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Productivity of western larch in relation to categorical measures of climate, soil moisture, and soil… New, David Morley 1999

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P R O D U C T I V I T Y O F W E S T E R N L A R C H IN R E L A T I O N T O C A T E G O R I C A L M E A S U R E S O F C L I M A T E , SOIL M O I S T U R E , A N D SOIL N U T R I E N T S  by  DAVE) MORLEY NEW  A T H E S I S S U B M I T T E D IN P A R T I A L F U L F I L M E N T O F THE REQUIREMENTS FOR THE DEGREE OF M A S T E R OF SCIENCE  in  T H E F A C U L T Y OF G R A D U A T E STUDIES Department of Forest Sciences  W e accept this thesis as conforming to the required standard  T H E UNIVERSITY OF BRITISH C O L U M B I A July 1999 © David Morley New, 1999  In p r e s e n t i n g t h i s t h e s i s i n p a r t i a l f u l f i l m e n t o f t h e r e q u i r e m e n t s f o r an a d v a n c e d d e g r e e a t t h e U n i v e r s i t y o f B r i t i s h C o l u m b i a , I a g r e e t h a t t h e L i b r a r y s h a l l make i t f r e e l y a v a i l a b l e f o r r e f e r e n c e and s t u d y . I f u r t h e r a g r e e t h a t p e r m i s s i o n f o r e x t e n s i v e c o p y i n g o f t h i s t h e s i s f o r s c h o l a r l y p u r p o s e s may be g r a n t e d by t h e head o f my department o r by h i s o r h e r r e p r e s e n t a t i v e s . I t i s u n d e r s t o o d t h a t c o p y i n g o r p u b l i c a t i o n of t h i s t h e s i s f o r f i n a n c i a l g a i n s h a l l not be a l l o w e d w i t h o u t my w r i t t e n p e r m i s s i o n .  Department  of  The U n i v e r s i t y o f B r i t i s h V a n c o u v e r , Canada Date  Columbia  ABSTRACT  The relationship between western larch (Larix occidentalis Nutt.) productivity, as determined by site index, and estimates of climate, soil moisture and soil nutrients, as delineated within the Biogeoecosystem classification system, was examined. Data was collected from 315 even-aged stands throughout the range of western larch in B . C . Climate, expressed by subzone, showed a significant effect on the site index of western larch; however, significant differences occurred only between two groups: lower precipitation (Interior Douglas-fir) and higher precipitation (Interior Cedar - Hemlock and Montane Spruce ) subzones. The climatic growth optimum for western larch corresponded to the intermediate segment of a regional climatic gradient - wetter temperate climate - that is represented by the Dry W a r m Interior Cedar Hemlock subzone. In relation to edatopes, site index significantly increased from water-deficient to moist sites and decreased from moist to wet sites, and on water-deficient sites, it increased with increasing soil nutrient regime. On water-deficient sites, estimates of both actual soil moisture regime and soil nutrient regimes had both positive significant and consistent effects on site index. On non-water deficient sites, the effect of soil nutrient regime appeared to be marginal. A cross-validated prediction model based on actual soil moisture regime and soil nutrient regime accounted for 83% of the variation in site index of western larch suggesting that there is a strong correlation between ecological site classification and western larch productivity. The developed model, combined with the identification of actual soil moisture regime, and soil nutrient regime can be used to provide reliable site index predictions for western larch throughout its range in B . C . to a level of accuracy required for practical forest management.  Key Words Larix occidentalis, biogeoclimatic subzone, actual soil moisture regime, soil nutrient regime, productivity, prediction, site index.  T A B L E OF CONTENTS  ABSTRACT T A B L E OF CONTENTS  ii iii  LIST O F T A B L E S  v  LIST OF FIGURES  vii  ACKNOWLEDGEMENTS  viii  1. I N T R O D U C T I O N  1  1.1 The Role of Western Larch  1  1.2 Site Index as the Measure of Forest Productivity  3  1.3 Estimating Site Index from Environmental Factors  3  1.4 A n Ecological Framework for Estimating Site Index  4  1.5 Objectives  6  2. T H E S T U D Y A R E A  8  3. M A T E R I A L S A N D M E T H O D S  10  3.1 Selection of Study Sites and Sampling  10  3.2 Estimates of Climate, Soil Moisture, and Soil Nutrient Regimes  13  3.3 Analysis of the Relationship between Site Index and Climate  16  3.4 Analysis of Relationships between Site Index and Soil Moisture and Nutrient Regimes  18  4. R E L A T I O N S H I P S B E T W E E N SITE I N D E X A N D C L I M A T I C , S O I L M O I S T U R E A N D SOIL N U T R I E N T REGIMES  23  4.1. Relationships between Site Index and Climate  23  4.2 Relationships between Site Index and Soil Moisture and Nutrient Regimes  26  4.2.1 The I D F Group  26  4.2.2 The I C H - M S Climate Group  27  4.3 Discussion  30  4.4 Conclusions  38  5. P R E D I C T I O N O F W E S T E R N L A R C H SITE I N D E X  40  5.1 Introduction  40  5.2 Methods  40  5.3 Results  42  5.4 Discussion  46  5.6 Conclusions  51  6. C O N C L U S I O N S  52  LITERATURE CITED  54  APPENDIX 1  59  APPENDIX 2  68  APPENDIX 3  71  APPENDIX 4  73  APPENDIX 5  74  iv  LIST OF  T A B L E S  Table 3.1 Means of selected climatic characteristics for the eight study subzones : Very Dry Hot I D F (IDFxh), Dry M i l d IDF (IDFdm), Moist Warm I D F (EDFmw), Dry Warm I C H (ICHdw), Moist W a r m I C H (ICHmw), Moist Cool I C H (ICHmk), Dry M i l d M S (MSdm), and Dry Cool M S (MSdk). The means were calculated from the data obtained from Environment Canada (1982). Precipitation is in mm and temperature in Celsius  11  Table 3.2 Number of study stands stratified according to the eight study subzones. Abbreviations for subzones as in Table 3.1  12  Table 3.3 Conversion table of relative to actual soil moisture regime ( R S M R s to A S M R s ) for the eight study subzones. A S M R s of zonal sites are shown outlined and shaded. Abbreviations for subzones as in Table 3.1; abbreviations for A S M R s are: X D - extremely dry, E D - excessively dry, V D - very dry, M D - moderately dry, S D slightly dry, F - fresh, M moist, V M - very moist, W - wet, V W - very wet  14  Table 3.4 Western larch site index means (in boldface), standard deviations (in parentheses) and number of stands on zonal sites stratified according to study subzone. Abbreviations for subzones as in Table 3.1  16  Table 3.5 Western larch site index means (in boldface), standard deviations (in parentheses) and number of stands on sites of poor and medium soil nutrient regime stratified by actual soil moisture regime and subzone. Abbreviations for subzones as in Table 3.1  17  Table 3.6 Number of stands and means (in bold print) and standard deviations (in parentheses) of western larch site index (m @ 50 yrs bh) of the 315 study sites stratified according to actual soil moisture and soil nutrient regimes  19  Table 3.7 Edatopic grids for the I D F group showing the number of stands sampled in each edatope and those edatopes selected in: (A) B l o c k 1 for analysis and (B) B l o c k 2 for analysis. Selected edatopes are shaded in grey. T w o identical edatopic grids are presented in order to clearly show edatope selection for each block  20  Table 3.8 Edatopic grids for the I C H - M S group showing the number of stands sampled in each edatope and those edatopes selected in: (A) B l o c k 1 for analysis and (B) Block 2 for analysis. Selected edatopes are shaded in grey. T w o identical edatopic grids are presented in order to clearly show edatope selection for each block  21  1  0  v  Table 4.1 Analysis of variance for mean site index on zonal sites in eight study subzones ( a = 0.05)  24  Table 4.2 Western larch site index means on zonal sites stratified according to study subzone. Values in the same row with different lower case superscripts are significantly different ( a = 0.05). Abbreviations for subzones as in Table 3.1  24  Table 4.3 Set 2: Analysis of variance for mean site index on moderately dry, poor and medium sites in seven study subzones ( a = 0.05)  25  Table 4.4 Set 3: Analysis of variance for mean site index on slightly dry, poor and medium sites in seven study subzones ( a = 0.05)  26  Table 4.5 Analysis of variance for mean site index in Block 1 of the I D F climatic group ( a = 0.05)  27  Table 4.6 Analysis of variance for mean site index in B l o c k 2 of the I D F group ( a = 0.05)  27  Table 4.7 Analysis of variance for mean site index in Block 1 of the I C H - M S group ( a = 0.05)  29  Table 4.8 Analysis of variance for mean site index in B l o c k 2 of the I C H - M S group ( a = 0.05)  29  Table 5.1 The A S M R S N R prediction model developed from the construction data set (n = 210) relating site index (m @ 50 yrs bh) of western larch to combinations of actual soil moisture and soil nutrient regimes  42  Table 5.2 The A S M R S N R prediction model developed from all site data (the combined construction and test data sets (n=315)) relating site index (m @ 50 yrs bh) of western larch to combinations of actual soil moisture and soil nutrient regimes Table 5.3 Edatopic grid showing the A S M R S N R model (n=315) predicted site index values and ± 95% confidence interval (m), measured mean site index values (m @ 50 yr bh), and S I B E C mean site index values (m @ 50 yr bh) according to actual soil moisture and soil nutrient regimes. Sample sizes indicated refer only to the measured and predicted site index values  45  47  vi  L I S T  O F  F I G U R E S  Figure 2.1 Range of western larch in B . C . The location of major and minor sampling areas are indicated by the larger and smaller points, respectively  9  Figure 4.1 Bar graph of western larch site index on zonal sites in eight study subzones. Error bars are for standard deviation. Abbreviations for subzones as in Table 3.1  25  Figure 4.2 Means and standard error of means of western larch site index for (A) poor and medium hygrosequences in relation to very dry, moderately dry, and slightly dry A S M R s for Block 1 of the I D F group and (B) for poor, medium, and rich hygrosequences in relation to moderately dry and slightly dry A S M R s for B l o c k 2 of the I D F group  28  Figure 4.3 Means and standard error of means of western larch site index for (A) poor, medium and rich hygrosequences in relation to very dry, moderately dry, and slightly dry A S M R s for Block 1 of the I C H - M S group and (B) for medium, and rich hygrosequences in relation to very dry, moderately dry, slightly dry, and fresh A S M R s for B l o c k 2 of the I C H - M S group  31  Figure 5.1 Residual analysis for the A S M R S N R construction model (n = 210): (A) residual (m) versus predicted site index (m @ 50 yrs bh) and (B) measured versus predicted site index (m @ 50 yrs bh)  43  Figure 5.2 Prediction error for the A S M R S N R construction model in relation to measured site index (m @ 50 yrs bh) of the test data set (n=105)  45  Figure 5.3 Residual analysis for the A S M R S N R model (n=315). Measured versus predicted site index (m @ 50 yrs bh)  46  vii  ACKNOWLEDGEMENTS  I would first like to thank Dr. Karel Klinka who willingly accepted me as his student despite the fact that my performance outside a field based working relationship had not been proven. It has been through his constant support and encouragement that I am now able to acknowledge him here. To him I am most grateful. I am also much indebted to those belonging to the "Klinka Machine" each of who in their own way have aided me in achieving this end. I would like to thank my committee members, Dr. Les Lavkulich and Dr. Peter Marshall for their time and their counsel which were not solely confined to matters of science. Finally, I must thank my wife Allison most of all, she was a constant support and managed to hold our family unit together and maintain a semblance of home despite my mind and body often being elsewhere.  1. I N T R O D U C T I O N  1.1 T h e Role of Western L a r c h  Western larch (Larix occidentalis Nutt.), a Western North American-Cordilleran species, is one of three larch species that occur in British Columbia. It is the only one of these larch that has timber values and silvical attributes that make it a very desirable component in a forest (Morrison 1991). Therefore, it would be beneficial to know what is the potential productivity of larch on all sites that are capable of supporting its growth.  Western larch contributes to aesthetic and wildlife diversity of forests. Seasonal changes in foliage add a great deal to the aesthetic diversity of the stands in which larch is even a small component. Larch veterans contribute to wildlife diversity by providing habitat for pileated woodpeckers and other primary cavity nesters (McClelland 1992). Larch's leafless winter habit makes it less palatable as browse for foraging ungulates. This enables larch seedlings to develop in areas where other tree species are consistently browsed due to intense wildlife feeding.  Pure stands of western larch are infrequent; most often it forms an admixture - usually a dominant stratum in mixed-species stands that have established after wildfires. The common associates with larch in continental temperate climates are lodgepole pine (Pinus contorta Dougl. ex Loud.), Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), western hemlock (Tsuga heterophylla (Raf.) Sarg.), and western redcedar (Thuja plicata Donn D. Don) Spach). Hybrid spruce (Picea engelmannii Parry ex Engelmann x P. glauca (Moench) Voss) and subalpine fir (Abies lasiocarpa (Hook.) Nutt.) associate with larch in mild continental subalpine boreal climates.  Within its relatively small range in the south-eastern part of the province, shade intolerant western larch is one of the fastest growing species, with the exception of some hardwoods, such as Populus species and paper birch (Betula papyrifera Marsh.). The only other conifer that can compete with larch is lodgepole pine and it is only for the first 50 years, after which long-lived larch (about 900 years) exceeds it in height growth (Feidler and Lloyd 1992). Its straight growth form and self-pruning make it a valuable timber crop species for lumber production. In addition, larch begins to produce high-density mature wood at 15 years of age while most other species require 40 years. Producing such wood quality at young ages will become desirable as oldgrowth stands are depleted and log size in second growth stands decreases (Jaquish et al. 1992). Although larch timber is usually marketed with or as Douglas-fir, its density and strength make it the strongest of the softwood species, and it is often used in manufacturing laminated beams and load bearing timbers (Keegan et al. 1992).  