SODIUM CHANGES IN FOREST FLOOR DEP VAR: FFL N: 17 MULTIPLE R: .973 SQUARED MULTIPLE R: .946 SOURCE SUM-OF-SQUARES IMPACT TRT IMPACT* TRT ERROR 27.122 186.204 31.917 14.632 ANALYSIS OF VARIANCE DF MEAN-SQUARE 9.041 186. 204 10.639 1 .626 F-RATIO 5.561 114.535 6.544 0.019 0.000 0.012 TWO WAY ANALYSIS OF VARIANCE FOR RELATIVE SODIUM CHANGES IN FOREST FLOOR DEP VAR: PFFL N: 17 MULTIPLE R: .996 SQUARED MULTIPLE R: .992 SOURCE IMPACT TRT IMPACT* TRT ERROR ANALYSIS OF VARIANCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO 221.262 3 73.754 1.955 38567.022 1 38567.022 1022.395 577.357 3 339.500 9 192.452 37.722 5.102 0.191 0.000 0.025 TWO WAY ANALYSIS OF VARIANCE FOR MAGNESIUM CHANGES IN FOREST FLOOR DEP VAR: FFL N: 17 MULTIPLE R: .977 SQUARED MULTIPLE R: .955 SOURCE IMPACT TRT IMPACT* TRT ERROR ANALYSIS OF VARIANCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO 456.231 3 5114.261 1 363.915 3 276.602 9 152.077 5114.261 121 .305 30.734 4 . 948 166.407 3.947 0.027 0.000 0.047 242 ONE WAY ANALYSIS OF VARIANCE FOR RELATIVE MAGNESIUM CHANGES IN FOREST FLOOR DEP VAR: PFFL N: 17 MULTIPLE R: .988 SQUARED MULTIPLE R: .976 SOURCE SUM-OF-SQUARES IMPACT TRT IMPACT* TRT ERROR 555.548 34469.283 397.833 861.500 ANALYSIS OF VARIANCE DF MEAN-SQUARE 185.183 34469.283 132.611 95.722 F-RATIO 1 .935 360.097 1 .385 0.195 0.000 0.309 TWO WAY ANALYSIS OF VARIANCE FOR CALCIUM CHANGES IN FOREST FLOOR DEP VAR: FFL N: 17 MULTIPLE R: .978 SQUARED MULTIPLE R: .957 SOURCE IMPACT TRT IMPACT* TRT ERROR ANALYSIS OF VARIANCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO 1144.613 3 381.538 48074.134 1 48074.134 11735.680 3 2922.702 9 3911.893 324.745 1 . 175 148.037 1 2 .046 0.372 0.000 0.002 TWO WAY ANALYSIS OF VARIANCE FOR RELATIVE CALCIUM CHANGES IN FOREST FLOOR DEP VAR: PFFL N: 17 MULTIPLE R: .990 SQUARED MULTIPLE R: .981 SOURCE IMPACT TRT IMPACT* TRT ERROR ANALYSIS OF VARIANCE SUM-OF-SQUARES DF MEAN - SQUARE F-RATIO 2195.190 3 731.730 27695.833 1 27695.833 2571.524 3 710.167 9 857.175 78 . 907 9 . 273 350.992 10.863 0.004 0.000 0.002 TWO WAY ANALYSIS OF DEP VAR: FFL 243 VARIANCE FOR SULPHUR CHANGES IN FOREST FLOOR N: 17 MULTIPLE R: .886 SQUARED MULTIPLE R: .785 ANALYSIS OF VARIANCE SOURCE IMPACT TRT IMPACT* TRT ERROR SUM-OF-SQUARES 517.875 1376.244 1005.882 773.017 DF MEAN-SQUARE 172.625 1376.244 335.294 85.891 F-RATIO 2.010 16.023 3.904 0.183 0.003 0 . 049 TWO WAY ANALYSIS OF VARIANCE FOR RELATIVE SULPHUR CHANGES IN FOREST FLOOR DEP VAR: PFFL N: 17 MULTIPLE R: .965 SQUARED MULTIPLE R: .931 SOURCE IMPACT TRT IMPACT* TRT ERROR ANALYSIS OF VARIANCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO 431.248 3 6652.269 1 88.544 3 542.773 9 143.749 6652 . 269 29.515 60.308 2 .384 1 1 0.305 0.489 0.137 0.000 0 .698 TWO WAY ANALYSIS OF VARIANCE FOR NITROGEN LOSSES FROM SLASH ' DEP VAR: SLASHL N: 17 MULTIPLE R: .880 SQUARED MULTIPLE R ,775 SOURCE IMPACT TRT IMPACT* TRT ERROR SUM-OF-SQUARES 32639.887 1 2781 .5 1 9 ANALYSIS OF VARIANCE DF MEAN-SQUARE F-RATIO 2160.719 3 13339.905 9 10879.962 12781.519 720 . 240 1482.212 7.340 8.623 0.486 0.009 0.017 0 . 700 TWO WAY ANALYSIS OF DEP VAR: PSLASHL VARIANCE FOR RELATIVE NITROGEN N: 17 MULTIPLE R: .940 LOSSES FROM SLASH SQUARED MULTIPLE R: .884 ANALYSIS OF VARIANCE SOURCE IMPACT TRT IMPACT* TRT ERROR SUM-OF -SQUARES 58.262 467.066 18.530 71.807 DF MEAN - SQUARE 19.421 467.066 6. 177 7.979 F-RATIO 2.434 58.540 0 . 774 0.132 0.000 0.537 TWO WAY ANALYSIS OF VARIANCE FOR PHOSPHORUS LOSSES FROM SLASH DEP VAR: SLASHL N: 17 MULTIPLE R: .911 SQUARED MULTIPLE R .831 SOURCE IMPACT TRT IMPACT* TRT ERROR ANALYSIS OF VARIANCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO 672.997 3 152.776 1 30.177 3 167.450 9 224.332 152.776 10 . 059 18.606 12.057 8.211 0.541 0.002 0.019 0.666 TWO WAY ANALYSIS OF VARIANCE FOR RELATIVE PHOSPHORUS LOSSES FROM SLASH DEP VAR: PSLASHL N: 17 MULTIPLE R: .877 SQUARED MULTIPLE R: .769 SOURCE IMPACT TRT IMPACT* TRT ERROR ANALYSIS OF VARIANCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO 268.752 3 405.820 1 66.037 3 223.138 9 89.584 405 .820 22.012 24.793 3.613 16.368 0.888 0.058 0.003 0 .484 TWO WAY A N A L Y S I S OF D E P V A R : S L A S H L V A R I A N C E FOR P O T A S S I U M L O S S E S N : 1 7 M U L T I P L E R : . 9 0 8 F R O M S L A S H S Q U A R E D M U L T I P L E R: . 8 2 4 S O U R C E I M P A C T T R T I M P A C T * T R T E R R O R S U M - O F - S Q U A R E S 1 4 9 9 . 7 3 5 2 1 9 6 . 8 1 4 1 1 5 . 0 1 9 7 7 6 . 8 6 7 A N A L Y S I S OF V A R I A N C E D F M E A N - S Q U A R E F - R A T I O 4 9 9 . 9 1 2 2 1 9 6 . 8 1 4 3 8 . 3 4 0 8 6 . 3 1 9 5 . 7 9 1 2 5 . 4 5 0 0 . 4 4 4 0 . 0 1 7 0 . 0 0 1 0 . 7 2 7 TWO WAY A N A L Y S I S OF V A R I A N C E F O R R E L A T I V E P O T A S S I U M L O S S E S F R O M S L A S H D E P V A R : P S L A S H L N : 1 7 M U L T I P L E R : . 9 4 3 S Q U A R E D M U L T I P L E R: . 8 8 9 S O U R C E I M P A C T T R T I M P A C T * T R T E R R O R S U M - O F - S Q U A R E S 7 . 5 1 0 2 1 5 . 2 5 0 1 1 . 5 3 6 3 0 . 3 1 8 A N A L Y S I S O F V A R I A N C E D F M E A N - S Q U A R E 3 2 . 5 0 3 1 2 1 5 . 2 5 0 3 . 8 4 5 3 . 3 6 9 F - R A T I O 0 . 7 4 3 6 3 . 8 9 8 1 . 