Western larch has few serious damaging agents. The most common is dwarf mistletoe {Arceuthobium laricis  (Piper) St. John) (Carlson et al. 1992). The larch sawfly  (Pristiphora  erichsonii Htg.), larch casebearer (Coleophora laricella Hbn.), and spruce budworm (Choristoneura  spp.) all pose a threat, but attacks rarely result in mortality (Carlson et al. 1992).  In terms of resistance to Armillaria root disease (Armillaria  ostoyae Ramagn. Herink), larch is  seen as a viable alternative to Douglas-fir, especially on sites that are known to be infected and, due to environmental constraints, do not permit extensive site preparation (Morrison 1991). In order to maintain a component of resistant tree species on such sites, western larch is being planted within and beyond its present natural range.  2  1.2 Site Index as the Measure of Forest Productivity  Tree growth depends on the ecosystems in which they are found. The ability to predict the growth of any tree species in any ecosystem is one of the prerequisites for sustainable forest management. Compared to other measures, site index (mean height of the largest diameter (dominant) trees in even-aged stands at a breast height reference age) is the most practical and widely used means of predicting tree growth, and estimating forest productivity (i.e., the capacity of a site to support the growth of a given tree species)(Spurr and Barnes 1980). However, the use of site index for estimating forest productivity is not always possible, such as in situations where the trees are suppressed in growth, damaged, not of a measurable age, or absent (e.g., Hagglund 1981, Monserud 1988, Monserud et al. 1990). In such situations, another method of estimating forest productivity must be used.  1.3 Estimating Site Index from Environmental Factors  Methods that do not use direct growth measures for estimating forest productivity are referred to as indirect (Clutter et al. 1983). Indirect methods use individual or complex (synoptic) environmental factors or classes (taxa) delineated in various classifications or combinations of both. To predict site index, most indirect methods employ multiple regression techniques, with several selected categorical and/or continuous independent variables that have been found to be strongly related to site index (e.g., Jones 1969, Green et al. 1989, Klinka and Carter 1990, Chen et al. 1998). Success and portability of such predictions vary, depending on the selected variables. As a rule, predictions are accurate in specific, usually small areas;  3  however, accuracy is most often lost with increasing area of application because the influence of the selected variables diminishes due to compensating effects (Monserud et al. 1990). Furthermore, procedures for obtaining measures of environmental factors can be time demanding and may require time-consuming laboratory analyses (Klinka and Carter 1990). Therefore, there is a need for site index estimates from factors that have a direct influence on tree growth and that are easily measured in the field.  1.4 A n Ecological Framework for Estimating Site Index  A s a rule, each forest consists of a number of ecosystems (i.e., a number of stands and sites) that are distributed in a certain pattern in the landscape. A biologically viable and sustainable manipulation of ecosystems necessitates knowing what ecosystems are in the forest and their distribution pattern. Ecosystem classification provides a means for recognizing similar (and different) ecosystems, and hence, is a tool for applying ecosystem- or site-specific management.  The system of biogeoclimatic ecosystem classification ( B E C ) (Krajina 1969, Pojar etal. 1987) is the most widely used classification system in British Columbia today (MacKinnon et al. 1992). This system, which has been used for about twenty years, has provided the ecological foundation for all silvicultural endeavours in the province. Site identification and hence, determination of ecological qualities of forest sites, is easily and consistently carried out with the aid of subzone maps and field keys.  4  In the B E C system, local ecosystems, represented either by plant communities or sites, are classified either according to their vegetation or environmental properties, and organized into a climatic superstructure using zonal classification (Pojar et al. 1987). Sites are classified, as well as identified, using three environmental characteristics: (1) climatic regime (represented by biogeoclimatic units), (2) soil moisture regime, (3) soil nutrient regime, and, if appropriate, by additional environmental factors or properties strongly affecting the development of vegetation (Pojar et al 1987). These three characteristics are, in fact, the primary factors influencing plant establishment, growth, and productivity (e.g., Major 1951). Therefore, site classification according to the B E C system is essentially an integration of the determinants of plant growth. The relationship of site productivity with these primary factors or delineated site units is implicit in the system.  Several studies using climatic, soil moisture, and soil nutrient regimes as categorical or continuous variables were successful in predicting site index for a number of tree species in the province. For example, Green et al. (1989) successfully predicted the site index of coastal Douglas-fir using field estimates of climatic, soil moisture, and soil nutrient regimes. Klinka and Carter (1990) reported that catagorical models based on soil moisture and nutrient regimes were superior to analytical models in predicting coastal Douglas-fir site index, and concluded that indirect synoptic measures of climate, soil moisture, and soil nutrients were good predictors of Douglas-fir site index over a large area and provided useful estimates of the direct measures. Using field estimates of soil moisture, nutrient, and aeration regimes as predictors, Wang and Klinka (1996) developed a model that accounted for 87% of the variation in white spruce site index in the Sub-Boreal Spruce zone. Using soil moisture and nutrient regimes in a combination  with selected climatic and topographic properties as independent variables, Chen et al. (1998) developed models for estimating site index of trembling aspen (Populus tremuloides Michx.) in the Boreal White and Black Spruce zone. The models developed provide precise predictions and their predictors are easily and consistently identified in the field.  1.5 Objectives In view of the importance of western larch, the goal of this study was to expand the efforts of past research to this species, for which no provincial height growth and site index functions and productivity - site relationships have been developed. Although there is considerable information about the silvical characteristics of larch (Schmidt et al. 1976, Fielder and L l o y d 1992, K l i n k a et al. 1998), little is known about its potential productivity on sites on which it may grow. The results of this study w i l l increase our knowledge about the productivity of western larch in relation to sites as characterized by the B E C system, and w i l l contribute to the provincially co-ordinated Site Index - Biogeoclimatic Ecosystem Classification program.  The study objectives were: (1) to estimate site index of western larch-dominated stands using the newly developed site index functions (Brisco 1999), (2) to describe the pattern and variation in mean site index in relation to field estimates of climatic, soil moisture, and soil nutrient regimes, and (3) to develop and validate models predicting larch site index using field estimates of climatic, soil moisture, and soil nutrient regimes, having in mind operational application.  6  These objectives were accomplished by sampling 315 stands located across the entire range of western larch in the province. Height growth functions developed by Brisco (1999) were used to determine site index of study stands located across a wide range of environmental conditions. Descriptive statistics were used to examine the relationship between site index and inferred climatic, soil moisture, and soil nutrient regimes. Inferential statistics were used to evaluate the strength of these relationships and site index predictions. To detect the relatively strongest climatic influence on height growth, the analysis of site index - climate relationships was based on the zonal concept (Pojar et al. 1987), so only stands on zonal sites were examined. In addition to examining separately the effect of soil moisture and nutrient regimes on site index, this study also examined the effect of their interaction on larch site index because this effect has not been addressed in the previous productivity - site studies. Unlike most previous studies, this study cross-validates the model developed for predicting larch site index (Neter et al. 1996).  7  2. T H E STUDY AREA  To cover the entire native range of western larch in British Columbia, the study area comprised the south-central and eastern part of the province ranging from 49° 03' to 50° 50' N latitude, from 115° 58' to 119° 25' W longitude, and from 395 to 1,590 m in elevation. The boundaries of the range are quite abrupt; larch does not occur or is very infrequent north of the Shuswap Lake (51° N latitude), west of the Okanagan River, and east of the Rocky Mountains (Thompson 1992) (Figure 2.1).  In view of the large size of the area, the great variation in orography and geomorphology, and the history of disturbance, the study area features a complex pattern of ecosystems as climate, soils, and vegetation can vary considerably over a short distance. The climate of the area is continental and ranges from dry cool temperate (delineated by the Interior Douglas-fir (IDF) zone) to wet cool temperate (delineated by the Interior Cedar-Hemlock (ICH) zone) to mild subalpine boreal (delineated by the Montane Spruce (MS) zone) (Krajina 1969). Glaciated igneous, metamorphic, and sedimentary rocks, glacial landforms, and colluvium dominate the landscape, although areas of fluvial and lacustrine deposits are encountered. In the mountains, thick deposits of glacial till are restricted to valley bottoms and adjacent lower slopes. Soils vary in texture and range from Brunisols to Luvisols to Podzols (Canada Soil Survey Committee 1978) with Moder to Mor humus formation (Green et al. 1993).  Forest communities in the study area are predominantly coniferous and vary in age, composition, and structure according to the variation in site and the history of disturbance. The  8  most common tree species are Douglas-fir, ponderosa pine (Pinus ponderosa Dougl. ex P. & C Lawson), lodgepole pine, and trembling aspen in the Interior Douglas-fir (IDF) zone; western hemlock, western redcedar, and paper birch in the Interior Cedar - Hemlock (ICH) zone; and lodgepole pine, hybrid spruce, and subalpine fir in the Montane Spruce (MS) zone. A more complete description of the study area is given in Holland (1976), Valentine et al. (1978), and Meidinger and Pojar (1991).  125°  120°  115°  Figure 2.1 Range of western larch in B.C. The location of major and minor sampling areas are indicated by the larger and smaller points, respectively. 9  3. MATERIALS AND METHODS  3.1 Selection of Study Sites and Sampling The presence of western larch in the study area is variable, as it has depended primarily on the history of disturbance by wildfires. Larch forms most often a minor or major admixture in mid-seral, coniferous stands across a wide range of sites. In general, its presence decreases with increasing latitude, precipitation, and elevation (i.e., decreasing temperature). To obtain the widest possible range in site quality, study sites were deliberately selected across the entire spectrum of climatic, soil moisture, and soil nutrient conditions found within in the study area.  Within the IDF zone, study sites were located in three subzones: Very Dry Hot IDF (IDFxh), Dry Mild IDF (IDFdm) and Moist Warm IDF (IDFmw). Within the ICH zone, study sites also were located in three subzones: Dry Warm ICH (ICHdw), Moist Warm ICH (ICHmw), and Moist Cool ICH (ICHmk). Within the MS zone, study sites were located in two subzones: Dry Mild MS (MSdm) and Dry Cool MS (MSdk) (Meidinger and Pojar 1991). A detailed description of climatic, vegetation, and soil characteristics for these subzones is given in Lloyd et al. (1990) and Braumandl and Curran (1992). Selected climatic characteristics of the subzones are given in Table 3.1.  Within each subzone, study sites were located in naturally established, unmanaged, more or less even-aged, mid-seral, western larch-dominated stands, which developed after wildfires. The selected stands were uniformly stocked (from 60 to 90% tree layer cover), ranged considerably in age (from 35 to 158 years @ bh) and site index (from 6.9 to 29.3 m @ 50 yr bh)  10  Table 3.1  Means of selected climatic characteristics for the eight study subzones : Very D r y Hot I D F (IDFxh), D r y M i l d I D F (IDFdm), Moist Warm I D F (TDFmw), D r y W a r m I C H (ICHdw), Moist Warm I C H (ICHmw), Moist Cool I C H (ICHmk), Dry M i l d M S (MSdm), and Dry Cool M S (MSdk). The means were calculated from data obtained from Environment Canada (1982). Precipitation is in mm and temperature in Celsius 0  Characteristic  IDFxh  IDFdm  TDFmw  ICHdw  ICHmw  ICHmk  MSdm  MSdk  Mean annual precipitation  409  446  507  746  947  722  605  590  Mean precipitation MaySeptember  163  193  210  246  297  333  199  229  20  26  35  47  31  28  23  Mean precipitation of the driest month Mean precipitation of the wettest month  54  61  64  107  153  106  83  87  Mean annual temperature  6.0  5.0  6.1  7.5  6.6  4.2  3.0  3.4  Mean temperature of the coldest month  -7.6  -9.1  -6.7  -4.1  -5.5  -9.3  -8.3  -10.2  Mean temperature of the warmest month  17.8  17.6  17.9  19.1  18.0  15.0  14.4  15.6  Frost free period (days)  111  105  108  144  134  ND  69  68  1653  1528  1640  1881  1685  1241  991  1209  Degree days >5°C  2  Two lowercase letters abbreviations used for subzones designate relative precipitation regime: x - very dry, d - dry, m - moist, w - wet, and v - very wet; and relative temperature regime: h - hot, w - warm, m - mild, k - cool, and c - cold (Meidinger and Pojar 1991). ND - no data obtained. 