1 4 2 0 . 5 5 3 0 . 0 0 0 0 . 3 8 4 TWO WAY A N A L Y S I S O F V A R I A N C E FOR S O D I U M L O S S E S F R O M S L A S H D E P V A R : S L A S H L N : 1 7 M U L T I P L E R : . 9 1 0 S Q U A R E D M U L T I P L E R . 8 2 8 S O U R C E I M P A C T T R T I M P A C T * T R T E R R O R A N A L Y S I S O F V A R I A N C E S U M - O F - S Q U A R E S DF M E A N - S Q U A R E F - R A T I O 8 . 7 9 9 3 7 . 0 5 4 1 1 . 2 3 9 3 3 . 4 3 0 9 2 . 9 3 3 7 . 0 5 4 0 . 4 1 3 0 . 3 8 1 7 . 6 9 6 1 8 . 5 0 9 1 . 0 8 4 0 . 0 0 7 0 . 0 0 2 0 . 4 0 4 246 TWO WAY ANALYSIS OF VARIANCE FOR RELATIVE SODIUM LOSSES FROM SLASH DEP VAR: PSLASHL N : 17 MULTIPLE R: .959 SQUARED MULTIPLE R: .920 ANALYSIS OF VARIANCE SOURCE SUM- OF - SQUARES DF MEAN-SQUARE F-RATIO P IMPACT 411.793 3 137.264 5.490 0.020 TRT 1860.103 1 1860.103 74.396 0.000 IMPACT* TRT 323 .848 3 107.949 4.318 0.038 ERROR 225.023 9 25.003 TWO WAY ANALYSIS OF VARIANCE FOR MAGNESIUM LOSSES FROM SLASH DEP VAR: SLASHL N : 17 MULTIPLE R: .874 SQUARED MULTIPLE R: . 763 -ANALYSIS OF VARIANCE -SOURCE SUM- OF -SQUARES DF MEAN-SQUARE F-RATIO P IMPACT 972.091 3 324.030 5.590 0.019 TRT 743.421 1 743.421 12.824 0.006 IMPACT* TRT 41 .435 3 13.812 0 . 238 0 . 868 ERROR 521.722 9 57.969 TWO WAY ANALYSIS OF VARIANCE FOR RELATIVE MAGNESIUM LOSSES FROM SLASH DEP VAR: PSLASHL N : 17 MULTIPLE R: .964 SQUARED MULTIPLE R: .930 ANALYSIS OF VARIANCE SOURCE SUM- OF -SQUARES DF MEAN-SQUARE F-RATIO P IMPACT 45.083 3 15.028 1 . 066 0.411 TRT 1 606. 247 1 1606.247 113.946 0.000 IMPACT* TRT 63.726 3 21.242 1.507 0 . 278 ERROR 126.869 9 14.097 247 TWO WAY ANALYSIS OF VARIANCE FOR CALCIUM LOSSES FROM SLASH DEP VAR: SLASHL N: 17 MULTIPLE R: .809 SQUARED MULTIPLE R: .655 ANALYSIS OF VARIANCE SOURCE SUM- OF - SQUARE S DF MEAN-SQUARE F -RATIO P IMPACT 3657.309 3 1219.103 1.250 0.348 TRT 1 2741 .130 1 12741.130 13.059 0.006 IMPACT* TRT 862 . 140 3 287.380 0.295 0.828 ERROR 8781.030 9 975.670 TWO WAY ANALYSIS OF VARIANCE FOR RELATIVE CALCIUM LOSSES FROM SLASH DEP VAR: PSLASHL N : 17 MULTIPLE R: .959 SQUARED MULTIPLE R: .919 ANALYSIS OF VARIANCE SOURCE SUM- OF -SQUARES D F MEAN - SQUARE F -RATIO P IMPACT 91 .329 3 30.443 1 . 065 0.411 TRT 2697.615 1 2697.615 94.385 0.000 IMPACT* TRT 63.097 3 21 .032 0 . 736 0.557 ERROR 257.229 9 28.581 TWO WAY ANALYSIS OF VARIANCE FOR SULPHUR LOSSES FROM SLASH DEP VAR: SLASHL N: 17 MULTIPLE R: .951 SQUARED MULTIPLE R: .905 ANALYSIS OF VARIANCE SOURCE SUM- OF -SQUARES D F MEAN- SQUARE F -RATIO P IMPACT 968 . 943 3 322.981 15.584 0.001 TRT 724.052 1 724 . 052 34.937 0.000 IMPACT* TRT 151.341 3 50.447 2 .434 0.132 ERROR 186.522 9 20.725 248 TWO WAY ANALYSIS OF VARIANCE FOR RELATIVE SULPHUR LOSSES FROM SLASH DEP VAR: PSLASHL N: 17 MULTIPLE R: .962 SQUARED MULTIPLE R: ,925 SOURCE SUM-OF-SQUARES IMPACT TRT IMPACT* TRT ERROR 808.024 2004.899 739.595 274.667 ANALYSIS OF VARIANCE DF MEAN-SQUARE 269.341 2004.899 246. 532 30.519 F- RAT I 0 8 .826 65.694 8.078 0.005 0.000 0 .006 TWO WAY ANALYSIS OF VARIANCE FOR NITROGEN LOSSES FROM ORGANIC MATTER DEP VAR: TOTAL N: 17 MULTIPLE R: .901 SQUARED MULTIPLE R: .812 SOURCE IMPACT TRT IMPACT* TRT ERROR ANALYSIS OF VARIANCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO 149173.469 3 49724.490 247158.957 1 247158.957 114233.308 3 38077.769 111958.507 9 12439.834 3.997 19.868 3.061 0 . 046 0.002 0 . 084 TWO WAY ANALYSIS OF VARIANCE FOR RELATIVE NITROGEN LOSSES FROM ORGANIC MATTER DEP VAR: PTOTALL N: 17 MULTIPLE R: .962 SQUARED MULTIPLE R: .926 SOURCE SUM-OF-SQUARES ANALYSIS OF VARIANCE DF MEAN-SQUARE IMPACT TRT IMPACT* TRT ERROR 32.679 1739.713 83.363 148.761 10.893 1739.713 27.788 16.529 F-RATIO 0.659 1 05 . 252 1 .681 0.598 0.000 0.240 TWO WAY A N A L Y S I S OF DEP V A R : T O T A L V A R I A N C E FOR PHOSPHORUS L O S S E S N: 17 M U L T I P L E R: . 9 6 4 FROM ORGANIC MATTER SQUARED M U L T I P L E R: 249 .929 A N A L Y S I S OF V A R I A N C E SOURCE IMPACT TRT I M P A C T * TRT ERROR S U M - O F - S Q U A R E S 1 8 2 8 . 9 6 0 4291 . 9 1 4 1 0 2 1 . 6 9 9 5 2 4 . 6 8 7 DF M E A N - S Q U A R E 6 0 9 . 6 5 3 4 2 9 1 . 9 1 4 3 4 0 . 5 6 6 5 8 . 2 9 9 F - R A T I O 1 0 . 4 5 7 7 3 . 6 2 0 5 . 8 4 2 0 . 0 0 3 0 . 0 0 0 0 . 0 1 7 TWO WAY A N A L Y S I S OF V A R I A N C E FOR R E L A T I V E PHOSPHORUS L O S S E S FROM ORGANIC MATTER DEP V A R : P T O T A L L N: 17 M U L T I P L E R: . 9 6 4 SQUARED M U L T I P L E R: . 9 3 0 SOURCE IMPACT TRT I M P A C T * TRT ERROR A N A L Y S I S OF V A R I A N C E S U M - O F - S Q U A R E S DF M E A N - S Q U A R E F - R A T I O 1 2 4 . 6 5 9 3 3 5 7 1 . 7 5 6 1 1 4 . 4 9 2 3 2 8 3 . 4 4 5 9 4 1 . 5 5 3 3 5 7 1 . 7 5 6 4 . 8 3 1 31 . 4 9 4 1 . 3 1 9 1 1 3 . 4 1 1 0 . 153 0 . 3 2 7 0 . 0 0 0 0 . 9 2 5 TWO WAY A N A L Y S I S OF V A R I A N C E FOR P O T A S S I U M L O S S E S FROM ORGANIC MATTER DEP V A R : T O T A L N: 17 M U L T I P L E R: . 9 7 7 SQUARED M U L T I P L E R: . 9 5 5 SOURCE IMPACT TRT I M P A C T * TRT ERROR A N A L Y S I S OF V A R I A N C E S U M - O F - S Q U A R E S DF M E A N - S Q U A R E F - R A T I O 2 7 8 2 . 4 3 3 3 9 2 7 . 4 7 8 1 9 2 8 8 . 3 5 0 1 1 9 2 8 8 . 3 5 0 1 7 7 8 . 0 5 0 3 1 1 1 3 . 0 1 2 9 5 9 2 . 6 8 3 1 2 3 . 