11  and were without signs of obvious damage and no history of growth suppression. The presence or absence of possible growth suppression was examined visually on increment cores. The number of study stands by subzones is given in Table 3.2, and selected characteristics of study sites are compiled in Appendix 1.  Each selected stand had a more or less uniform, upper tree layer which featured dominants of western larch. In each study stand, a 20 x 20 m (0.04 ha) sample plot was located to represent an individual ecosystem that was relatively uniform in stand, understory vegetation, and soil characteristics. In order to prevent bias in plot selection, the first plot within a candidate stand that met the predetermined criteria was chosen.  Western larch productivity was estimated by site index (m @ 50 years bh). In each sample plot, the three largest diameter (dominant) larch trees, with no obvious evidence of growth abnormalities and damage, were measured for age at breast height, using an increment borer, and height, using a clinometer. The average height and breast height age for the measured trees at each plot was calculated, and the larch site index for each study plot was determined using the height growth functions developed by Brisco (1999).  Table 3.2  IDFxh 31  Number of study stands stratified according to the eight Abbreviations for subzones as in Table 3.1. IDFmw 12  IDFdm 53  ICHmw 87  ICHdw 22  ICHmk 36  study  subzones.  MSdm  MSdk  38  37  12  3.2 Estimates of Climate, Soil Moisture, and Soil Nutrient Regimes Site and vegetation characteristics of each study stand were described using the site diagnosis procedure of Green and Klinka (1994). Biogeoclimatic subzone, representing climatic regime, was identified using maps obtained from the Kamloops and Nelson regional offices of the B C Ministry of Forests. Each site was identified in the field to one of eight relative soil moisture regimes (RSMRs) and to one of five soil nutrient regimes (SNRs). Field identification of RSMRs and SNRs was based on keys, using a combination of topographic and soil morphological properties (Appendices 2 and 3).  Despite the fact that each regional climate has a unique soil moisture gradient, the same RSMRs are used to describe soil moisture conditions of climatically different sites (Krajina 1969, Klinka et al. 1989). However, comparison of soil moisture conditions across a range of climates requires an absolute scale (i.e., conversion of RSMRs into actual soil moisture regimes (ASMRs)). The A S M R (a class of an actual soil moisture gradient) describes the average amount of soil water that is actually available for plant growth during the growing season. The gradient is composed of ten ASMRs, ranging from extremely dry (representing sites with a prolonged, chronic water deficit) to fresh (representing sites with no water deficit and surplus) to very wet (representing sites with a prolonged water excess) (Appendix 4).  In this study, field-estimated RSMRs were converted to ASMRs using the criteria and methods proposed by Klinka et al. (1989) (Table 3.3, Appendix 4). First, moist, very moist, wet, and very wet ASMRs were determined according to the occurrence and depth of the growingseason groundwater table or gleyed soil horizon. Second, the actual 13  Table 3.3  RSMR  Conversion table of relative to actual soil moisture regime (RSMRs to ASMRs) for the eight study subzones. ASMRs of zonal sites are shown outlined and shaded. Abbreviations for subzones as in Table 3.1; abbreviations for ASMRs are: X D extremely dry, E D - excessively dry, V D - very dry, M D - moderately dry, SD slightly dry, F - fresh, M - moist, V M - very moist, W - wet, V W - very wet.  JDFxh  IDFmw  JDFdm  Subzone ICHdw ICHmw  ICHmk  MSdm  MSdk  Actual Soil Moisture Regime 0  EX  VD  VD  VD  VD  VD  VD  VD  1  ED  VD  VD  MD  MD  MD  MD  MD  2  VD  VD  VD  MD  MD  MD  MD  MD  3  VI»  \1D  Ml)  M>  SD  SI)  SI.)  SI)  4  Ml)  \1D  SD  SD  F  F  SI)  SI)  5  SD  SD  SD  F  M  M  F  F  6  F  F-M  F-M  M  VM  VM  M  M  7  M-VM  VM-W  VM-W  VM-W  W  W  VM-W  VM-W  evapotranspiration/potential evapotranspiration ratio (Et/E ), max  using the Energy/Soil Limited  model of Spittelhouse and Black (1981), was calculated in each study subzone for sites having RSMRs of 4 (so called mesic or intermediate sites) to determine whether they were waterdeficient or not. If they were found to be non-deficient, they were converted to fresh or moist ASMRs, depending on the presence or absence of a utilization phase in annual water balance, respectively; if they were found to be deficient, they were converted to the appropriate ASMRs according to the calculated E^E  r a t max  i ° - Third, the remaining RSMRs (<4) were converted to  water-deficient A S M R s according to the estimated water-holding capacity of the soils in the field and the correlations between R S M R s and A S M R s established in other studies (e.g. K l i n k a and Carter 1990, K l i n k a et al. 1996b, Kayahara et al. 1997). Whenever understory vegetation was well developed, conversions were verified by indicator plant analysis (Klinka et al. 1989, Green and K l i n k a 1994). The soil moisture spectra of the study stands were compared to the standard spectra using V T A B R E P O R T E R (Emanuel 1998) and each study stand was assigned to one of the five water-deficient A S M R s .  To some extent, A S M R s of rapidly to imperfectly drained soils imply soil aeration regimes (SARs), as soil aeration usually decreases with decreasing depth of groundwater table from moist to very wet sites depending on soil drainage. However, S A R s were not estimated in this study, and it was assumed that all the study stands had good or adequate aeration.  The five S N R s (classes framed along a soil nutrient gradient) represent sites with the levels of plant-available soil nitrogen ranging from low levels (very poor S N R ) to high levels (very rich S N R ) . Although not quantified in this study, the quantitative characterization of S N R s in several other studies suggests a possible relationship between field-identified, qualitative and quantitative S N R s of the study sites (Appendix 5). Several of the study sites in the Rocky Mountains Trench featured calcareous soils, which should be recognized as a special S N R , and were not included in the study data set. A s with A S M R s , whenever possible, the assignment of study sites into S N R s was augmented by indicator plant analysis (Klinka et al. 1989, Green and K l i n k a 1994).  15  3.3 Analysis of the Relationship between Site Index and Climate  Stands on zonal sites were analyzed to examine the influence of climate on the height growth of western larch, with minimum confounding effects of local topography and soils. The zonal concept (e.g., Hills 1952, Krajina 1969, Daubenmire 1976) presumes that the vegetation on sites that represent intermediate topographic and edaphic conditions, relative to existing extremes found within an area influenced by a specific regional climate, will reflect the influence of that climate on vegetation most strongly. The zonal sites occurred on flats, gently sloping heights of land, or mid-slopes where the influence of aspect was minimized, and had RSMRs of 3 and 4 and poor and medium SNRs. In total, 151 stands on zonal sites were selected for the analysis (Table 3.4).  Table 3.4  IDFxh  18.9  (1.7) n=12  Western larch site index means (in boldface), standard deviations (in parentheses) and number of stands on zonal sites stratified according to study subzone. Abbreviations for subzones as in Table 3.1. IDFdm  18.8  (2.1) n=34  IDFmw  ICHdw  21.4  22.4  (2.0) n=3  (1.1) n=4  ICHmk  20.9  (1.5) n=19  ICHmw  MSdk  MSdm  20.8  20.8  21.6  (1.8) n=44  (1.7) n=18  (1.8) n=17  Stands on sites with the same A S M R and SNR were analyzed to further examine the influence of climate on larch site index. The selected stands were on sites that all had poor and medium SNRs, and were either very dry (Set 1), moderately dry (Set 2), or slightly dry (Set 3)  16  (Table 3.5). In total, 213 stands were selected for the analysis.  In both analyses, following calculation of the mean larch site index for each study subzone, a simple comparison was made to determine if the differences in the mean site index between any of the subzones were large enough to merit statistical testing. A difference of 2 meters (or 10%) or larger was considered to warrant testing. One-way analysis of variance (a = 0.05) and the Tukey pair-wise comparison test (a = 0.05)(Chambers et al. 1983) were used to detect the presence of differences in the mean site index between study subzones.  Table 3.5  Western larch site index means (in boldface), standard deviations (in parentheses) and number of stands on sites of poor and medium soil nutrient regime stratified by actual soil moisture regime and subzone. Abbreviations for subzones as in Table 3.1.  Actual Soil Moisture Regime  Subzone ICHdw ICHmk  IDFxh  IDFdm  Very Dry (Set 1)  14.6 (2.4) n=6  14.4 (1.4) n=3  ND  -  -  Moderately Dry (Set 2)  18.9 (1.7) n=12  18.9 (2.1) n=34  ND  Slightly Dry (Set 3)  21.7 (0.4) n=3  18.9 (2.1) n=3  ND  IDFmw 1  -  -  ICHmw  MSdk  MSdm  14.6 (0.8) n=3  14.7 (1.4) n=4  ND  14.3 (1.0) n=3  20.8 (0.7) n=3  17.6 (1.7) n=7  17.6  18.4  (1.8) n=ll  (1.6) n=12  22.4 (1.1) n=4  20.9 (1.5) n=18  20.7 (1.8) n=44  20.8 (1.7) n=18  ND  -  18.5 (1.6) n=8 21.6 (1.8) n=17  1 N D - no data were obtained due to the absence or sporadic occurrence of western larch under some edaphic conditions.  17  3.4 Analysis of Relationships between Site Index and Soil Moisture and Nutrient Regimes  Following identification of ASMR and SNR for each sample plot (Appendix 1), study stands were stratified according to edatopes (Table 3.6). Each edatope represents a combination of a particular RSMR or ASMR and SNR - i.e. a cell on a two-dimensional matrix (edatopic grid).  It would be desirable for studies of site - productivity relationships to have equal representation of samples with respect to climatic and edaphic factors within the native range of western larch. However, this situation was not possible because certain combinations of climatic, soil moisture, and soil nutrient regimes did not occur or occurred rarely. The usual sequence of edatopes in a topographically diversified landscape proceeds in a diagonal direction from water-deficient and poor sites to water-surplus and rich sites. Such a sequence was present and sampled in the study area. Larch stands were poorly represented on excessively dry, moist, very moist, and wet ASMRs and on very poor and very rich SNRs (Table 3.6).  To minimize the confounding effect of climate when examining the effect of A S M R and SNR on western larch site index, the entire data set of 315 stands was divided into two subsets (climatic groups) according to the result of the climate analysis. The stands from the IDF zone formed one group (IDF group) and those sampled in the ICH and MS zones formed the other group (ICH-MS group). To facilitate the analysis, the study stands were stratified by edatopes separately for each climatic group. The edatopic grids were used as a visual means for selecting stands for the analysis. For each climatic group, two blocks of edatopes (Block 1 and 2) were selected for the analysis. Each block consisted of two or three sequences of adjacent edatopes, with each sequence comprised of edatopes with the same SNR but different ASMRs (hygrosequences, Major 1951)(Table 3.7, 3.8).  18  Table 3.6  Number of stands, means (in bold print) and standard deviations (in parentheses) of western larch site index (m @ 50 yrs bh) for the 315 study sites, stratified according to actual soil moisture and soil nutrient regimes.  Actual soil moisture regime  Very poor  Excessively dry  3  Soil nutrient regime Poor Medium  Rich  Very rich  ND  ND  ND  2  ND  1  ND  8 . 6  (2.21) Very dry  Moderately dry  Slightly dry  6  14 1 4 . 3  1 5 . 4  1 6 . 6  (1.36)  (1.49)  (1.47)  (1.33)  ND  ND  45  44  6  1 7 . 2  1 9 . 9  2 0 . 8  (1.15)  (1.50)  (2.77)  52 1 9 . 9  (1.06) Fresh  8  1 3 . 2  ND  ND  58 2 1 . 9  (1.72)  ND  ND  11 2 4 . 1  1 (NA)  Very moist  ND  ND  (1.72)  18  2 6 . 7  ND  (1.67) 2 2 6 . 2  (0.08) 4 2 0 . 6  Wet  ND  ND  ND  ND  2 3 . 7 0  2 4 . 2  (0.78) Moist  28  ND  5 2 5 . 6  (0.99) 5 2 6 . 8  (0.76) 1 1 8 . 7  (2.10)  (NA )  1  ND  2  2 0 . 4  (NA)  N D - no site index data were obtained due to the absence or sporadic occurrence of western larch under some edaphic conditions. 19  2  N A - not available  Table 3.7  Edatopic grids for the DDF group showing the number of stands sampled in each edatope and those edatopes selected in: (A) Block 1 for analysis and (B) Block 2 for analysis. Selected edatopes are shaded in grey. T w o identical edatopic grids are presented in order to clearly show edatope selection for each block.  (A) Actual moisture  Soil nutrient regime Very poor  Poor  Medium  Rich  Very rich  regime Excessively dry  1  Very dry  2  Moderately dry  1111111  j^H||jH|j|f  19  28  4  '  1  Slightly dry Fresh  15 1  Moist  1  1  1  3  Very moist  1  Wet  (B) Actual moisture  Soil nutrient regime Very poor  Poor  Medium  7  3  Rich  Very rich  regime Excessively dry  1  Very dry  2  Moderately dry Slightly dry Fresh Moist Very moist  19 1  • 28 . Y :  •\  . 7;;. ^f^Bf* - 4 t  l  15 1  1  1  3 1  Wet  20  Table 3.8  Edatopic grids for the ICH-MS group showing the number of stands sampled in each edatope and those edatopes selected in: (A) Block 1 for analysis and (B) Block 2 for analysis. Selected edatopes are shaded in grey. Two identical edatopic grids are presented in order to clearly show edatope selection for each block.  