6 6 8 7 . 5 0 0 1 5 5 . 9 6 9 4 . 793 0 . 008 0 . 0 0 0 0 . 0 2 9 TWO WAY ANALYSIS OF DEP VAR: PTOTALL VARIANCE FOR RELATIVE POTASSIUM N: 17 MULTIPLE R: .986 250 LOSSES FROM ORGANIC MATTER SQUARED MULTIPLE R: .973 ANALYSIS OF VARIANCE SOURCE IMPACT TRT IMPACT* TRT ERROR SUM-OF-SQUARES 184.371 8221 . 955 210.465 247.888 DF MEAN-SQUARE 3 61.457 1 8221.955 3 70.155 9 27.543 F-RATIO 2.231 298.512 2.547 0.154 0.000 0.121 TWO WAY ANALYSIS OF VARIANCE FOR SODIUM LOSSES FROM ORGANIC MATTER DEP VAR: TOTAL N: 17 MULTIPLE R: .909 SQUARED MULTIPLE R: .826 SOURCE IMPACT TRT IMPACT* TRT ERROR SUM-OF-SQUARES 18.209 209.420 9.863 49.527 ANALYSIS OF VARIANCE DF MEAN-SQUARE 6.070 209.420 .288 5.503 F-RATIO 1.103 38.056 0.597 0.397 0.000 0 . 633 TWO WAY ANALYSIS OF VARIANCE FOR RELATIVE SODIUM LOSSES FROM ORGANIC MATTER DEP VAR: PTOTALL N: 17 MULTIPLE R: .978 SQUARED MULTIPLE R: .956 SOURCE IMPACT TRT IMPACT* TRT ERROR ANALYSIS OF VARIANCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO 233.309 3 77.770 10309.249 1 10309.249 624.963 3 526.283 9 208.321 58.476 1.330 176.299 3 .563 0.324 0.000 0 . 060 251 TWO WAY ANALYSIS OF VARIANCE FOR MAGNESIUM LOSSES FROM ORGANIC MATTER DEP VAR: TOTAL N : 17 MULTIPLE R: .963 SQUARED MULTIPLE R; .928 ANALYSIS OF VARIANCE SOURCE SUM -OF -SQUARES DF MEAN-SQUARE F -RATIO P IMPACT 21 06 . 207 3 702.069 7.280 0.009 TRT 9287.322 1 9287.322 96.301 0.000 IMPACT* TRT 262.346 3 87.449 0.907 0.475 ERROR 867.962 9 96.440 TWO WAY ANALYSIS OF VARIANCE FOR RELATIVE MAGNESIUM LOSSES FROM ORGANIC MATTER DEP VAR: PTOTALL N: 17 MULTIPLE R: .980 SQUARED MULTIPLE R: .960 ANALYSIS OF VARIANCE -SOURCE SUM -OF -SQUARES DF MEAN-SQUARE F -RATIO P IMPACT 35.988 3 11.996 0.430 0 . 737 TRT 5997.428 1 5997.428 214.778 0.000 IMPACT* TRT 71.045 3 23.682 0 . 848 0.502 ERROR 251.314 9 27.924 TWO WAY ANALYSIS OF VARIANCE FOR CALCIUM LOSSES FROM ORGANIC MATTER DEP VAR: TOTAL N : 17 MULTIPLE R: .954 SQUARED MULTIPLE R: .910 ANALYSIS OF VARIANCE SOURCE SUM -OF - SQUARES DF MEAN-SQUARE F -RATIO P IMPACT 2702.864 3 900.955 0.726 0 .562 TRT 100364.540 1 100364.540 80.856 0.000 IMPACT* TRT 7145.664 3 2381 .888 1.919 0. 197 ERROR 11171.447 9 1241.272 252 TWO WAY ANALYSIS OF VARIANCE FOR RELATIVE CALCIUM LOSSES FROM ORGANIC MATTER DEP VAR: PTOTALL N: 17 MULTIPLE R: .980 SQUARED MULTIPLE R: .960 SOURCE IMPACT TRT IMPACT* TRT ERROR SUM-OF-SQUARES 35.988 5997.428 ANALYSIS OF VARIANCE DF MEAN-SQUARE 71.045 3 251.314 9 11.996 5997.428 23.682 27.924 F-RATIO 0.430 214.778 0.848 0.737 0.000 0.502 TWO WAY ANALYSIS OF VARIANCE FOR SULPHUR LOSSES FROM ORGANIC MATTER DEP VAR: TOTAL N: 17 MULTIPLE R: .940 SQUARED MULTIPLE R: .884 SOURCE IMPACT TRT IMPACT* TRT ERROR ANALYSIS OF VARIANCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO 2451.410 3 3033.399 1 1119.661 825 .447 3 9 817.137 3033.399 373.220 91.716 8.909 33.074 4 . 069 0.005 0.000 0.044 TWO WAY ANALYSIS OF VARIANCE FOR RELATIVE SULPHUR LOSSES FROM ORGANIC MATTER DEP VAR: PTOTALL N: 17 MULTIPLE R: .979 SQUARED MULTIPLE R: .959 SOURCE IMPACT TRT IMPACT* TRT ERROR ANALYSIS OF VARIANCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO 294.146 3 2288.073 1 67.492 3 110.449 9 98.049 2288.073 22.497 12.272 7.990 186.445 1 .833 0 .007 0.000 0.211 253 T.UO WAY ANALYSIS OF VARIANCE FOR MINERAL SOIL NITROGEN CHANGES DEP VAR: N N: 17 MULTIPLE R: .800 SQUARED MULTIPLE R: .641 SOURCE IMPACT TRT IMPACT* TRT ERROR SUM-OF-SQUARES 723499.048 172144.029 328489.524 687277.667 DURBIN-WATSON D STATISTIC FIRST ORDER AUTOCORRELATION ANALYSIS OF VARIANCE DF MEAN-SQUARE F-RATIO 241166.349 172144.029 109496.508 76364. 185 2.553 - .461 3.158 2 .254 1 .434 0 . 079 0. 167 0 . 296 TWO WAY ANALYSIS OF VARIANCE FOR MINERAL SOIL PHOSPHORUS CHANGES '" DEP VAR: P N: 17 MULTIPLE R: .876 SQUARED MULTIPLE R: 767 SOURCE IMPACT TRT IMPACT* TRT ERROR SUM-OF-SQUARES 52 . 690 1371.196 1093.262 797.500 ANALYSIS OF VARIANCE DF MEAN-SQUARE F-RATIO DURBIN-WATSON D STATISTIC 2.914 FIRST ORDER AUTOCORRELATION -.495 17.563 1371.196 364 .421 88.611 0 . 198 1 5 . 474 4.113 0 .895 0 . 003 0 . 043 TWO WAY ANALYSIS OF VARIANCE FOR MINERAL SOIL POTASSIUM CHANGES DEP VAR: K N: 17 MULTIPLE R: .970 SQUARED MULTIPLE R: .941 ANALYSIS OF VARIANCE SOURCE IMPACT TRT IMPACT* TRT ERROR SUM-OF-SQUARES 9567.524 5016.116 25032 . 667 2276.667 DF MEAN-SQUARE 3189.175 5016.116 8344.222 252.963 F-RATIO 12.607 19.829 32.986 0.001 0.002 0.000 254 T.WO WAY ANALYSIS OF VARIANCE FOR MINERAL SOIL MAGNESIUM CHANGES DEP VAR: SOURCE IMPACT TRT IMPACT* TRT ERROR MG N: 17 MULTIPLE R: .966 SQUARED MULTIPLE R: ANALYSIS OF VARIANCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO P .933 40995.381 53966.964 15328.381 7339.167 13665 . 1 27 53966.964 5109.460 815.463 16.758 66. 180 6.266 0.001 0.000 0.014 DURBIN-WATSON D STATISTIC 2.557 FIRST ORDER AUTOCORRELATION -.452 TWO WAY ANALYSIS OF VARIANCE FOR MINERAL SOIL CALCIUM CHANGES DEP VAR: CA N: 17 MULTIPLE R: .968 SQUARED MULTIPLE R: .936 ANALYSIS OF VARIANCE DF MEAN-SQUARE F-RATIO P SOURCE IMPACT TRT IMPACT* TRT ERROR SUM-OF-SQUARES 749805.190 1817467.891 182908.762 178214.500 3 249935.063 1 1817467.891 60969.587 19801 .61 1 12.622 91.784 3 . 079 DURBIN-WATSON D STATISTIC 2.228 FIRST ORDER AUTOCORRELATION -.259 0.001 0.000 0 . 083 TWO WAY ANALYSIS OF VARIANCE FOR MINERAL SOIL MINERALIZABLE NITROGEN CHANGES DEP VAR: MINN N: 17 MULTIPLE R: .889 SQUARED MULTIPLE R: .791 ANALYSIS OF VARIANCE DF MEAN-SQUARE F-RATIO P SOURCE SUM-OF-SQUARES IMPACT TRT IMPACT* TRT ERROR 8.881 0.116 3 .595 3.667 2.960 0.116 1.198 0.407 7. 266 0 . 285 2.942 0.009 0.607 0.091 DURBIN-WATSON D STATISTIC FIRST ORDER AUTOCORRELATION 2.742 - .508 255 TWO WAY ANALYSIS OF VARIANCE FOR MINERAL SOIL SULPHUR CHANGES DEP VAR: S N: 17 MULTIPLE R: .853 SQUARED MULTIPLE R: .728 SOURCE IMPACT TRT IMPACT* TRT ERROR SUM-OF-SQUARES 24759.929 13324.174 1912.262 14456.000 ANALYSIS OF VARIANCE DF MEAN-SQUARE F-RATIO 8253.310 13324.174 637.421 1606.222 5.138 8 .295 0.397 0.024 0.018 0 . 759 DURBIN-WATSON D STATISTIC FIRST ORDER AUTOCORRELATION 2.429 - . 288 256 APPENDIX 3-11 Tukey's (HSD) test of significance of the effects of treatment type (windrow burn vs knockdown and broadcast burn) and fire severity on nutrient changes, both absolute and relative, in slash, forest floor and slash and forest floor combined. 257 Average estimated nutrient losses (kg/ha) from the forest floor for each fire severity combination. T reatment N P K Na Mg Ca S Low s e v e r i t y burns i n f r e s h s l a s h b r o a d c a s t 313a windrow 5 4 6a 15a 41a 9a 41a 0a 4a 5a 35a 22a 1 13a 27a 42a Low s e v e r i t y burns i n cured s l a s h b r o a d c a s t 277a windrow 508a 10a 40a -9a 40a 1 a 4 a - 1 a 33a 42a 111a 19a 40a Moderate s e v e r i t y burns b r o a d c a s t 428a windrow 445a 22a 35a 2a 35a -5a 4a 2a 29a 18a 94a 38a 3*5 a High s e v e r i t y burns b r o a d c a s t 304a windrow 829a 12b 66c -7b 64c -3b 7c 3b 53c -21b 1 73c" 25a 64a - For each nutrient, means followed by the same letter are not significantly different at p< 0.05. 258 Average estimated nutrient losses (kg/ha) from the forest floor in broadcast burns immediately postburn and one year following burning for each fire severity level. T reatment N P K Na Mg Ca S 1) IMMEDIATELY POSTBURN (1987) Low s e v e r i t y burns i n f r e s h s l a s h 313a 15a 8a 0a 5a 22a 27a Low s e v e r i t y burns i n cured s l a s h 277a 10a -9a 1 a - 1a 43a 19a Moderate s e v e r i t y burns 429a 22a 2a -5a 3a - 157a 38a High s e v e r i t y burns 337a 18a -7a -4a 6a - 149a 25a 2) ONE YEAR FOLLOWING Low s e v e r i t y burns i n BURNING f r e s h s l a s h 300a 22a 3a 2a 3a 32a 16a Low s e v e r i t y burns i n cured s l a s h 247a 14a -8a 1 a 4a -41a 16a Moderate s e v e r i t y burns 440a 26a -8a 2a - 1 a - 1 7a 31a High s e v e r i t y burns 356a 22a -5a 1a 5a 4a 16a For each nutrient, means followed by the same letter are not significantly different at p<0.05. Negative values indicate nutrient gains. 259 Average estimated nutrient losses (kg/ha) from slash for each fire severity level. Treatment N P K Na Mg Ca S Low s e v e r i t y burns i n f r e s h s l a s h 265a 30a 58a 5 . 7a 57a 1 70a 34a Low s e v e r i t y burns in cured s l a s h 272ab 25ab 49a 5 .4ab 54a 1 79a 30ab Moderate s e v e r i t y burns 352a 38ac 69a 6 . 9ac 70a 207a 46a High s e v e r i t y burns 361ac 40ac 73a 6 . 7a 72a 1 98a 48ac For each nutrient, means followed by the same letter are not significantly different at p< 0.05. 260 Average estimated total nutrient losses (kg/ha) for each fire severity level. Treatment N P K Na Mg Ca S Low s e v e r i t y burns i in f r e s h s l a s h . 773a 61a 94a 8 .3a 81a 254a 73a Low s e v e r i t y burns i in cured s l a s h 735a 51a 73a 7 . 7a 73a 265a 62a Moderate s e v e r i t y burns 853a 69a 97a 6 . 6a 89a 280a 86a High s e v e r i t y burns 974a 79a 108a 9 .4a 103a 324a 94a For each nutrient, means followed by the same letter are not significantly different at p< 0.05. 261 Average estimated changes in the quantity of nutrients (kg/ha) in the surface 0-15 cm of mineral soil for each fire severity level. T r e a t n e n t N N P M i n e r a l i z a b l e K Mg Ca S Low s e v e r i t y burns i n f r e s h s l a s h 236a 2a 15a 21a -46a - 1 94a 32a Low s e v e r i t y burns i n cured s l a s h 214a 1a 10a 45a -65a - 285a 25ab Moderate s e v e r i t y burns -1 44a 0a 1 1 a -8a -74a - 500a -55ac High s e v e r i t y burns -227a 0a 10a 44a - 1 47a -628a -37a For each nutrient, means followed by the same letter are not significantly different at p < .05. Negative values indicate nutrient gains. APPENDIX 4-1 Two-way analysis of variance results for seedling responses 263 TUO-UAY ANALYSIS OF VARIANCE FOR 1988 SEEDLING SURVIVAL DEP VAR: SUR N : 25 MULTIPLE R: .914 SQUARED MULTIPLE R: .834 ANALYSIS OF VARIANCE SOURCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO IMPACT TRT IMPACT* TRT 541.262 919.632 346.809 180.421 459.816 57.801 6.571 0.006 16.746 0.000 2.105 0.123 ERROR 356.961 13 27.459 DURBIN-WATSON D STATISTIC 2.947 FIRST ORDER AUTOCORRELATION -.513 TWO- WAY ANALYSIS OF VARIANCE FOR 1988 SEEDLING TOTAL HEIGHT DEP VAR: THT88 N: 25 MULTIPLE R: .731 SQUARED MULTIPLE R: .535 ANALYSIS OF VARIANCE SOURCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO P TRT 23.510 2 11.755 3.146 0.077 x IMPACT 16.896 3 5.632 1.508 0.259 TRT* IMPACT 16.825 6 2.804 0.751 0.620 ERROR 48.568 13 3.736 DURBIN-WATSON D STATISTIC 2.928 FIRST ORDER AUTOCORRELATION -.465 TWO-WAY ANALYSIS OF VARIANCE FOR 1988 SEEDLING INCREMENT DEP VAR: INC88 N: 25 MULTIPLE R: .718 SQUARED MULTIPLE R: .516 ANALYSIS OF VARIANCE SOURCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO P TRT 20.590 2 10.295 2.807 0.097 IMPACT 14.274 3 4.758 1.297 0.317 TRT* IMPACT 17.862 6 2.977 0.812 0.579 ERROR 47.680 13 3.668 DURBIN-WATSON D STATISTIC 2.934 FIRST ORDER AUTOCORRELATION -.470 264 TWO WAY A N A L Y S I S OF V A R I A N C E FOR 1988 BASAL D I A M E T E R DEP V A R : C A L 8 8 N: 25 M U L T I P L E R: . 