Actual moisture  Soil nutrient regime Very poor  Poor  Medium  Rich  Very rich  regime Excessively dry  2  Very dry  4  Moderately dry  (IBiilBIIB 2  •NiiiHB  Slightly dry  13  Fresh  18  10  4  Moist  1  1  2  Very moist  4  Wet  1  (B) Actual moisture  Soil nutrient regime Very poor  Poor  Medium  Rich  Very rich  regime Excessively dry  2  Very dry  4  7  5 .  : 2  Moderately dry  26  16  Slightly dry  51  • 51  13  Fresh  18  10  4  Moist  1  1  2  Very moist  4  Wet  1  21  Analysis of variance (a = 0.05) were used to determine whether ASMR, SNR, and the ASMR*SNR interaction had a significant effect on western larch site index. A significant interaction implies that the effects of soil moisture and soil nutrients on site index are not additive. Plotted site index data for each block were used to demonstrate the trend in site index in relation to change in ASMRs and/or SNRs. In view of missing and poorly represented edatopes, and the selection requirements, not all edatopes were included in the analysis. It was assumed that the sequences of edatopes excluded from the analysis would exhibit similar trends in site index as those as those that were analyzed.  The SYSAT statistical package (1997 Version 7.0) was used to carry out all statistical tests. All figures relating to the statistical tests were produced using SIGMA PLOT (1997 Version 4.00).  22  4. R E L A T I O N S H I P S B E T W E E N S I T E I N D E X A N D C L I M A T I C , S O I L M O I S T U R E AND SOIL NUTRIENT R E G I M E S  4 . 1 . Relationships between Site Index and Climate  Analysis of variance (a = 0.05) indicated that there was a significant change in western larch site index with biogeoclimatic subzone (Table 4.1). The Tukey's multiple range test (Table 4.2) showed that the significant differences occurred primarily between the IDF subzones and the other study subzones. There were no significant differences in site index between the IDFxh and IDFdm subzones, and among any of the ICH and MS subzones, with the Moist Warm IDF (IDFmw) subzone being not significantly different from any study subzone. A visual summary of the variation in site index on zonal sites in relation to the eight study subzones is given in Figure 4.1. The highest mean site index value occurred in the Dry Warm ICH (ICHdw) subzone, while the lowest values were associated with the Very Dry Hot IDF (IDFxh) and the Dry Mild IDF (IDFdm) subzones.  The differences in western larch site index on zonal sites among subzones can be attributed either to the differences in precipitation (reflected in actual soil moisture conditions), temperature, or both. This comparison, which was based on zonal sites with RSMRs of 3 and 4 and poor and medium SNRs, suggests that the differences in site index could be explained by the differences in ASMRs because ASMRs of zonal sites varied with subzone (Table 3.3). However, this comparison, did not address the possible influence of temperature.  23  Table 4.1  Analysis of variance for mean site index on zonal sites in eight study subzones (a = 0.05).  Source  Sum of squares  Degrees of freedom  Mean square  F-ratio  P  Subzone  175.90  7  25.13  7.61  0.00  Error  472.00  143  3.30  Table 4.2  IDFxh 18.9  b  Western larch site index means on zonal sites stratified according to study subzone. Values in the same row with different lower case superscripts are significantly different (a = 0.05). Abbreviations for subzones as in Table 3.1. IDFdm 18.8  b  IDFmw 21.4  a b  ICHdw  ICHmk  ICHmw  MSdm  MSdk  22.4  20.9  20.8  21.6  20.8  a  a  a  a  a  Comparison of western larch site index on very dry (Set 1), moderately dry (Set 2), and slightly dry (Set 3), poor and medium sites showed no significant change with subzone (Tables 4.3 and 4.4). Testing was not considered necessary for Set 1 because the spread in site index between subzones was only 0.4 meters (Table 3.5). Thus, the results of the comparisons of site index on sites with equivalent soil moisture and nutrient conditions between subzones suggest that height growth of larch is not temperature-limited. Taking into account the results of both comparisons, it appears that height growth of larch in the province is moisture, but not temperature, dependent.  24  30  25  T  o  20 H -  •HI  X  u -a c B c/5  II  III Ili  >  , ?  10 Pi  IBI  [  '  I  IDFxh IDFdm IDFmw ICHdw ICHmw ICHmk MSdm  MSdk  Biogeoclimatic subzone  Figure 4.1 Bar graph of western larch site index on zonal sites in eight study subzones. Error bars are for standard deviation. Abbreviations for subzones as in Table 3.1.  Table 4.3  Set 2: Analysis of variance for mean site index on moderately dry, poor and medium sites in seven study subzones (a = 0.05).  Source  Sum of squares  Degrees of freedom  Mean square  F-ratio  P  Subzone  34.58  6  5.76  1.69  0.13  Error  272.70  80  3.41  25  Table 4.4  Set 3: Analysis of variance for mean site index on slightly dry, poor and medium sites in seven study subzones (a = 0.05).  Source  Sum of squares  Degrees of freedom  Mean square  F-ratio  P  Subzone  32.13  6  5.36  1.80  0.11  Error  300.44  101  2.98  4.2 Relationships between Site Index a n d Soil M o i s t u r e a n d Nutrient Regimes  4.2.1 The IDF Group  Analysis of variance (a = 0.05) for each of the two blocks of the selected edatopes for the IDF group, indicated that both ASMR and SNR had a significant effect on western larch site index (Tables 4.5 and 4.6). However, the ASMR*SNR interaction was not significant in either block (P = 0.13 for Block 1, P = 0.48 for Block 2), suggesting that the influence of soil moisture and nutrients on site index is consistent across the selected range of edatopes.  Line graphs of site index means for five hygrosequences (poor and medium SNRs in Block 1 and poor, medium, and rich SNRs in Block 2) in relation to very dry, moderately dry, and slightly dry ASMRs in Block 1, and in relation to moderately dry and slightly dry ASMRs in Block 2 showed consistent trends in change of site index with edatopes (Figure 4.2 (A) and (B)). In general, western larch site index increased (1) regardless of SNR, with increasing soil moisture, with the rate of change being faster from very dry to moderately dry sites than from moderately dry to slightly dry sites, and, (2) regardless of ASMR, with increasing availability of soil nutrients (nitrogen). 26  Table 4.5  Analysis of variance for mean site index in B l o c k 1 of the IDF climatic group ( a = 0.05).  Source  Sum of squares  Degrees of freedom  Mean square  F-ratio  P  SMR  95.04  2  47.52  23.98  0.00  SNR  44.17  1  44.17  22.29  0.00  SMR*SNR  2.91  2  1.46  0.74  0.48  Error  116.92  59  1.98  Table 4.6  Analysis of variance for mean site index in B l o c k 2 of the IDF group ( a = 0.05).  Source  Sum of squares  Degrees of freedom  Mean square  F-ratio  P  SMR  17.82  1  17.84  6.88  0.01  SNR  62.70  2  31.35  12.11  0.00  SMR*SNR  10.82  2  5.41  2.09  0.13  Error  176.06  68  2.59  4.2.2 The I C H - M S Climate Group  Analysis of variance ( a = 0.05) for each of the two blocks of the selected edatopes for the I C H - M S group produced similar results as for the IDF group (Tables 4.7 and 4.8). The A S M R had a significant effect on western larch site index in both blocks, and the A S M R * S N R 27  (B)  Figure 4.2 Means and standard error of means of western larch site index for (A) poor medium hygrosequences in relation to very dry, moderately dry, and slightly A S M R s for Block 1 of the IDF group and (B) for poor, medium, and hygrosequences in relation to moderately dry and slightly dry A S M R s for B l o c k the IDF group  and dry rich 2 of  28  interaction was not significant in either block (P = 0.17 for Block 1, P = 0.16 for B l o c k 2) suggesting again that the influence of soil moisture and nutrients on western larch site index is consistent across the range of selected edatopes. Although significant in Block 1, the effect of S N R was marginally non-significant in Block 2 (P = 0.06).  Table 4.7  Analysis of variance for mean site index in Block 1 of the I C H - M S group.  Source  Sum of squares  Degrees of freedom  Mean square  F-ratio  P  SMR  426.30  2  213.15  108.39  0.00  SNR  111.28  2  55.64  28.29  0.00  SMR*SNR  12.71  4  3.17  1.62  0.17  Error  322.51  164  1.97  Table 4.8  Analysis of variance for mean site index in Block 2 of the I C H - M S group.  Source  Sum of squares  Degrees of freedom  Mean square  F-ratio  P  SMR  378.61  4  94.65  40.40  0.00  SNR  8.63  1  8.63  3.68  0.06  SMR*SNR  15.77  4  3.94  1.68  0.16  Error  255.38  109  2.34  29  Line graphs of site index means for five hygrosequences (poor, medium, and rich S N R s in B l o c k 1, and medium and rich S N R s in Block 2) in relation to very dry, moderately dry, and slightly dry A S M R s in Block 1, and in relation to very dry through fresh A S M R s in B l o c k 2 showed consistent trends in change of site index with edatopes, with one exception (Figures 4.3 (A) and (B)). In general, western larch site index increased (1) regardless of S N R , with increasing soil moisture and, (2) regardless of A S M R , with increasing availability of soil nutrients (nitrogen), with the exception of fresh sites where there was little change in site index with change in S N R (Figure 4.3(B)). Non-significant variations in site index with S N R on fresh and moist sites are apparent in Table 3.6 which shows the pattern of site index for all study sites.  4.3 Discussion  To determine the influence of climate (i.e., precipitation and temperature) on western larch productivity, a two-step analysis was employed. In the first step, site index on zonal sites was compared among eight study subzones (zonal climoseqence), and in the second step, comparison included three climosequences, each with specific A S M R . Differences in site index between zonal sites could be explained either by differences in precipitation (if reflected in actual soil moisture conditions) or in temperature, or both. If zonal sites under comparison vary in A S M R , then the differences in site index can be attributed to the differences in precipitation between study subzones. If sites with equivalent soil moisture conditions across different subzones do not vary in site index, then it can be concluded that larch site index is not influenced by temperature across the study subzones.  30  (A)  28  26 -  12  ,  ,  VD  MD  -I  rSD  Actual soil moisture regime  (B)  26  14  -I  1  1  1  VD  MD  SD  1-  F  Actual soil moisture regime  Figure 4.3 Means and standard error of means of western larch site index for (A) poor, medium and rich hygrosequences in relation to very dry, moderately dry, and slightly dry A S M R s for Block 1 of the I C H - M S group and (B) for medium, and rich hygrosequences in relation to very dry, moderately dry, slightly dry, and fresh A S M R s for B l o c k 2 of the I C H - M S group.  31  In the B E C system, classes delineated at the regional level of integration through floristic differences in zonal vegetation (e.g., biogeoclimatic subzones), are expected to be climatically different. Conceptually, each subzone should represent a distinct segment of a regional climatic gradient. However, testing subzones for the strength of climatic differences is fraught with difficulties due to the lack of long-term climatic data and in making decisions at which point any particular difference in climatic characters becomes ecologically significant.  Assuming that each of the eight study subzones represents a distinct regional ecosystem influenced by a different climate, then it could be inferred that differences in forest productivity (measured by site index on zonal sites) would exist among each subzone. This assumption could not be supported, albeit based on testing only one tree species, as significant differences in western larch site index occurred only between two groups of subzones. The I D F m w subzone was transitional between the groups in both site index and climatic characteristics (Tables 3.1 and 4.2). However, the small sample size (n=3) on zonal sites and large variation in site index within that sample, may have also resulted in the IDFmw subzone not being significantly different in site index from any of the other subzones.  The arrangement of the subzones, based on significant differences in the site index of western larch, into the I D F climate group and the I C H - M S climate group seems to reflect differences in mean annual precipitation between the subzones. Climate records indicate that the three I D F subzones sampled have the lowest mean annual precipitation levels of any of the subzones sampled (Table 3.1), and consequently significantly lower mean site index values. A s such, zonal sites in the I D F subzones are water-deficient (moderately dry) while in the I C H and  32  MS subzones they are fresh and slightly dry, respectively. Thus, larch growth on the IDF zonal sites is water-limited while on the ICH and MS zonal sites some factor other than water is limiting growth.  A variety of temperature related measures (Table 3.1) appear to suggest that temperature has little effect on the site index of western larch among the subzones studied. Temperature does not account for the significant differences in site index between the IDF and MS/ICH subzones. The lack of significant differences in site index measures between the MS and ICH subzones, despite much cooler mean annual temperatures, cooler mean temperature warmest month and shorter frost free period in the MS subzones, indicates that temperature differences related to climate was not significantly affecting western larch site index. A number of observations and 1  2  planting trials (Newsome et al. 1992, Lloyd and Jaquish pers. comm .) have shown that western larch can remain very productive when planted well outside its natural range in locations, where growing season temperature and frost free periods are much cooler and shorter respectively. During data collection for this study, several sites were located within the lower limits of the ESSF zone; however, they were excluded from the analysis due to a small number of replicas per subzone. Compared to the study subzones, the climate of these ESSF subzones had a shorter growing season and colder growing-season temperatures. A simple comparison suggested that the western larch site index on these sites was very similar to that measured on sites with similar A S M R and SNR, but located in climates that are more temperate.  