7 8 2 SQUARED M U L T I P L E R: . 6 1 1 SOURCE TRT IMPACT T R T * IMPACT ERROR A N A L Y S I S OF V A R I A N C E S U M - O F - S Q U A R E S DF M E A N - S Q U A R E 3 . 0 9 7 1 . 6 0 1 1 . 5 4 9 0 . 5 3 4 3 . 0 5 4 6 0 . 5 0 9 4 . 8 5 7 13 0 . 3 7 4 F - R A T I O 4.145 1.429 0 . 040 0 . 2 7 9 1.362 0.300 265 APPENDIX 4-2 Two-way analysis of variance for 1988 vegetation biomass 266 TWO WAY ANALYSIS OF VARIANCE FOR 1988 EPILOBIUM BIOMASS DEP VAR: EPIL N: 25 MULTIPLE R: .714 SQUARED MULTIPLE R: .510 ANALYSIS OF VARIANCE DF MEAN-SQUARE F-RATIO P SOURCE IMPACT TRT IMPACT* TRT ERROR SUM-OF-SQUARES 379.535 3 61.850 2 107.395 6 550.555 13 DURBIN-WATSON D STATISTIC 2.645 FIRST ORDER AUTOCORRELATION -.359 126.512 30.925 17.899 42.350 2.987 0 . 730 0.423 0.070 0.501 0.851 TWO WAY ANALYSIS OF VARIANCE FOR 1988 LINNAEA BIOMASS DEP VAR: LINN N: 25 MULTIPLE R: .765 SQUARED MULTIPLE R: 586 ANALYSIS OF VARIANCE SOURCE IMPACT TRT IMPACT* TRT ERROR SUM-OF-SQUARES 37.544 7.266 16.472 42.367 DF MEAN-SQUARE 3 2 6 13 DURBIN-WATSON D STATISTIC 3.025 FIRST ORDER AUTOCORRELATION -.553 12.515 3.633 2 . 745 3 .259 F - RAT I 0 3.840 1.115 0.842 0.036 0.357 0.559 TWO WAY ANALYSIS OF VARIANCE FOR 1988 GRASSES DEP VAR: GRASS N: 25 MULTIPLE R: .726 SQUARED MULTIPLE R: ,527 SOURCE IMPACT TRT I M P AC T * TRT ERROR SUM-OF-SQUARES 126.653 43.75 1 1 85 .469 312.712 ANALYSIS OF VARIANCE DF MEAN-SQUARE F-RATIO 3 2 6 13 42.218 21.876 30.911 24.055 1 . 755 0 . 909 1 .285 0 .205 0.427 0.329 DURBIN-WATSON D STATISTIC FIRST ORDER AUTOCORRELATION 3.184 - . 592 267 TWO WAY ANALYSIS OF VARIANCE FOR 1988 CORNUS BIOMASS DEP VAR: CORNUS N: 25 MULTIPLE R: .767 SQUARED MULTIPLE R: .588 SOURCE SUM-OF-SQUARES ANALYSIS OF VARIANCE DF MEAN-SQUARE F-RATIO IMPACT TRT IMPACT* TRT ERROR 6.569 6.701 21 .049 24.000 3 2 6 13 2. 190 3.351 3.508 1 .846 1.186 1.815 1.900 0.353 0 .202 0.156 DURBIN-WATSON D STATISTIC 3.005 FIRST ORDER AUTOCORRELATION -.503 TWO WAY ANALYSIS OF VARIANCE FOR 1988 ROSA BIOMASS DEP VAR: ROSA N: 25 MULTIPLE R: .823 SQUARED MULTIPLE R , 678 ANALYSIS OF VARIANCE SOURCE SUM-OF-SQUARES DF MEAN-SQUARE F-RATIO IMPACT TRT IMPACT* TRT ERROR 27.259 18. 138 53.467 46.210 3 2 6 13 9. 086 9.069 8.911 3.555 2 .556 2.551 2.507 0.100 0.116 0 . 078 DURBIN-WATSON D STATISTIC 3.170 FIRST ORDER AUTOCORRELATION -.586 TWO WAY ANALYSIS OF VARIANCE FOR 1988 OTHER SHRUB BIOMASS DEP VAR:OTHSHRUB N : 25 MULTIPLE R: .634 SQUARED MULTIPLE R ,402 SOURCE SUM-OF-SQUARES ANALYSIS OF VARIANCE DF MEAN-SQUARE F-RATIO IMPACT TRT IMPACT* TRT 2.340 1.163 1 .634 0.780 0.581 0 .272 1.341 0 . 999 0.468 0.304 0 .395 0 . 820 ERROR 7.562 13 0 .582 DURBIN-WATSON 0 STATISTIC 3.142 FIRST ORDER AUTOCORRELATION . -.571 268 TWO WAY A N A L Y S I S OF V A R I A N C E FOR 1988 S P I R E A BIOMASS DEP V A R : S P I R E A N: 25 M U L T I P L E R: . 8 4 5 SQUARED M U L T I P L E R: 714 SOURCE IMPACT TRT I M P A C T * TRT ERROR A N A L Y S I S OF V A R I A N C E S U M - O F - S Q U A R E S DF M E A N - S Q U A R E F - R A T I O 3 3 . 1 12 3 2 3 . 0 5 0 2 4 5 . 7 5 9 6 3 9 . 5 5 5 13 1 1 . 0 3 7 1 1 . 5 2 5 7 . 6 2 7 3 . 043 3 . 6 2 7 3 . 788 2 . 5 0 7 0 . 0 4 2 0 . 0 5 1 0 . 0 7 8 269 APPENDIX 4-3 Two-way analysis of variance results for 1988 herb, shrub, moss and total biomass 270 TWO WAY ANALYSIS OF VARIANCE FOR 1988 TOTAL HERB BIOMASS DEP VAR: HERB N: 25 MULTIPLE R: .651 SQUARED MULTIPLE R: .423 SOURCE IMPACT TRT IMPACT* TRT ERROR SUM-OF-SQUARES 79.054 30.846 999.834 1512.957 ANALYSIS OF VARIANCE DF MEAN-SQUARE F-RATIO 1 3 26.351 15.423 166.639 116.381 DURBIN-WATSON D STATISTIC 3.174 FIRST ORDER AUTOCORRELATION -.599 0.226 0. 133 1 .432 0.876 0.877 0.275 TWO WAY ANALYSIS OF VARIANCE FOR 1988 TOTAL SHRUB BIOMASS DEP VAR: SHRUB N: 25 MULTIPLE R: .750 SQUARED MULTIPLE R: 562 SOURCE IMPACT TRT IMPACT* TRT ERROR SUM-OF-SQUARES 35.994 60.912 113.980 158.247 ANALYSIS OF VARIANCE DF MEAN-SQUARE F-RATIO 3 2 6 13 DURBIN-WATSON 0 STATISTIC 3.212 FIRST ORDER AUTOCORRELATION -.617 11.998 30.456 18.997 1 2.173 0 . 986 2.502 1.561 0.430 0.120 0.235 TWO WAY ANALYSIS OF VARIANCE FOR 1988 TOTAL MOSS BIOMASS DEP VAR: MOSS N: 25 MULTIPLE R: .734 SQUARED MULTIPLE R: .538 SOURCE IMPACT TRT IMPACT* TRT ERROR SUM-OF-SQUARES 14.824 5.317 11.268 26.827 ANALYSIS OF VARIANCE DF MEAN-SQUARE F-RATIO 3 2 6 13 4.941 .658 1 .878 2 .064 2 .394 1 . 288 0.910 0.115 0.309 0.517 DURBIN-WATSON D STATISTIC FIRST ORDER AUTOCORRELATION 2 . 648 - .325D 271 TWO WAY ANALYSIS OF VARIANCE FOR 1988 TOTAL BIOMASS DEP VAR: TOTAL N: 25 MULTIPLE R: .706 SQUARED MULTIPLE R: .499 ANALYSIS OF VARIANCE SOURCE IMPACT TRT IMPACT* TRT ERROR SUM - OF - SQUARES 188.570 200.781 1 231 . 531 1610.547 DF MEAN-SQUARE 3 2 6 13 62.857 100.391 205.255 123.888 F - RAT 1O 0.507 0.810 1 .657 0 .684 0.466 0.209 DURBIN-WATSON D STATISTIC FIRST ORDER AUTOCORRELATION 3.084 - .549 272 APPENDIX 4-4 The average height, height increment, basal diameter and survival of lodgepole pine _ seedlings planted in the experimental plots at the end of the first and second growing season 273 The average height, height increment, basal diameter, and survival at the end of the first growing season of lodgepole pine seedlings planted in each of the experimental plots. Treatment T o t a l Increment Basal S u r v i v a l Height Diameter (cm) (cm) (mm) (%) 1 ) BROADCAST BURN PLOTS Low s e v e r i t y burns i n f r e s h s l a s h P l o t 2 15.7 1.9 - 88 P l o t 17 16.5 2.7 - 82 Low s e v e r i t y burns i n cured s l a s h P l o t 1 15.4 3.3 - 94 P l o t 4 15.6 2.9 - 90 Moderate s e v e r i t y burns P l o t 8 15.7 2.7 - 84 P l o t 11 15.7 2.7 - 78 High s e v e r i t y burns P l o t 9 15.7 3.5 - 94 P l o t 13 15.5 2.2 - " 82 P l o t 14 14.5 1.9 - 84 2) WINDROW BURNED PLOTS a) areas between windrows Low s e v e r i t y burns i n f r e s h s l a s h P l o t 7 17.1 4.6 - 96 P l o t 10 16.6 5.0 - 96 Low s e v e r i t y burns in cured s l a s h P l o t 3 14.9 2.1 - 91 P l o t 5 16.7 3.4 - 94 Moderate s e v e r i t y burns P l o t 12 16.1 3.1 - 89 P l o t 16 16.5 0.8 - 78 High s e v e r i t y burns P l o t 15 16.6 2.7 - 91 P l o t 18 16.7 3.6 - 89 b) areas beneath windrows Low s e v e r i t y burns i n f r e s h s l a s h P l o t 7 15.8 2.0 - 89 P l o t 10 15.7 1.5 - 81 Low s e v e r i t y burns i n cured s l a s h P l o t 3 14.6 0.9 - 85 P l o t 5 1 14.6 -0.5 - 94 Moderate s e v e r i t y burns P l o t 12 16.5 2.0 - 81 P l o t 16 14.9 1.0 - 83 High s e v e r i t y burns P l o t 15 14.5 0.5 - 78 P l o t 18 14.6 0.3 - 74 Broadcast plot averages n=49 seedlings Windrow plot averages n=54 seedlings 274 The average height, height increment, basal diameter, and survival at at the end of the second growing season of lodgepole pine seedlings planted in each of the experimental plots. T reatment T o t a l Inc rement Basal S u r v i v a l Height Diameter ( cm) (cm) (mm) (%) 1) BROADCAST BURN PLOTS Low s e v e r i t y burns i n f r e s h s l a s h P l o t 2 23.6 7.6 6.0 84 P l o t 17 23. 1 6.5 5.9 73 Low s e v e r i t y burns i n cured s l a s h P l o t 1 20.4 5.0 5 .1 59 P l o t 4 26.0 10.2 6.8 67 Moderate s e v e r i t y burns P l o t 8 22.9 5.6 6.0 78 P l o t 11 24 . 6 8.5 6.3 71 High s e v e r i t y burns P l o t 9 24 . 2 8.0 5.4 76 P l o t 13 23.6 7.4 6. 1 71 P l o t 14 28.0 12.1 7.4 71 2) WINDROW BURNED PLOTS a) areas between windrows Low s e v e r i t y burns i n f r e s h s l a s h P l o t 7 25 .5 8.3 6.6 89 P l o t 10 24 . 1 7.4 6.7 94 Low s e v e r i t y burns i n cured s l a s h P l o t 3 24 . 4 9.4 5.5 85 P l o t 5 24 . 0 7.2 6.2 87 Moderate s e v e r i t y burns P l o t 12 27.1 10.9 9.5 76 P l o t 16 29.5 12.5 7.4 70 High s e v e r i t y burns P l o t 15 27.4 11.4 7.3 89 P l o t 18 27.9 11.1 7.9 78 b) areas beneath windrows Low s e v e r i t y burns in f r e s h s l a s h P l o t 7 22 . 7 6 . 9 6 . 1 85 P l o t 10 27.0 11.0 7.3 74 Low s e v e r i t y burns i n cured s l a s h P l o t 3 25 . 4 10.8 6.8 63 P l o t 5 23 . 1 8.5 7. 1 65 Moderate s e v e r i t y burns P l o t 12 27. 1 10.8 7.2 76 P l o t 16 23 . 9 8.5 6.8 59 High s e v e r i t y burns P l o t 15 24 . 0 9 . 3 6. 1 61 P l o t 18 24 . 0 9 . 2 6 . 7 57 Broadcast plot averages n=49 seedlings Windrow plot averages n=54 seedlings 275 APPENDIX 4-5 - SHmmary of the biomass and percent cover of the most important understory species during the first and second growing seasons in each of the experimental plots 276 Average biomass of the most important understory species in the experimental plots during the first and second growing seasons. Treatment Shrubs Herbs Rosa Spirea Epilobium Linnaea Grasses Cornus g\m Growing season 87 88 87 88 87 88 87 88 87 88 87 88 1) Low s e v e r i t y burns i n f r e s h s l a s h B roadcast burn areas 2.7 2.6 2.4 4.0 1.0 10.2 1.2 4.8 0.4 4.0 0.5 3.3 Areas between windrows 1.0 2.4 6.6 3.9 2.3 14.6 6.3 4.5 1.0 0.9 0.3 0.5 Areas beneath windrows 3.0 4.4 2.4 7.8 1.7 5.9 0.3 2.1 0.0 2.0 0.3 0.9 2) Low s e v e r i t y burns in cured s l a s h B r o a dcast burn areas 0.2 1.5 0.3 0.8 0.9 1.5 0.3 2.9 0.0 0.&- 0.3 0.2 Areas between windrows 0.7 8.1 2.3 4.4 2.8 3.9 0.3 2.1 1.2 14.3 0.4 3.8 Areas beneath windrows 0.2 5.6 0.0 4.7 0.0 4.2 0.0 0.0 0.0 7.3 0.0 0.2 3) Moderate s e v e r i t y burns Broadcast burn areas 0.5 1.4 1.8 2.8 2.2 9.9 0.2 1.1 0.2 5.0 0.1 0.8 Areas between windrows 2.3 1.0 8.2 7.5 5.7 10.6 0.3 9.2 1.3 5.7 0.1 0.4 Areas beneath windrows 0.2 2.5 0.7 6.5 3.8 16.0 0.0 0.3 0.0 3.6 0.0 0.2 4) High s e v e r i t y burns Broadcast burn areas 0.1 1.5 2.4 5.9 2.1 16.4 0.2 1.2 0.2 2.6 0.1 0.5 Areas between windrows 5.2 0.7 1.8 3.4 3.1 11.1 0.0 0.1 3.2 1.3 0.1 0.6 Areas beneath windrows 1.0 0.9 0.8 5.4 3.3 12.4 0.0 0.0 0.5 0.4 0.1 0.1 277 The average biomass of the most important understory species during the first growing season in each of the experimental plots. Treatment Shrubs Herbs Rosa Spirea Oth Shrb Epilob Linnaea Grasses Cornus g\m 1) BROADCAST BURN PLOTS Low s e v e r i t y burns i n f r e s h s l a s h P l o t 2 2 .0 1 .2 0 .8 0 .8 0 . 