1  Dennis L l o y d , B . C . Ministry of Forests, Kamloops Forest Region., Phone:(250) 828-4131  33  Further examination of the effect of climate on the site index of western larch was carried out by comparing the mean site index of similar edatopes between a number of subzones (Table 3.5, 4.3, and 4.4). Testing seems to indicate that temperature plays a very insignificant role in influencing the site index of western larch within its range in B.C. Climate and A S M R are not independent of one another. By maintaining a similar ASMR across subzones, the effect of variable precipitation is eliminated and thus the effect of temperature on the site index of western larch should be seen. Large differences in growing season temperature and length do exist between subzones (Table 3.1); however, these differences do not appear to manifest themselves in site index measures. Therefore, within the range of western larch in B.C., one could speculate that significant change in larch productivity, due to climate differences, would only be expected when those differences were in annual precipitation.  The reason for the lack of significant difference in site index of western larch between each subzone cannot be resolved with certainty. It may be that either the subzones of each climatic group were not climatically different or that climatic differences among them were minor and without a measurable effect on larch site index. A plausible explanation for the similarity of site index between the IDF subzones or among the ICH and MS subzones could be in the similarity in actual evapotranspiration. Vascular plant activity and hence, forest productivity, should increase with increasing actual evapotranspiration, which depends on temperature and soil water (i.e., precipitation) (Major 1951). Either temperature and precipitation differences among subzones of each climatic group are so minor that they do not  2  Barry Jaquish, Kalamalka Research Station, B . C . Ministry of Forests, Vernon, B . C . , Phone:(250) 549-4477  34  exert a significant influence on forest growth via actual evapotranspiration, or compensating effects between precipitation and temperature result in similar actual evapotranspiration. Zonal sites in one subzone with a higher growing-season temperature (i.e., higher potential evapotranspiration) but lower precipitation may have the same or similar actual evapotranspiration (i.e., potential productivity) as those in another subzone with a lower temperature (i.e., lower potential evapotranspiration) but higher precipitation. Thus, due to the presence of a weak actual evapotranspiration gradient among the subzones of each of the IDF and ICH-MS groups, it would suffice to describe the climatic effect on western larch site index in the study area by low and high precipitation strata. Wang and Klinka (1996), who studied the variation in site index of lodgepole pine, interior spruce, and subalpine fir on zonal sites in ten subzones of the Sub-Boreal Spruce zone, came to a similar conclusion.  The distribution of study stands according to soil moisture and nutrient regime shows that an abundance of stands (199 of the total 315 sampled) occurred on sites of moderately dry and slightly dry A S M R and poor or medium SNR (Table 3.6). This suggests, as does the literature, that western larch is a species of moderate ecological amplitude (Fielder and Lloyd 1992, Schmidt and Shearer 1992, Klinka et al. 1998).  In view of the distribution of the study sites (Table 3.6), testing the effects of ASMR, SNR and their interaction on western larch site index could be done only for the central portion of the edatopic grid (Figures 4.2, 4.3, Tables 3.7, 3.8). Thus, the assumption had to be made that the variation in site index outside the sampled region would exhibit similar trends. However, this assumption may not be valid for water-surplus sites on which the effects of SNR on site  35  index appeared to have decreased (Table 3.6). Excluding very moist and wet sites from further investigations is of little practical significance, as such sites are infrequent in the study area and larch grows on these sites very infrequently and less productively compared to other tree species.  The maximum site index (about 26 m) of western larch occurred on moist sites, albeit with only minor differences between medium, rich, and very rich sites (Table 3.6). The minimum mean site index value was found on excessively dry and very poor sites. Site index sharply decreased with increasing water surplus from moist through wet sites; however, a small sample size prevented testing this trend. Spitzer and Stark (1982) reported that the growth of western larch was superior on rapidly drained sites compared to sites with restricted rooting zones and slow water percolation. Whether larch occurs infrequently on these sites because of the lack of wildfires or competition or because it poorly tolerates soil water surplus needs to be resolved in other studies. Site index also decreased with decreasing soil moisture from moist through excessively dry sites, and within any water-deficient A S M R , it increased with increasing S N R (Table 3.6, Figures 4.2 and 4.3). A general, though not significant, trend of an increasingly positive effect of increasing S N R on site index with increasing A S M R in the range from very dry to slightly dry sites was also detected. The edaphic conditions supporting the optimum growth and the pattern of change in larch site index in relation to edatopes are similar to those reported for several other tree species (see Green et al. 1989; K l i n k a and Carter 1990; Wang et al. 1994; Wang and K l i n k a 1996; Kayahara and Pearson 1996; Chen etal. 1998).  The rate of increase or decrease in site index of western larch along a soil moisture gradient was generally greater than the rate of increase along a soil nutrient gradient, with the  36  positive effect of soil moisture changing into a negative one from moist through wet sites, as soil aeration decreased with increasing water surplus. For example, site index increased by about 4 m from very dry to moderately dry sites, about 3 m from moderately dry to slightly dry sites, and only to about 2 m from slightly dry through moist sites compared to about less than 3 m increase from poor to rich sites within the water-deficient region of the edatopic grid (Table 3.6). The greater influence of soil moisture than soil nutrients on forest growth was also reported in other studies (see Green et al. 1989; Klinka and Carter 1990; Wang et al. 1994; Wang and Klinka 1996; Kayahara and Pearson 1996; Chen et al. 1998).  The substantial increase in site index values from the very dry to the moderately dry moisture regime (Figures 4.2 (A) and 4.3 (A and B)), may be reflective of western larch's inability to control water use. At some point between these two A S M R values there seems to be a threshold, below which the amount of water necessary for vigorous western larch growth is not available and height is severely reduced. Above the threshold enough soil moisture is available for western larch to realize its full growth potential.  To achieve a rate of height growth sufficient to remain competitive, western larch must assimilate large amounts of carbon and as a result has high photosynthetic rates. This characteristic along with an inability to control stomata openings, results in high water use by western larch compared to its associated species (Higgens et al. 1987). This greater water demand may, in part, account for the absence of larch on dry sites and its abundance on mesic sites (Gower and Richards 1990, Gower et al. 1992). This hypothesis seems to be supported by the distribution of sample plots acquired in this study (Table 3.6).  37  An exception to the effect of SNR on site index (P = 0.06) occurred in Block 2 of the ICH-MS climatic group (Table 4.8, Figure 4.3(B)). Although the P was close to being significant and the effect of the ASMR*SNR interaction was insignificant, examination of Table 3.6 and Figure 4.3(B) suggested that on sites without a water deficit or surplus (i.e., fresh and moist sites) there is only a marginal or no increase in site index with increasing SNR. Despite the small sample size for moist sites, it appears that the growth response of western larch to an increasing supply of soil nutrients (nitrogen) is not consistent across the entire soil moisture gradient and differs with respect to soil moisture conditions (i.e., on water-deficient sites the response is significant while the fresh and moist there is little or no growth response). It may be that once all water and essential nutrient needs are met, the growth of larch does not benefit from increased nutrient supply due to the efficient use of nitrogen.  4.4 Conclusions  Climate, represented by biogeoclimatic subzones, had a significant effect on site index of western larch; however, due to compensating effects between temperature and precipitation, significant differences occurred only between two groups: lower-precipitation (Interior Douglasfir) and higher-precipitation (Interior Cedar-Hemlock and Montane Spruce) subzones. Thus the climatic effect on larch productivity was detectable above the subzone or even zone level of generalization (i.e., the productivity gradient does not coincide with the climatic gradient described by biogeoclimatic units). The climatic growth optimum corresponded to the intermediate segment of a regional climatic gradient - wetter temperate climate - that is  38  represented by the Dry Warm Interior Cedar-Hemlock subzone. In relation to edatopes, site index significantly increased from water-deficient to moist sites and decreased from moist to wet sites, and on water-deficient sites, it increased with increasing soil nutrient regime. On waterdeficient sites, estimates of both actual soil moisture regime and soil nutrient regimes had both positive significant and consistent effects on site index, but the effect of soil nutrient regime appeared to be marginal on non-water deficient sites.  39  5. P R E D I C T I O N O F W E S T E R N L A R C H S I T E I N D E X  5.1 Introduction  It was determined in Chapter 4 that any noticeable change in the site index of western larch due to climate was largely a reflection of a change in precipitation and not in temperature. Precipitation and A S M R are not independent of each other and, as such, the effect of climate on site index is accounted for, or represented by, ASMR. Hence, the insignificant differences seen in Chapter 4 when comparing site index on similar edatopes stratified by subzone. Therefore, climate, represented by zone or subzone (or as it was stratified in Chapter 4) into climate group) will not be considered as a prediction term in model development. It was also determined that the interaction of A S M R and SNR (ASMR*SNR) had no significant effect on the site index of western larch. Therefore it will not be included as a prediction term in model development either. Based on these findings, the focus of this section is on the construction and crossvalidation of a single additive model using ASMR and SNR as prediction terms for estimating the site index of western larch in B.C.  5.2 M e t h o d s  A model was constructed using eight soil moisture regime classes and five soil nutrient regime classes as determined in the B E C system. These thirteen independent, categorical variables were coded as dummy variables (Chatterjee and Price 1977). Site index was used as the dependent variable. A cross-validation technique (Neter et al. 1996) was used to validate the  40  model. This required that data be systematically split into two sets prior to model development; one set for model development, called the construction data set (n=2/3 total n), and one set for model validation, called the test data set (n= 1/3 total n). The general linear model, using the least squares procedure, was used to determined the line of best fit for the construction data set. The resulting construction model was initially tested for lack of fit by examining plotted residuals. If no lack of fit was evident, the construction model was then validated.  The model validation procedure involved testing the construction model for bias and precision using the test data set. The construction model was tested for bias by examining the differences in site index between the predicted site index values of the construction model and the measured site index values of the test data set (i.e., error terms) using a paired t-test. M o d e l precision was estimated by comparing the square root of the average squared deviation of the predicted test values (i.e., the root mean square prediction error - root-MSPR) and the mean square error ( M S E ) of the construction model. The function of this test is to assess the relative predictive capability of the regression model (Neter et al. 1996). Following model validation, the test data set and construction data set were recombined so that the entire data set was used to produce a final prediction model. Residuals of this final prediction model were plotted to examine for lack of fit.  In order to assess the practical utility of predicted site index values, the ±95% confidence interval for mean site index estimates, and the ±95% confidence interval for the standard error of the estimate, also called the prediction interval, were calculated.  Regression analysis for producing the model and confidence interval calculations were 41  performed using the SAS statistical package (1996 Version 6.12). The SYS A T statistical package (1997 Version 7.0) was used to carry out all other statistical tests. All figures relating to the statistical tests were produced using SIGMA PLOT (1997 Version 4.00).  