0 0 . 5 0 .4 P l o t 17 3 .4 3 . 7 0 .8 1 . 3 0 . 0 0 . 3 0 .6 Low s e v e r i t y burns i n cured s l a s h P l o t 1 0 .0 0 .0 0 . 1 0 .4 0 .2 0 . 0 0 .3 P l o t 4 0 . 4 0 .7 0 .2 1 .4 0 .5 0 . 0 0 . 2 Moderate s e v e r i t y burns P l o t 8 0 .0 0 . 1 0 . 1 0 . 4 0 . 2 0 . 0 0 . 2 P l o t 11 0 .9 3 .5 1 .0 4 . 0 1 .3 0. 4 0 . 1 High s e v e r i t y burns P l o t 9 0 .3 0 .8 0 .9 1 . 7 0 . 8 0 . 5 0 . 1 P l o t 13 0 . 1 4 . 0 0 . 1 3 . 0 1 .3 cf. 1 0 . 1 P l o t 14 0 . 0 2 .5 0 .9 1 . 7 0 . 7 0 . 0 0 . 1 2) WINDROW BURNED PLOTS a) areas between windrows Low s e v e r i t y burns in f r e s h s l a s h P l o t 7 0 . 7 2 . 1 0 . 2 4 . 4 0 .4 0 . 9 0 . 4 P l o t 10 1 .2 11 . 1 3 . 5 0 . 2 0 . 0 1. 2 0 . 2 Low s e v e r i t y burns in cured s l a s h P l o t 3 0 .7 4 . 1 0 .2 0 . 5 0 . 5 0 . 3 0 . 7 P l o t 5 0 .6 0 . 5 0 . 1 5 . 0 1 . 9 2 . 2 0 . 1 Moderate s e v e r i t y burns P l o t 12 0 .6 12 .5 0 . 1 4 .0 0 . 0 2 . 1 0 . 1 P l o t 16 4 . 1 3 . 9 1 .4 7 . 5 0 . 3 0 . 4 0 . 1 High s e v e r i t y burns PIot 1 5 4 . 9 1 . 2 0 . 8 1 6 . 2 1 . 4 4 . 1 0 . 1 P l o t 18 5 . 5 2 . 5 0 .4 1 0 . 0 0 . 9 2 . 3 0 . 1 b) areas beneath windrows Low s e v e r i t y burns in f r e s h s l a s h P l o t 7 1 .8 1 .6 0 .4 3 . 1 0 .3 0 . 0 0 .7 P l o t 10 4 .3 3 . 2 0 . 7 0 . 4 0 . 0 0 . 0 0 . 0 Low s e v e r i t y burns in cured s l a s h P l o t 3 0 . 3 0 . 0 0 . 7 0 . 1 0 . 0 0 . 0 0 . 0 P l o t 5 " 0 . 0 0 . 0 0 . 1 0 . 0 0 . 0 0 . 0 0 . 0 Moderate s e v e r i t y burns P l o t 12 0 . 4 1 . 0 0 . 0 5 . 7 0 . 0 0 . 0 0 . 0 P l o t 16 0 . 1 0 . 4 0 . 5 1 . 8 0 . 0 0 . 0 0 . 0 High s e v e r i t y burns P l o t 15 2 . 1 0 . 0 0 . 0 4 . 4 0 . 3 0 . 1 0 . 1 PIot 1 8 0 . 0 1 . 6 0 . 0 2 . 2 0 . 0 0 . 0 0 . 0 Category averages are based on n=10 samples per treatment plot. 278 The percent cover of the most important understory species during the first growing season in each of the experimental plots. T reatment Sh rubs Herbs Rosa Spirea Epilob Linnaea Grasses Cornus % 1) BROADCAST BURN PLOTS Low s e v e r i t y burns in f r e s h s l a s h P l o t 2 3 T i 2 3 T P l o t 17 T 3 2 2 T T Low s e v e r i t y burns i n cured s l a s h P l o t 1 2 T 1 1 T T P l o t 4 T T T T T T Moderate s e v e r i t y burns P l o t 8 T T 1 1 T T P l o t 11 T 2 1 T T T High s e v e r i t y burns P l o t 9 T 2 1 T T T P l o t 13 T 1 4 T "T T P l o t 14 1 3 2 T T T 2 ) WINDROW BURNED PLOTS a) areas between windrows Low s e v e r i t y burns in f r e s h s l a s h P l o t 7 T 3 1 1 T T P l o t 10 2 5 1 T T T Low s e v e r i t y burns i n cured s l a s h -P l o t 3 2 4 1 1 2 T P l o t 5 T T T T T T Moderate s e v e r i t y burns P l o t 12 T 5 1 T T T P l o t 16 T 2 3 T T T High s e v e r i t y burns P l o t 15 T 1 1 T T T P l o t 18 T 5 1 T T T b) areas beneath windrows Low s e v e r i t y burns i n f r e s h s l a s h P l o t 7 T 1 1 T T T P l o t 10 T T T T T T Low s e v e r i t y burns in cured s l a s h P l o t 3 T T T T T T P l o t 5 - T T T T T T Moderate s e v e r i t y burns P l o t 12 T T T T T T P l o t 16 T T T T T T High s e v e r i t y burns P l o t 15 T T T T T T P l o t 18 T T T T T T T indicates trace presence of the species. 279 The average biomass of the most important understory species during the second growing season in each of the experimental plots. Treatment Shrubs Herbs Rosa Spirea Oth Shrb Epilob Linnaea Grasses Cornus g\m 1) BROADCAST BURN PLOTS Low s e v e r i t y burns i n f r e s h s l a s h P l o t 2 2 . 6 5 . 0 0.4 4 . 2 2 .9 3.8 3 .4 P l o t 17 2 . 5 2 .9 0 . 5 16 . 1 6 .6 4 . 2 3 . 1 Low s e v e r i t y burns i n cured s l a s h P l o t 1 1 . 1 0 . 0 0.0 0 . 1 2 .4 0 . 0 0 . 2 P l o t 4 1 .8 1 .6 0.0 2 .8 3 .4 0 . 0 0 . 1 Moderate s e v e r i t y burns P l o t 8 0 . 0 2 . 0 0.0 16 .3 0 . 6 9 . 0 0 . 5 P l o t 11 2 .8 3 . 6 0 . 0 3 . 5 1 .6 1 . 0 1 . 0 High s e v e r i t y burns P l o t 9 0 . 1 6 .8 0 . 0 5 .3 1 .3 4 . 7 1 . 1 P l o t 13 1 . 2 4 . 5 0 . 1 24 . 7 1 .6 r.s 0 . 1 P l o t 14 3 .2 6 . 4 0.0 19 . 2 0 .6 1 . 7 0 .3 2) WINDROW BURNED PLOTS a) areas between windrows Low s e v e r i t y burns i n f r e s h s l a s h P l o t 7 1.5 6.2 0.0 8.1 2.0 0.3 1.4 P l o t 10 7.3 9.3 0.1 3.6 2.1 3.6 0.4 Low s e v e r i t y burns i n cured s l a s h P l o t 3 10.6 5.7 0.0 4.9 0.4 5.6 0.4 P l o t 5 5.6 3.0 0.0 2.9 3.7 23.0 7.1 Moderate s e v e r i t y burns P l o t 12 0.7 8.4 0.1 7.1 4.2 6.5 0.3 P l o t 16 1.2 6.4 0.0 14.0 0.4 4.8 0.4 High s e v e r i t y burns P l o t 15 0.2 1.5 0.1 17.3 0.0 0.1 0.6 P l o t 18 1.2 5.2 7.8 4.9 0.2 2.5 0.5 b) areas beneath windrows Low s e v e r i t y burns in f r e s h s l a s h P l o t 7 1.3 2.2 0.2 18.5 1.2 0.6 0.8 P l o t 10 3.4 5.2 0.0 10.7 7.7 1.1 0.1 Low s e v e r i t y burns in cured s l a s h P l o t 3 . 