5.3 Results A total of 210 plots were used in developing a model for predicting the site index of western larch (Table 5.1). The coefficient of determination (R ) indicated that the developed model 2  explained 84% of the variation in site index due to ASMR and SNR. The standard error of the estimate (SEE) was 1.5 m. Visual inspection of plotted residuals indicated that no significant lack of fit existed between the fitted regression line and the data from which it was derived (Figure 5.1).  Table 5.1  The ASMR SNR prediction model developed from the construction data set (n = 210) relating site index (m @ 50 yrs bh) of western larch to combinations of actual soil moisture and soil nutrient regimes.  SI= 7.9 + 0.0(ED) + 4.8(VD) + 8.4(MD) + 10.8(SD) + 12.5(F) + 14.1(MST) + 7.3(VM) + 7.4(W) + 0.0(VP) + 1.1 (P) + 3.4(M) + 4.5(R) +4.7(VR) R = 0.84 SEE = 1.5 M S E = 2.1 2  The intercept represents E D (excessively dry) and VP (very poor).  42  (A)  3  0  15  20  30  Predicted site index (m )  (B)  ®  e  10  15  20  25  Predicted site index (m @ 50 yrs bh))  Figure 5.1  Residual analysis for the ASMR SNR construction model (n = 210): (A) residual (m) versus predicted site index (m @ 50 yrs bh) and (B) measured versus predicted "site index (m @ 50 yrs bh). 43  When predicted values were compared to measured values on the test data set (n=105), the construction model proved to be unbiased in predicting site index. A paired t-test (a = 0.05) showed the regression model predicted a site index that did not differ significantly from the mean site index of the test data set. The mean difference was 0.09 m between the predicted and measured site index, with p = 0.55. Visual inspection of plotted prediction error values also indicated that no bias in site index prediction existed (Figure 5.2) and showed that the model estimates of the test data site index were usually within ±3 metres of the actual measured values. The calculated MSPR was 2.2 m. The 0.1 metre difference in value between the MSPR and M S E for the construction model indicate that the M S E (2.1m) of the model likely gives a reasonable estimate of the predictive ability of the model (Neter et al. 1996).  Once the model has been validated it is customary to use the entire data set for final model construction (Neter et al 1996). Re-combining the test and construction data sets for estimating a final prediction model resulted in a model that explained 83% of the variance in site index (Table 5.2.). The final model showed virtually no change in R , SEE or M S E values when compared to the construction data set. Visual inspection of plotted residuals indicated no significant lack of fit existed between the fitted regression line and the data from which it was derived (Figure 5.3).  Calculated confidence intervals for the mean are shown in Table 5.3. The prediction interval results are not shown. The estimated values for mean site index of any given edatope have a 95% confidence interval of less than 1 m, except at edatope extremes and when the sample size is small.  44  -4 I5  10  15  20  25  30  35  Measured site index (m @ 50 yrs bh)  Figure 5.2 Prediction error for the A S M R S N R construction model in relation to measured site index (m @ 50 yrs bh) of the test data set (n=105).  Table 5.2  The A S M R S N R prediction model developed from all site data (the combined construction and test data sets (n=315)) relating site index (m @ 50 yrs bh) of western larch to combinations of actual soil moisture and soil nutrient regimes.  SI= 8.6 + 0.0(ED) + 4.6(VD) + 8.1(MD) + 10.6(SD) + 12.3(F) + 13.9(MST) + 7 . 5 ( V M ) + 7.7(W) + 0.0(VP) + 0.7(P) + 2.9(M) + 4.1(R) +4.4(VR) R = 0.83 S E E = 1.5 M S E = 2.2 2  The intercept represents E D (excessively dry) and V P (very poor). 45  -6 I 5  1  1  1  10  15  20  1  25  30  Predicted site index (m )  Figure 5.3 Residual analysis for the ASMR SNR model (n=315). Measured versus predicted site index (m @ 50 yrs bh).  5.4 Discussion The final ASMR SNR model (n = 315) accounted for a high proportion of the variation in site index, indicting that even though the representation of some ASMRs and SNRs was limited, a strong relationship exists between western larch site index and estimates of soil moisture and soil nutrients. As expected, the results for western larch concur with those of similar studies which also showed a strong relationship between the site index of selected tree species and estimates of soil moisture and nutrients as delineated within the working framework of the B E C system (Klinka and Carter 1990, Wang 1992, Wang and Klinka 1996, Chen etal 1998).  46  Table 5.3  Edatopic grid showing the ASMR SNR model (n=315) predicted site index values and ± 95% confidence interval (m), measured mean site index values (m @ 50 yr bh), and SH3EC mean site index values (m @ 50 yr bh) according to actual soil moisture and soil nutrient regimes. Sample sizes indicated refer only to the measured and predicted site index values.  Actual soil moisture regime  Statistic parameters  Very poor  Poor  Soil nutrient regime Medium .  Rich  Very rich  Excessively dry  n Predicted Measured SIBEC  3 8.6±1.7 8.6 NA  0 9.2 ND NA  0 11.5 ND NA  0 12.7 ND NA  0 13.0 ND NA  Very dry  n Predicted Measured SIBEC  6 13.2+0.6 13.2 NA  14 13.8+0.8 14.3 18.0  8 16.1+0.9 15.4 17.0  2 17.3+0.7 16.6 18.6  0 17.5 ND NA  Moderately dry  n Predicted Measured SIBEC  0 16.7 ND NA  45 17.4+0.5 17.2 19.6  44 19.6+0.5 19.9 18.8  6 20.8+0.5 20.8 20.1  0 21.1 ND 23.7  Slightly dry  n Predicted Measured SIBEC  0 19.2 ND NA  52 19.9+0.3 19.9 23.4  58 22.2+0.5 21.9 23.0  28 23.3+0.7 23.7 21.0  0 23.6 ND 19.2  Fresh  n Predicted Measured SIBEC  0 20.9 ND NA  0 21.5 ND 22.9  18 23.8+0.5 21.9 23.7  11 25.0+0.6 23.7 21.9  5 25.2+1.1 25.6 27.0  Moist  n Predicted Measured SIBEC  0 22.5 ND NA  0 23.1 ND 18.9  1 25.4+1.3 26.5 24.8  2 26.6±1.3 26.2 24.1  5 26.8+1.1 26.8 20.0  Very moist  n Predicted Measured SIBEC  0 16.1 ND NA  0 16.7 ND NA  0 19.0 ND 22.3  4 20.2+1.3 20.6 22.5  1 20.4+2.9 18.7 25.2  Wet  n Predicted Measured SIBEC  0 16.3 ND NA  0 17.0 ND NA  0 19.2 ND NA  1 20.4+1.6 20.4 NA  0 20.7 ND NA  2  1  N D - n o d a t a w e r e o b t a i n e d d u e to the a b s e n c e o r s p o r a d i c o c c u r r e n c e o f w e s t e r n l a r c h u n d e r s o m e edaphic conditions. 2  N A - not available  47  The small difference in value between M S E of the construction model and the calculated MSPR suggested the construction model is unbiased. The similar SEE values between the model developed from the construction data set and the final model indicates that the construction data set was sufficiently large so that the addition of data did not seem to improve the prediction ability of the final model.  The general trend of increasing site index with increasing ASMR and SNR, and the lack of a significant ASMR*SNR interaction on site index was established in Chapter 4. Considering this, the prediction model developed here may be used to predict the site index of western larch in some edatopes where no sampling occurred (Table 5.3). The lack of sampling within various combinations of A S M R and SNR likely reflects the natural distribution of western larch and a preference for particular sites. However, this does not mean that western larch does not, or could not, exist on sites which were not sampled, or that these sites do not occur in nature. Thus, having an estimate of western larch site index for such sites would be beneficial until such time as adequate sampling of those sites can occur. However, the extrapolated values must be used with due caution as these estimates go beyond the range of the data and the trends established in Chapter 4 are based on a limited series of edatopes.  The preferred method for model validation is through the collection of new, independent data (Bruce and Wensel 1987, Neter et al. 1996, Kayahara et al. 1998). However, this was not practical or feasible within this study. The cross-validation technique used here, withholding a portion of the original data set in order to test model predictive ability, is really an attempt to simulate the replication of the study (Neter et al 1996). Despite the short comings of this  48  technique, it does result in a model whose relative predictive ability is known. However, the model's usefulness can only be fully determined when tested against a reliable, independent data set.  A n effort was made to ensure that sampling occurred throughout the entire range of western larch in B . C . Within this range, the only subzones not sampled, that commonly have western larch growing in them, are two subzones of the E S S F zone ( E S S F w m , E S S F d k ) and the very small I C H x w subzone. Although western larch may be found in small numbers in other subzones on particular sites, the general population of western larch was sampled. Thus, the A S M R S N R model that was developed provides site index estimates that w i l l be applicable throughout most of the natural range of western larch in B . C .  In order to examine the usefulness of the A S M R S N R model, estimates for field application, the mean ±95% confidence interval and the ±95% prediction interval for the predicted site index value of each filled edatope were calculated. The results of mean confidence interval calculations (Table 5.3) suggest that predicted mean site index values provide an acceptable level of accuracy when estimating the mean site of western larch for a given area. The prediction interval (not shown) (i.e., the range of possible site indices accompanying a predicted site index for a single site at a confidence level of 95%) is so wide, generally ± 3 m, that there is likely little practical use for such predictions. A similar study, in which the confidence limits and prediction intervals were used to evaluate the practical usefulness of estimated site index values for western redcedar, showed comparable results (Kayahara et al. 1997).  A n independent data set of 182 plots was acquired from S I B E C . S I B E C is an acronym 49  for site index biogeoecosystem classification system. It is the title given to a current project undertaken by the B.C. Ministry of Forests who are correlating site index data for the major tree species in B.C. to site units of the B E C system. The assignment of a site index value to a site unit of the B E C system (in SIBEC's case to the site series level of the B E C system) is meant to provide practicing foresters with an easily attainable estimate of site index when height and age can not be used. The independent data set acquired from SIBEC was used by SJJBEC to produce site index values for western larch which were correlated to site units at the site series level. The data set contained combinations of ASMR, SNR, and the associated site index for western larch. Due to the variety of sources used by SIBEC to compile the data set, it was considered unreliable and so was not used to test the predictive ability of the A S M R SNR model. However, a comparison of mean site index values of the SIBEC data and predicted values from the A S M R SNR model for various edatopes was made (Table 5.3). The comparison indicated that the SIBEC data tends to underestimate the site index of western larch among the moist, nutrient medium to very rich edatopes while overestimating site index on very dry, nutrient poor through rich edatopes. Assuming the site index values generated in this study are reasonably accurate, the apparent bias in the SIBEC data set implies a similar bias will also exist in the SIBEC site index values currently used by forest practitioners for site index estimates of western larch at the site series level.  The confidence placed in the SIBEC estimates of site index, called a reliability rating, are applied by Forest Service regional ecologists (MOF 1997). The reliability of estimates of site index for western larch is generally rated low to medium among the subzones in which it occurs. The exception is the ICHmw and the IDFdm subzones where the rating is high. The pooling of 50  data complied for this study with that of the SJJBEC data set will help to improve the reliability of SJJBEC site index estimates in all but a few of the subzones occupied by western larch.  5.6 Conclusions Despite the limited representation of some ASMRs and SNRs, the large amount of variation in site index accounted for by the model indicates a strong relationship exists between western larch site index and estimates of soil moisture and soil nutrients.  The results of the cross-validation indicate that the ASMR SNR model is unbiased and has an acceptable level of precision when predicting the site index of western larch. Until such time as a reliable, independent data set is available, it is reasonable to assume that the site index of western larch can be accurately predicted throughout the majority of its range in B.C. using this model. The model may also be used to extrapolate site index values for western larch in some of the edatopes where no sampling occurred. However, extrapolated values must be used with caution.  For practical purposes, predicted mean site index values provide an acceptable degree of accuracy and level of confidence needed for estimating the mean site of western larch for a given area.  A simple comparison of predicted mean site index values generated here with SIBEC site index means, calls into question the accuracy of site index values currently used by forest practitioners for estimating western larch site index at the site series level.  51  6. C O N C L U S I O N S  This study expands the efforts of past research in using categorical measures of ecological site quality, as delineated within the working framework of the B E C system, to explain the variation in site index of major tree species in B.C.  Climate, represented by biogeoclimatic subzones, had a significant effect on site index of western larch; however, due to compensating effects between temperature and precipitation, the climatic effect on larch productivity was only detectable above the subzone or even zone level of generalization. The climatic growth optimum for western larch corresponded to the intermediate segment of a regional climatic gradient - wetter temperate climate - that is represented by the Dry Warm Interior Cedar - Hemlock subzone. In relation to edatopes, site index significantly increased from water-deficient to moist sites and decreased from moist to wet sites, and on water-deficient sites, it increased with increasing soil nutrient regime. On water-deficient sites, estimates of both actual soil moisture regime and soil nutrient regimes had both positive significant and consistent effects on site index, however, on non-water deficient sites, the effect of soil nutrient regime appeared to be marginal.  The model developed in this study, combined with the identification of A S M R and SNR, can be used to provide reliable site index predictions for western larch to a level of accuracy required for practical forest management throughout its range in B.C. The reliable prediction of western larch site index through the identification of ASMR and SNR, suggests that there is a strong correlation between ecological site classification and forest productivity. Testing the  52  model against a reliable, independent data set would enhance the confidence that can be placed in the predictive ability of the model.  The relationships developed here, between the B E C system and the site index of western larch, challenges the validity of some of the existing western larch site index values correlated to site series through the SIBEC program. At the same time, information obtained in this study can be used to improve those sites series relationships established through that program.  53  LITERATURE CITED  Braumandl, T.F. and M . Curran. (editors). 1992. A field guide for site identification and interpretation for the Nelson Forest Region. B . C . M i n . For. Land Manage. Handbook N o . 20.311pp. Brisco, D. 1999. Height growth and site index curves for western Larch in British Columbia. Unpublished manuscript. Bruce, D. and L . C . Wensel. 1987. Modelling forest growth: approaches, definitions, and problems. Presented at the J U F R O Forest Growth Modelling and Prediction Conference, Minneapolis, M n , August 24-28, 1987. Canadian Soil Survey Committee (CSSC). 1978. The Canadian system of soil classification. Can. Dept. Agric. Publ. N o . 1646. Supply and Serv. Canada, Ottawa. 164pp. Carlson, C . E . , J.W. Byler, J.E. Dewey. 1995. Western larch: pest tolerant conifer of the Northern Rocky Mountains. In W . C . 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Vancouver, B.C. 207 pp.  58  APPENDIX 1  Selected Characteristics of Study Stands  # 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35  Stand 9501 9502 9503 9504 9505 9506 9507 9508 9509 9510 9511 9512 9513 9514 9515 9516 9517 9518 9519 9520 9521 9522 9523 9524 9525 9526 9527 9701 9702 9703 9706 9707 9708 9709 9711  Zone Subzone Species B H A Lw IDF dm 69 dm Lw IDF 49 Lw 55 IDF dm Lw 56 IDF dm Lw IDF dm 60 dm Lw 61 IDF Lw IDF dm 43 Lw 55 IDF dm L w dm 70 IDF Lw IDF dm 53 dm Lw 56 IDF 54 IDF dm Lw Lw IDF dm 56 Lw 57 IDF dm Lw IDF dm 58 Lw dm 99 IDF Lw IDF dm 101 dm Lw 93 IDF dk Lw 75 MS dk Lw 72 MS Lw 72 dk MS Lw 65 dk MS dk Lw 72 MS Lw dk 56 MS dk L w 93 MS Lw dk 59 MS dk Lw 41 MS mw Lw 101 IDF Lw IDF mw 96 Lw IDF mw 97 Lw 56 ICH mk Lw ICH mk 91 mw Lw 63 ICH dw Lw 120 ICH Lw 73 ICH mw  Height 22.20 20.90 17.60 18.00 19.90 21.90 16.40 24.40 28.40 20.00 21.60 24.30 19.60 20.30 25.80 23.30 26.30 26.90 27.80 25.70 28.00 27.10 32.50 22.00 25.70 20.50 13.80 32.81 33.40 42.11 24.93 28.12 17.33 36.95 26.60  ASMR SI 19.20 M D MD 21.09 16.87 MD MD 17.11 MD 18.34 20.02 MD 17.54 M D 23.36 M D 24.36 SD 19.48 MD 20.52 MD 23.46 M D MD 18.63 19.14 M D 24.11 SD 17.14 VD 19.13 MD 20.30 M D SD 23.11 SD 21.78 SD 23.71 24.04 SD 27.50 M SD 20.90 19.41 MD 19.03 SD 15.05 VD 24.04 SD 24.78 SD SD 31.01 SD 23.68 21.42 SD 15.64 M D 24.73 SD SD 22.39  SNR  Elev.  M M P P M M R R R M M R •M M R P P M M P M M R P P M R M M R M M P M M  N 875 Flat 870 Flat 880 N 900 N 885 Flat 880 Rdge 925 920 E E 975 1000 Flat/Rdg N 995 N 985 960 Flat R 965 960 Gully 1060 E N 1045 1110 Flat N 1115 N 1120 1110 N Rdge 1115 Gully 1100 1150 E Flat 1120 W 1140 W 1125 470 Flat Flat 460 Flat 452 N 825 W 1215 N 1080 970 N W 1125  Aspect  59  # 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70  Stand Zone Subzone Species B H A Lw 9712 I C H mw 50 dk Lw 47 9713 MS 9714 dk Lw 55 MS Lw dk 51 9715 MS dk Lw 56 9716 MS Lw 56 9717 MS dk mk Lw 71 9718 ICH Lw mk 48 9719 I C H dk Lw 57 9720 MS dk Lw 53 9721 MS dk Lw 53 9722 MS Lw MS dk 97 9723 mw Lw 87 9732 I C H ICH mw Lw 109 9735 mw Lw 76 9736 I C H Lw mw 151 9739 I C H Lw 9741 ICH mw 47 mw Lw 46 9742 I C H mw Lw 47 9743 ICH mw Lw 45 9744 I C H Lw ICH mw 45 9745 Lw dk 65 9746 MS Lw MS dk 87 9747 Lw mk 69 9749 I C H Lw mk 59 9750 I C H Lw 54 ICH mk 9751 Lw 9752 IDF dm 57 Lw 82 97071 I C H mk Lw 90 97072 I C H mk mk Lw 89 97073 I C H xh Lw 52 BA01 IDF Lw 53 B A 0 2 IDF xh Lw xh 48 B A 0 4 IDF Lw 54 xh B A 0 5 IDF xh Lw 49 B A 0 7 IDF  Height 21.86 21.95 26.00 17.20 21.13 16.63 26.83 21.40 22.42 25.23 22.18 28.45 32.43 25.67 27.70 23.40 23.62 17.28 24.83 18.15 13.05 22.72 27.73 22.63 16.40 25.50 26.00 26.87 31.68 26.85 17.30 24.00 12.90 27.60 14.20  SI ASMR 21.86 SD SD 22.58 SD 24.89 17.05 VD MD 20.08 15.82 M D F 22.88 SD 21.80 SD 21.13 SD 24.57 MD 21.61 MD 21.05 SD 25.17 18.05 SD SD 22.89 14.34 SD F 24.29 17.94 VM 25.54 SD 19.03 SD 13.66 VD SD 20.18 21.56 SD SD 19.57 15.24 MD 24.62 SD MD 24.49 SD 21.46 24.21 SD SD 20.67 17.00 M D SD 23.37 VD 13.01 26.64 M 14.33 VD  SNR M M M P P P R M M R P M M M M P M R M P M P M M M R M M M M P R P VR M  Elev. 1145 1095 1195 1200 1190 1240 940 1140 1035 1140 1140 1450 1100 1515 1400 1100 1100 1100 1070 1080 1080 1170 1155 1050 1280 945 1000 1280 1330 1410 1070 1090 1120 980 1030  Aspect W S N N W W Flat Flat N S S E S S S S Flat Flat Flat W W E Flat N S N E W W S  w w N  w N  60  # 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105  Stand Zone Subzone Species B H A xh Lw B A 1 0 IDF 54 BA11 IDF xh Lw 49 xh Lw B A 1 2 IDF 57 B A 1 3 IDF xh Lw 51 B A M IDF xh Lw 53 xh Lw 52 B A 1 5 IDF xh Lw B A 1 6 IDF 116 dm Lw B A 1 7 IDF 55 dm Lw B A 1 8 IDF 55 dm Lw B A 1 9 IDF 51 B A 2 0 IDF dm Lw 55 Lw BA21 IDF dm 53 B A 2 2 IDF dm Lw 56 dm Lw 54 BA23 MS BA24 MS dm Lw 59 BA25 MS dm Lw 50 dm Lw BA26 MS 53 dm Lw BA27 MS 46 Lw BA28 MS dm 40 xh Lw B A 2 9 IDF 53 Lw B A 3 0 IDF xh 57 B A 0 6 IDF xh Lw 56 xh Lw 54 B A 0 9 IDF xh Lw KaOl IDF 49 Lw Ka06 I C H mw 62 mw Lw Ka07 I C H 71 mw Lw Ka08 I C H 58 mw L w I C H 78 Ka09 Lw KalO ICH mw 118 mw Lw Kail ICH 54 mw Lw Kal2 ICH 67 Lw ICH mw 55 Kal3 mw Lw Kal35 ICH 115 mw Lw 112 Kal36 ICH Lw mw 119 Kal37 ICH  Height 17.20 19.50 19.30 27.10 22.80 11.10 14.80 27.10 24.60 23.40 24.50 21.20 24.70 27.10 26.20 20.20 19.00 14.60 20.20 22.30 15.50 23.60 22.70 20.20 27.60 32.00 25.10 28.20 31.70 25.80 24.60 28.40 24.30 33.60 34.00  ASMR SI 16.62 M D 19.68 M D 18.20 M D 26.61 M 22.21 SD V D 10.91 10.31 ED 25.95 F 23.56 SD 23.19 F SD 23.46 SD 20.65 SD 23.46 F 26.16 24.30 SD SD 20.20 18.51 MD VD 15.15 22.35 F 21.72 M D 14.63 VD 22.42 SD 21.92 M D MD 20.39 25.02 F F 27.25 23.47 SD SD 23.03 21.44 SD 24.34 F 21.54 W F 27.19 16.72 VD 23.24 SD SD 22.88  SNR P M P VR M VP VP VR R R R R R VR M P P M R M M M M M M R M P P M R R VP M M  Elev. 1160 1175 1150 1120 1130 1135 1125 1200 1200 1230 1230 1240 1240 1330 1330 1350 1370 1420 1420 1135 1140 990 1100 1250 760 760 830 780 945 1015 1010 1015 920 915 910  Aspect N N N N W E N Flat Flat Flat W W S W W W N W W Flat E N S S Flat Flat S Flat W Rdge Flat N W  s  N  61  # 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140  Stand Zone Subzone Species B H A mw Lw 78 Kal38 ICH mw Lw Kal4 ICH 71 mw Lw 93 Kal40 ICH mw Lw Kal41 ICH 92 mw Lw Kal42 ICH 90 mw Lw Kal44 ICH 85 ICH mw Lw 87 Kal5 mw Lw 96 Kal6 ICH ICH mw Lw 117 Kal7 ICH mw Lw 116 Kal9 mw Lw Ka20 I C H 116 Lw Ka21 I C H mw 63 mw Lw 73 Ka22 I C H mw Lw 71 Ka23 I C H mw Lw 71 Ka24 I C H mw Lw 82 Ka245 I C H mw Lw 67 Ka25 IDF mw Lw IDF 56 Ka26 mw Lw 60 Ka27 IDF mw Lw Ka28 IDF 58 IDF mw Lw 60 Ka29 Lw mw 81 Ka30 IDF mw Lw 78 Ka31 I D F mw Lw 65 Ka32 I D F mw Lw Ka33 I C H 67 mw Lw 64 Ka34 I C H xh Lw 56 KE01 IDF xh Lw 62 K E 0 2 IDF KE03 IDF xh Lw 65 L w 54 K E 0 4 IDF xh xh Lw 46 KE05 IDF Lw xh 50 KE06 IDF KE07 IDF xh Lw 54 xh Lw 59 KE08 IDF dm Lw 116 K E 0 9 IDF  Height 26.30 21.40 33.60 35.30 34.20 32.70 27.50 26.30 33.40 27.60 31.76 24.70 24.10 25.40 27.70 22.60 29.30 25.70 17.50 18.20 29.40 25.70 29.50 28.90 28.10 27.50 20.20 26.80 15.80 23.20 22.90 17.90 19.10 20.90 32.80  ASMR SI 21.50 SD SD 18.30 25.28 F F 26.68 26.12 F 25.64 F 24.35 SD SD 19.57 F 22.65 18.86 M D 21.64 SD 22.24 SD 20.31 SD SD 21.66 23.61 SD 18.09 M D 25.63 SD 24.41 SD 16.14 VD 17.03 M D 27.04 M 20.65 M D SD 24.08 25.63 F SD 24.58 F 24.57 19.20 V M 24.30 SD VD 14.08 SD 22.40 23.78 SD 17.90 M D 18.45 M D 19.40 M D 22.34 M D  SNR P P M M M M P P R P M P P P M P R R M R R M R M M M VR R P M R P P M M  Elev. 750 1120 780 760 760 755 1120 960 970 995 1015 665 660 660 665 710 430 410 400 400 395 420 500 660 705 695 1120 1130 1175 1170 1175 1210 1205 1220 720  Aspect Flat Rdge S Flat Flat Flat E E E E E W W W W W N N Rdge Flat N Flat S S E E E W W S  w w N  w Flat  62  # 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175  Stand KE10 KE11 KE12 KE13 KE14 KE15 KE16 KE17 KE18 KE19 KE20 KE21 KE22 KE23 KE24 KE25 KE26 KE27 KE28 KE29 KE30 KE31 KE32 KE33 KE34 KE35 KE36 KE37 KE38 KE39 KE40 NeOl Ne02 Ne03 Ne05  Zone Subzone Species B H A IDF dm Lw 108 Lw IDF dm 114 Lw IDF dm 113 Lw IDF dm 53 IDF dm Lw 57 IDF dm Lw 58 Lw IDF dm 63 TDF dm Lw 54 Lw IDF dm 49 Lw MS dm 55 dm Lw MS 53 dm Lw MS 56 dm Lw 45 MS dm Lw 45 MS dm Lw MS 53 dm Lw MS 51 Lw MS dm 53 dm Lw 52 MS Lw MS dm 53 dm Lw 53 MS dm Lw MS 50 dm Lw MS 49 dm Lw MS 49 Lw MS dm 52 dm Lw 54 MS dm Lw 58 MS Lw MS dm 50 dm Lw 51 MS dm Lw MS 58 dm Lw MS 55 MS dm Lw 53 dm Lw IDF 86 IDF dm Lw 87 IDF dm Lw 94 ICH mk Lw 98  Height 29.70 36.50 33.50 22.50 17.70 21.30 15.00 23.10 17.80 25.90 27.60 28.00 12.50 12.30 25.20 23.60 20.40 20.60 21.40 20.70 22.30 22.50 16.10 24.10 20.60 22.00 14.10 19.90 24.10 20.80 22.70 23.30 26.30 28.00 27.70  SI ASMR MD 20.93 25.01 SD 23.08 MD 21.92 M D 16.70 M D 19.92 M D 13.56 VD 22.31 SD 17.96 M D 24.80 SD 26.87 M F 26.58 VD 13.08 VD 12.87 24.54 F F 23.39 19.87 M D 20.24 M D 20.84 SD 20.16 SD SD 22.30 22.70 SD 16.24 M D 23.68 SD SD 19.89 20.57 SD 14.10 VD 19.73 SD SD 22.53 19.93 SD 22.11 SD 18.25 M D 20.46 M D 21.02 M D 20.42 M D  SNR P R M M P M P M P M VR VR P VP VR R M M P P R M P M P P M P M P R P M M M  Elev. 820 840 920 1025 1050 1040 1070 1050 1035 1100 1140 1140 1220 1205 1220 1200 1130 1130 1130 1135 1200 1200 1255 1230 1180 1215 1165 1165 1155 1100 1170 860 850 850 1360  Aspect S E E S  s s w s w E E E  s w E E Flat E E N E E E E E  s S N E E E N N N N  _  63  # 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210  Stand Zone Subzone Species B H A mk Lw Ne06 ICH 69 mk Lw Ne07 ICH 72 mk Lw Ne08 ICH 68 ICH mk Lw Ne09 73 mk Lw 72 NelO ICH dm Lw Nei 08 IDF 91 dm Lw Nei 09 IDF 99 ICH mk Lw Nell 80 dm Lw 74 Nei 10 IDF N e i l l IDF dm Lw 79 Nei 12 ICH mw Lw 137 mw Lw 134 Nei 13 ICH dm Lw Nei 14 IDF 79 dm Lw 72 N e l l 5 IDF dm Lw 82 Nei 16 IDF Lw Nei 17 IDF dm 93 dk Lw Nei 18 MS 116 dk Lw Nei 19 MS 58 mk Lw 72 Nel2 ICH Nel21 MS dk Lw 67 Nei 22 MS dk Lw 69 Lw Nei 23 MS dk 71 Lw Nei 23 MS dk 71 Nei 24 MS dk Lw 102 dk Lw 94 Nei 25 MS dk Lw Nei 26 MS 118 dk Lw 75 Nei 27 MS Nei 28 MS dk Lw 100 dk Lw Nei 29 MS 103 Lw Nel3 ICH mk 75 dk Lw 101 Nei 30 MS Lw dk 78 Nel31 MS dk Lw Nei 32 MS 91 dk Lw 121 Nel33 MS dk Lw Nei 34 MS 73  Height 27.00 27.90 18.80 24.90 26.20 30.20 22.70 29.20 20.60 20.90 34.50 23.50 20.90 22.10 19.20 23.40 21.40 25.10 31.60 23.30 21.30 24.10 25.20 25.20 28.00 31.80 24.30 23.20 29.20 20.70 31.90 29.70 24.90 27.90 21.70  SI ASMR 23.32 SD 23.63 SD 16.40 VD 20.98 M D SD 22.20 22.98 M D 16.71 VD 23.56 V M 17.28 M D 17.03 M D SD 21.78 15.12 VD 17.03 M D SD 18.75 15.41 VD 17.70 M D VD 14.71 SD 23.47 26.74 F 20.42 SD 18.43 M D 20.56 SD 21.49 M D 18.27 M D 21.02 SD 21.50 SD 20.23 M D 17.00 V D 21.02 SD 17.26 M D 23.13 SD 24.24 SD 19.00 M D 18.70 M D 18.31 M D  SNR M M P M P M P R P P P VP P P VP P VP M R P P P M P P P M P P P M R P P P  Elev.  Aspect  1330 1330 1295 1275 1290 960 970 1285 960 950 1310 1410 1100 1100 1110 1090 1135 1200 1275 1200 1280 1300 1300 1295 1285 1270 1275 1255 1220 1285 1240 1115 1375 1445 1465  S S E N E Flat Flat E Rdge Flat N W E E E E N Flat E W W Rdge W Flat E E Flat E E S E Gully E S E  64  # 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245  Stand Nel4 Nel5 Nel6 Nel7 Nel8 Nei 9 Ne20 Ne21 Ne22 Ne23 Ne24 Ne25 Ne26 Ne27 Ne28 Ne29 Ne30 Ne31 Ne32 Ne33 Ne34 Ne35 Ne36 Ne37 Ne38 Ne39 Ne40 Ne41 Ne42 Ne43 Ne44 Ne45 Ne46 Ne47 Ne48  Zone Subzone Species B H A ICH mk Lw 67 ICH mk Lw 81 ICH mk Lw 86 mk Lw ICH 78 Lw ICH mk 86 mw Lw 84 ICH ICH mw Lw 90 mw Lw ICH 89 ICH mw Lw 81 mw Lw ICH 86 mw Lw ICH 88 mw ICH Lw 88 mw Lw ICH 89 mw Lw ICH 90 mw Lw ICH 85 mw L w ICH 87 mw Lw ICH 81 mw ICH Lw 77 ICH mw Lw 82 ICH mw Lw 85 mw Lw ICH 87 ICH dw Lw 116 ICH dw Lw 93 dw Lw ICH 106 ICH dm Lw 93 Lw ICH dm 84 mw Lw ICH 83 mw Lw ICH 101 mw Lw 62 ICH mw Lw ICH 58 mw Lw ICH 52 mw Lw ICH 62 Lw ICH mw 60 mw Lw ICH 56 mw Lw ICH 53  Height 16.60 26.30 24.00 29.10 26.10 27.80 28.10 22.60 26.60 29.30 30.90 27.90 27.40 32.10 24.20 28.80 29.40 26.50 25.40 30.60 33.60 35.00 31.10 37.00 34.30 35.10 31.40 35.00 30.20 28.90 20.20 28.10 24.40 24.30 23.80  ASMR SI VD 14.59 21.13 SD 18.79 M D SD 23.76 20.42 MD SD 21.96 21.51 SD VD 17.45 21.37 SD SD 22.89 23.87 M D 21.58 SD SD 21.09 24.52 SD 19.05 MD 22.38 SD SD 23.59 21.78 MD SD 20.30 SD 24.01 26.06 F SD 23.81 SD 23.43 F 26.20 F 25.81 27.66 F 25.04 F F 25.36 27.36 F . 