1.6 1.2 0.0 0.6 0.0 0.1 0.0 P l o t 5 ' 0.6 3.7 0.0 7.7 0.0 14.5 0.0 Moderate s e v e r i t y burns P l o t 12 1.0 1.2 0.0 13.0 0.6 1.4 0.3 P l o t 16 3.9 6.4 0.0 18.9 0.0 5.7 0.0 High s e v e r i t y burns P l o t 15 1.2 3.5 0.1 10.3 0.0 0.3 0.0 P l o t 18 0.5 7.2 0.0 14.4 0.0 0.4 0.2 Category averages are based on n=10 samples per treatment plot. 280 The percent cover of the most important understory species during the second growing season in each of the experimental plots. T reatment Sh rubs Herbs Rosa Spirea Epilob Linnaea Grasses Cornus X 1) BROADCAST BURN PLOTS Low s e v e r i t y burns i n f r e s h s l a s h P l o t 2 T i T 1 10 T P l o t 17 1 i 7 2 T T Low s e v e r i t y burns i n cured s l a s h P l o t 1 T T 1 1 T T P l o t 4 4 3 T T T T Moderate s e v e r i t y burns P l o t 8 T T 3 1 T 1 P l o t 11 T 2 7 T 1 T High s e v e r i t y burns P l o t 9 T 4 6 T T T P l o t 13 T 5 1 5 T • T P l o t 14 1 3 20 T T T 2) WINDROW BURNED PLOTS a) areas between windrows Low s e v e r i t y burns i n f r e s h s l a s h P l o t 7 T 3 1 1 1 T P l o t 10 2 5 1 T T T Low s e v e r i t y burns i n cured s l a s h P l o t 3 2 4 10 1 2 T P l o t 5 T T 3 T T 20 Moderate s e v e r i t y burns P l o t 12 T 5 6 T 1 T P l o t 16 T 2 5 T T T High s e v e r i t y burns P l o t 15 T 1 7 T T T P l o t 18 1 5 7 T T T b) areas beneath windrows Low s e v e r i t y burns i n f r e s h s l a s h P l o t 7 T 1 1 T T T P l o t 10 4 T T T T T Low s e v e r i t y burns i n cured s l a s h P l o t 3 T T T T T T P l o t 5 - T T T T T T Moderate s e v e r i t y burns P l o t 12 T T 1 T T T P l o t 16 T T 2 1 T T High s e v e r i t y burns P l o t 15 T T 5 T T T P l o t 18 T T 4 1 T T T indicates trace presence of the species. 281 APPENDIX 4-6 List of pre and postburn plant species present in the experimental plots 282 RICHARDSON L A K E - PLANT SPECIES LIST - A U G U S T 21,1988 P R E A N D POSTBURN SPECIES N A M E Achillea millefolium Agrostis scabra Alnus viridis Arnica cordifolia Aster foliaceus Calamagrostis canadensis Carex athrostachya Carex praticola Cinna latifolia Cladonia spp. Comus canadensis Corydalis sempervirens Crepis capillaris Dracocephalum parvifolium Dicranum spp. Epilobium anagustifolium Equisetum arvense Equisetum silvaticum Festuca occidentalis Fragaria virginiana Galium boreale Geranium bicknellii Hieracium albiflorum Linnaea borealis Lonicera involucrata Lupinus sericeus Lycopodium complanatum Marchantia polymorpha Petasites palmatus Phleum pratense Pinus contorta Pleurozium schreberi Polytrichum juniperinum Populus tremuloides Ribes lacustre Rosa acicularis Rubus idaeus Rubus pedatus Rubus pubescens Salix bebbiana Sheperdia canadensis Spiraea betulifolia Taraxacum officinale Tiarella trifoliata Trisetum spicatum Vaccinium caespitosum Vaccinium membranaceum Viburnum edule Vicia americana Viola orbiculata yarrow hair bentgrass green alder heart-leaved arnica leafy aster bluejoint slender-beaked sedge meadow sedge nodding wood-reed pineapple weed bunchberry pink corydalia smooth hawksbeard American dragonhead fireweed common horsetail wood horsetail western fescue wild strawberry northern bedstraw Bicknell's geranium white-flowered hawkweed twinflower black twinberry silky lupine ground-cedar palmate coltsfoot timothy lodgepole pine red-stemmed feathermoss juniper haircap moss trembling aspen black gooseberry prickly rose evergreen blackberry five-leaved bramble trailing raspberry Bebb's willow soopalallie birch-leaved spirea common dandelion three-leaved foamflower spike trisetum dwarf blueberry black huckleberry high-bush cranberry American vetch round-leaved violet APPENDIX 4-7 Layout of tree seedling assessment plots within the study Examples of sample tree layouts in broadcast burn (plot 4) and windrow burn (plot 10)P l o t s -NOT TO S C A L E 30m MEASUREMENT START l - ~ » 1 4 IS 28 2"» 42 43 2 13 16 2-1 30 41 44 3 12 17 26 31 40 43 4 11 I d 23 32 46 6 10 is 24 33 38 47 * 1 20 23 34 37 +8 7 S 21 22 36 36 4S 30m 7S1 7S2 7S3 <t 10 u 64 27 28 at 82 4S 4« 1 8 11 •2 88 2E » 60 63 44 47 T6 Z 7 12 61 86 29 30 T1 64 43 46 3 8 11 •0 87 24 31 7* as 42 4*. 4 8 14 « 66 23 32 77 88 41 00 "a • 4 IB M 22 33 7S 67 40 St S4 t 3 18 87 70 21 34 78 as 3"» S2 •a 7 2 17 m 71 20 JB 74 81 36 S3 • m 77 73 «W * 7W3 7W2 7W1 7 P L O T • s INTOWIWKW 3 7 P L O T • w wittxov 3 REPLICATE a I N D I C A T E S PERMENANT S A M P L E TREES x I N D I C A T E S NON MEASUREMENT bCRDt<v TREES INDICATES PERMENHNT WINDROW SAMPLE TREES INDICATES PERMENANT INTERWINDROW I SCRAPE ) SAMPLE TREES 285 PLOTS 1-6 PERMANENT SAMPLE TREE NUMBER SEQUENCE * START MEASUREMENT OF STAKED BROADCAST PLOTS AT THIS POINT F FLAGGED PLOTS , S STAKED PLOTS PLOTS 7-12 0 r r « F 8 CCNTKCL S NFS NFS NFS LOTUS rRira-iur r 3 12S3 12W1 12 12S2 12W2 I2S1 12W3 NFS 10-58i NFS CONTROL NFS LOTUS NFS NFS TRtFOLIUf S 7WI 7 731 7V2 732 7V3 NFS 733 11 NFS NFS TR1FUL]1|' 1031 10S2 10V2 10S3 1QV3 HU NF3 « START MEASUREMENT OF STAKED BROADCAST PLOTS AT THIS POINT NFS NITROGEN F I X A T I O N STUDY PLOTS F FLAGGED PLOTS ' S STAKED PLOTS 23/ PLOTS' 13-18 • 50M * START MEASUREMENT OF STAKED BROADCAST PLOTS AT THIS POINT F FLAGGED PLOTS S STAKED PLOTS 1QOM 1 « START MEASUREMENT OF WINDROW OR 1NTERW1NDROW TREES AT THIS POINT 

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