27.00 SD SD 19.84 SD 25.47 SD 22.46 SD 23.08 23.18 SD  SNR P P P R M P P M P M R P P M P P P M P M M R P M M R M M M R P R M M M  Elev. Aspect 1285 Flat/Rdg 1135 E E 1155 1035 E/Flat E 1035 1130 E 1120 Deprssn N 1150 E 1150 E 1140 E 1150 1000 E 1200 W 1190 W 1220 Rdge W 1220 1300 S Rdge 1320 W 1330 W 1325 E 1320 Flat 595 W 865 W 860 S 650 Rdge 650 W 820 W 880 S 920 950 S 950 s S/Rdge 940 E 590 610 Flat E 600  65  # 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280  Stand Ne49 Ne50 Ne52 Ne53 Ne54 Ne55 Ne56 Ne57 Ne58 Ne59 Ne60 Ne61 Ne62 Ne63 Ne64 Ne65 Ne66 Ne67 Ne68 Ne69 Ne70 Ne71 Ne72 Ne73 Ne74 Ne75 Ne76 Ne77 Ne78 Ne79 Ne80 Ne81 Ne82 Ne83 Ne84  Zone Subzone Species B H A ICH mw Lw 55 mw Lw ICH 59 dw Lw ICH 97 ICH mw Lw 87 mw Lw 82 ICH Lw ICH mw 84 dw Lw 62 ICH dw Lw ICH 66 Lw 92 ICH dw dw Lw 93 ICH ICH mw Lw 103 mw Lw ICH 95 Lw ICH mw 94 mw Lw ICH 100 dw Lw ICH 71 dw Lw 55 ICH ICH dw Lw 58 dw Lw 63 ICH dw Lw 63 ICH Lw ICH dw 80 dw Lw 85 ICH dw Lw 87 ICH Lw ICH dw 60 dw Lw 63 ICH dw Lw ICH 55 mw Lw ICH 80 mw Lw 52 ICH Lw ICH mw 89 mw Lw ICH 89 mw Lw ICH 88 mw Lw 108 ICH mw Lw 107 ICH Lw 72 ICH mw mw Lw 70 ICH mw L w 71 ICH  Height 20.90 25.50 35.50 35.20 26.70 28.80 23.30 20.80 37.30 29.50 35.10 34.40 28.40 34.10 30.30 27.10 29.50 27.20 25.40 28.70 37.90 33.60 23.90 27.40 24.20 28.20 17.80 24.00 23.30 23.70 30.20 26.80 25.10 19.70 21.20  SI ASMR 20.02 SD SD 23.65 F 26.19 SD 27.29 MD 21.33 22.73 SD 21.14 MD 18.36 VD 28.17 M 22.23 M D F 25.20 25.63 F 21.32 SD 24.82 F 25.81 SD 25.95 SD F 27.56 SD 24.50 22.87 M D 23.17 MD 29.68 M 26.06 F 22.00 SD SD 24.66 23.17 VM 22.66 M D 17.49 M D 18.50 M D MD 17.98 18.37 MD VM 21.27 SD 19.00 20.76 SD VD 16.95 18.13 MD  SNR P M R R M P M R M M M M P M R R VR M R M VR M P R R M P P P P R P P M P  Elev. 610 620 660 835 1045 1055 905 935 1050 1090 1115 1225 1245 1250 700 720 720 740 750 810 880 880 960 970 960 1090 1100 1090 1180 1260 1140 1145 1120 1080 1075  Aspect E E N S Rdge/W E S S Gully S S  w S S Flat Flat Flat Flat W Flat Deprssn N N N N N N N W W N N N R S  66  # 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315  Stand Ne85 Ne87 Ne88 Ne89 Ne90 Ne91 Ne92 Ne93 Ne94 Ne95 Ne96 Ne97 OK01 OK02 OK03 OK04 OK05 OK06 OK07 OK08 OK10 OK11 OK12 OK13 OK14 OK14n OK15 OK16 OK17 OKI 8 OK19 OK20 OK21 OK22 OK23  Zone Subzone Species B H A ICH mk Lw 77 Lw 92 ICH mk mk Lw ICH 70 Lw ICH mk 69 Lw ICH mk 60 ICH mk Lw 74 Lw ICH mk 57 Lw ICH mk 56 mk Lw ICH 65 ICH mk Lw 56 Lw ICH mk 59 mk Lw ICH 56 IDF dm Lw 84 IDF dm Lw 88 IDF dm Lw 86 Lw IDF dm 86 dm Lw IDF 88 Lw 82 IDF dm IDF xh Lw 35 dm Lw IDF 53 dm Lw 50 MS dm L w MS 55 dm Lw 53 MS dm Lw 52 MS dm Lw 102 MS dm Lw 108 MS Lw MS dm 50 dm Lw 82 MS dm Lw MS 79 Lw MS dm 69 xh Lw 53 IDF xh Lw IDF 39 xh Lw 57 IDF Lw IDF dm 81 IDF xh Lw 78  Height 27.50 9.00 12.40 18.10 25.80 25.90 23.50 22.20 21.50 23.60 24.00 19.50 24.10 26.70 32.30 28.70 30.00 23.90 20.70 22.10 17.70 24.40 22.30 19.10 31.10 26.30 19.10 31.80 29.50 29.20 20.80 14.00 18.60 29.20 17.10  SI ASMR SD 22.59 ED 7.03 ED 10.70 VD 15.69 23.75 SD 21.67 SD SD 22.14 SD 21.09 19.10 M D 22.42 SD 22,52 SD 18.54 SD 19.07 M D 20.66 M D 25.18 SD 22.42 M D SD 23.18 19.12 M D 24.33 M 21.53 M D 17.70 M D F 23.36 21.72 SD 18.76 M D 22.47 MD 18.57 M D SD 19.10 SD 25.36 SD 23.94 SD 25.20 20.26 M D 15.62 VD 17.54 M D 23.43 M D VD 14.05  SNR P VP VP P M P P P P M P P P M R M M P VR M P R M P M P P M M M M P P M P  Elev. 960 1000 980 970 990 1050 1130 1190 1240 1310 1370 1470 1390 1380 1380 1360 1360 1390 1170 1540 1470 1430 1450 1530 1585 1580 1520 1460 1590 1590 950 1120 1160 1390 800  Aspect Flat R N N W E E W N W E N N N N W W N W N W W N S  w w S N N N N W N N N  67  APPENDIX 2 The Key to Identification of Relative Soil Moisture Regimes (after Greene et al. 1994) This key is designed to assist in identifying relative soil moisture regimes using observable edaphic feature during site assessment (diagnosis). Attempt always to check the results against plant indicators.  Explanation of the Key Ridge crest: distinctly shaped height of land; usually with a convex slope shape. Upper slope: the convex-shaped, upper (water-shedding) portion of a mesoslope. Middle slope: the portion between the upper and lower portion of a mesoslope; the slope shape is usually straight. Lower slope: the concave-shaped, lower (water-receiving) portion of a mesoslope. It includes toe slopes which are nearly level areas directly below and adjacent to the lower slope. Flat: any level area excluding toe slopes; the surface shape is horizontal with no significant aspect Depression: any area that is concave-shaped (water-collecting); usually in a flat or subdued topography. Soil depth (= potential rooting depth): depth from the ground surface to a root restricting layer such as bedrock' strongly compacted or strongly cemented materials; or permanent, stagnant water table. Particle size coarse: sandy (sandy or loamy sand) with >35% coarse fragment content by volume, or loamy (sandy loam, loam, or sandy clay loam) with >70% coarse fragment volume. Particle size fine: silty (silt loam or silt) or clayey (silty clay loam, clay loam, sandy clay, silty clay, or clay) with <35% coarse fragment volume. Floodplain: post-glacial alluvial deposits bordering rivers and streams, still under the influence of periodic flooding. Gleyed layer or mottles: one or more soil horizons >10cm thick that have developed under poor drainage, waterlogging, and permanent or periodic reduction of iron and other elements. Typically, they feature mottles- many distinct and prominent, orange to red spots or blotches interspersed in a predominantly dull yellow, gray, blue, or olive coloured soil matrix.  68  Appendix 2 (continued) Key to Identification of Relative Soil Moisture Regimes l a ridge crest or upper slope lb. other slope positions 2a soil depth <40cm 2b soil depth >40cm 3a exposed bed > 50% 3b exposed bedrock <50% 4a particle size coarse and forest floor <20cm 4b particle size fine or forest floor >20cm 4c other soils 5a particle size coarse and forest floor <20cm 5b other soils  2 6 3 5 0 4 1 2-3 1-2 2 2-3  6a middle slopes" 6b other slope positions 7a water table seepage, or mottles present 7b water table seepage, or mottles absent 8a water table seepage, or mottles > 60 cm deep 8b water table seepage, or mottles< 60 cm deep 9a soil depth <40cm 9b soil depth >40cm 10a particle size coarse and forest floor <20cm 10b particle size fine and forest floor >20cm 10c other soils I la particle size coarse and forest floor <20cm II b particle size fine 1 lc other soils  7 12 8 9 5 6 10 11 2 4 2-3 2 5 3-4  3  12a lower slopes 12b other slope positions 13a water table seepage, or mottles present 13b water table seepage, or mottles absent 14a water table or seepage<30 cm deep 14b water table seepage >30 cm deep 15a particle size coarse and forest floor <20cm 15b particle size fine and forest floor >20cm 16a water table seepage, or mottles >60cm deep 16b particle size coarse and forest floor <60cm deep  13 17 14 5 15 16 6 7 5 6  69  Appendix 2 (continued) Key to Identification of Relative Soil Moisture Regimes 17a flat ( s l o p e < 5 % ) 17b. depression  18  --2S  18a f l o o d p l a i n  •  18b o t h e r s o i l s  19 22  19a w a t e r table o r mottles present  20  19b w a t e r table o r mottles absent  21  2 0 a w a t e r table o r mottles < 3 0 c m d e e p  7  2 0 b w a t e r table o r mottles > 6 0 c m d e e p  5  2 0 c other s o i l s  6  2 1 a particle size coarse  3-4  21b other soils  5  2 2 a particle size fine  23  22b other soils  25  2 3 a w a t e r table o r mottles present and soil depth >60 c m  5  2 3 b other soils  24  2 4 a water table o r m o t t l e s < 2 0 c m d e e p  7  2 4 b water table o r mottles >35 c m d e e p  5  2 4 c other s o i l s  6  C  C  C  2 5 a w a t e r table o r mottles present  26  2 5 b w a t e r table o r m o t t l e s absent  27  2 6 a w a t e r table o r mottles < 3 0 c m d e e p  7  2 6 b water table or mottles >60 c m deep  5  2 6 c other s o i l s  6  2 7 a particle size coarse  2-3  2 7 b other s o i l s  4  28a mineral soil  29  2 8 b other soils  32  2 9 a p a r t i c l e size f i n e 29b other soils  30 ."  7  3 0 a w a t e r table o r mottles p r e s e n t 3 0 b water table o r mottles absent  32 31 5  3 1 a water table o r mottles < 2 0 c m d e e p  7  3 1 b water table o r mottles > 2 0 c m d e e p  6  C  C  3 2 a w a t e r table < 3 0 c m d e e p  7  3 2 b w a t e r table > 6 0 c m d e e p  5  3 2 c other s o i l s  6  " C o n s i d e r a l o w e r r a n k i n g f o r steep s l o p e g r a d i e n t s a n d w a r m - a s p e c t s l o p e s . b  A t t a c h s u f f i x 1, m, o r h f o r f l o o d p l a i n b e n c h h e i g h t : 1 ( l o w b e n c h ) , m ( m i d d l e b e n c h ) , h ( h i g h b e n c h ) , e.g. 6 m .  ° A t t a c h s u f f i x f f o r s t r o n g l y f l u c t u a t i n g water table, e.g., 5f. T h e s o i l a e r a t i o n r e g i m e o f sites w i t h a s t r o n g l y f l u c t u a t i n g w a t e r table is a l w a y s restricted o r d e f i c i e n t . 70  APPENDIX 3 Key to Identification of Soil Nutrient Regimes (after Greene et al. 1994). This key is designed to assist in identifying soil nutrient regimes using observable edaphic features during site assessment (diagnosis). Attempt always to check the results against plant indicators.  Explanation of the Key Wet soil: soil that has the growing-season water table within between 0 and <30 cm of the ground surface. Forest floor: all organic materials (L, F, and H horizons) on the mineral soil surface. Organic materials friable: well decomposed organic materials that dry out sufficiently during the growing season that they will have a crumbly consistency. Mor: humus form composed of L, F, and H horizons; the Fm horizon is matted and contains abundant fungal mycelia. Particle size coarse: sandy (sandy or loamy sand) with >35% coarse fragment content by volume, or loamy (sandy loam, loam, or sandy clay loam) with >70% coarse fragment volume. Soil dark coloured: soil that has high organic matter content, indicated by dark, chocolatebrown colours (Munsell notation value for moist colours<4). Soil light-coloured: soil that has a very low organic matter content, indicated by very pale colours(Munsell notation of value for moist colours>6). Soil depth (= potential rooting depth): depth from the ground surface to a root restricting layer such as bedrock; strongly compacted or strongly cemented material; or permanent, stagnant water table. Soil colluvial: soil derived from colluvial parent materials.  71  A p p e n d i x 3 (continued) T h e key to the identification of soil nutrient regimes (SNRs) Symbols for S N R s are: V P - very poor, P - poor, M - medium, R - rich, and V R - very rich.  la soil wet  2  lb. soil not wet 2a forest floor >20cm 2b forest floor <20cm 3a materials poorly decomposed 3b materials not poorly decomposed 4a materials well decomposed 4b materials not well decomposed 5a materials friable 5b materials not friable 6a Mor humus form 6b Other humus forms than Mor 7a Ae horizon>2cm or particle size coarse 7b Ae horizon<2cm or particle size not coarse 8a soil dark coloured or Ah horizon >5cm 8b soil not dark coloured or Ah horizon <5cm  9a soil depth <30cm 9b soil depth >30cm 10a Mor humus form 10b Other humus forms than Mor 1 la soil light-coloured 1 lb soil not light-coloured 12a soil dark coloured or Ah horizon >5cm 12b soil not dark coloured or Ah horizon <5cm 13a Mor humus form or Ae horizon >2cm 13b Other humus forms than Mor Ae horizon <2cm 14a particle size coarse 14b particle size not coarse 15a soil light-coloured 15b soil not light-coloured 16a soil colluvial or dark-coloured 16b soil not colluvial or dark-coloured 17a soil light-coloured 17b soil not light-coloured 18a seepage present 18b seepage not present 19a soil dark coloured or Ah horizon >5cm 19b soil not dark coloured or Ah horizon <5cm 20a particle size coarse 20b particle size not coarse 21a soil light-coloured and particle size coarse 21b soil not light-coloured and particle size not coarse  9 .....3 6 VP 4 5 P-M VR R 7 8 VP P R-VR M  10 13 11 12 VP P-M R M 14 19 15 17 VP 16 R P-M P 18 R M 20 21 R VR M R  72  APPENDIX 4  Tentative classification of actual soil moisture regimes (ASMRs) based on annual water balance and the depth of the growing-season groundwater table (from Klinka et al. 1998).  Characteristic  ASMR  la. Rooting-zone groundwater absent during the growing season 2a. Water deficit occurs (soil-stored reserve water is used and drought begins if current precipitation is insufficient for plant needs) 3a. Deficit >7 months or A E T / P E T <0.30 extremely dry (XD) 3b. Deficit >5 but <7 months or AET/PET <0.55 but >0.30 excessively dry (ED) 3c. Deficit >3 but <5 months or AET/PET <0.75 but >0.55 very dry (VD) 3d. Deficit > 1.5 but <3 months or AET/PET <0.90 but >0.75... moderately dry (MD) 3e. Deficit >0 but <1.5 month or AET/PET >0.90 slightly dry (SD) 2b. No water deficit occurs 4a. Utilization (and recharge) occurs (current need for water exceeds supply and soil-stored water is used) fresh (F) 4a. No utilization occurs (current need for water does not exceed supply) moist (M) lb. Rooting-zone groundwater present during the growing season 5a. Groundwater table >60 cm deep moist (M) 5b. Groundwater table >30 but <60 cm deep very moist (VM) 5c. Groundwater table >0 but <30 cm deep wet (W) 5d. Groundwater table at or above the ground surface very wet (VW) 1  AET/PET — actual evapotranspiration/potential evapotranspiration ratio.  73  APPENDIX 5 M e a n values of soil properties used to characterize soil nutrient regimes of B r i t i s h C o l u m b i a ' s soils (from K l i n k a et al. 1998).  Very poor (VP)  Property  Forest floor p H Forest floor C / N ratio  3.8  1  Soil Soil Soil Soil  Soil nutrient regime Medium Rich Poor (M) (P) (R)  min-N min-N min-N min-N  (kg/ha) (kg/ha) (kg/ha) (kg/ha)  Mineral soil CWH Mineral soil CWH Mineral soil CWH Mineral soil CWH Mineral soil Mineral soil  1  ?3_  in drier C W H in drier C W H in S B P S and S B S in S B S  <10  2  3  4  ISIIllliilS  5  m i n - N (mg/kg) in drier  ND  Very rich (VR)  4.0 42  4.1  4.5 20  5.0 21  18 13 10 29  54 25 30 43  113 47 38 hO  242  4.0  14  32  58  31  50  176 no 111  2  10  min-N (mg/kg) in drier  6  23  m i n - N (mg/kg) in wetter  34  29  70  ND  41  X5  172  322  5~  17  47  181  7  min-N (mg/kg) in wetter  8  min-N (mg/kg) in S B S min-N (mg/kg) in E S S F 9  9  ~  T 3 1  S'Sllllilljl  N D — not determined. 'Courtin et al. (1988). Kabzems and K l i n k a (1987). Carterand K l i n k a (1990) Wang(1992). W a n g (1993) K l i n k a and Carter (1990). Kayahara(1992). V a r g a and K l i n k a (unpublished manus.) K l i n k a etal. (1994). K l i n k a et al. (1998). 2  3  4  5  6  7  8  9  10  74  

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