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Estimates of above-ground biomass, net primary production and energy flows in 8 to 10 year old red alder… Smith, Nicholas John 1977

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ESTIMATES OF ABOVE-GROUND BIOMASS, NET PRIMARY PRODUCTION AND ENERGY FLOWS IN 8 TO 10 YEAR-OLD RED ALDER (Alnua rubra Bong.) ECOSYSTEMS BY NICHOLAS JOHN SMITH B.Sc.For.(Hons.)(Wales), 1975 A THESIS SUBMITTED IN PARTIAL FULFILMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF FORESTRY i n THE FACULTY OF GRADUATE STUDIES (FACULTY OF FORESTRY) We accept t h i s thesis as conforming to the required standards THE UNIVERSITY OF BRITISH COLUMBIA AUGUST, 1977 © Nicholas John Smith, 1977 In presenting th i s thes is in pa r t i a l fu l f i lment of the requirements f o r an advanced degree at the Univers i ty of B r i t i s h Columbia, I agree that the L ibrary shal l make it f ree ly ava i l ab le for r e f e r e n c e and study. I further agree that permission for extensive copying of th is thesis for scho lar ly purposes may be granted by the Head o f my Department o r by his representat ives. It is understood that copying o r p u b l i c a t i o n o f th is thes is for f inanc ia l gain sha l l not be allowed without my writ ten permission. Department of HRGSTftj The Univers i ty of B r i t i s h Columbia 2075 Wesbrook Place Vancouver, Canada V6T 1W5 Date 1th Sept - 1911 ABSTRACT Estimates of the above-ground net primary production, standing crop biomass and above-ground auto-trophic energy flows were made for eight 0.04 ha plots i n naturally seeded 8 to 10 yr old red alder (Alnus rubra Bong.) ecosystems near the University of B r i t i s h Columbia. A l l plots had closed canopies and covered a range of stem densities (8,204 to 42,971 stems per ha.) and s i t e classes (good, medium and poor). The mean overstorey biomass was 82 mt/ha (range: 40-112 mt/ha) and current overstorey net productivity was 28,601 Kg/ha/yr (range: 17,802-40,831 Kg/ha/yr). Understorey biomass and productivity were 1.5 percent and 2 percent of the overstorey values respectively. Salmonberry (Rubus speatabilis Pursh) formed 68 percent of the understorey biomass and required at least 6 percent f u l l - s u n l i g h t before growth was s i g n i f i c a n t . L i t t e r f a l l averaged 4,454 Kg/ha (range: 3,019-5,713 Kg/ha) and the undecomposed f o r e s t - f l o o r (L l a y e r ) , 5,811 Kg/ha. The plot averages for the biomass accumulation r a t i o of 2.86 Kg/Kg, 2 2 for the leaf area index (one side only) of 7.64m /m , f o r the fol i a g e a s s i m i l a t i o n e f f i c i e n c y of 4.9 Kg/Kg and f o r the 3 standing crop density index of 1.06 Kg/m were a l l i n the upper ranges f o r cool-temperate deciduous f o r e s t s . The mean c a l o r i c content of the above-ground tree biomass was 4.53 Kcal/g ash-containing matter. There was a i i i . s i g n i f i c a n t increase i n c a l o r i c values with increasing height i n the tree and during the f a l l . Net conversion e f f i c i e n c y of v i s i b l e r a d i a t i o n for the growing season (April-Qct.) was 2.9 percent (range: 1.8-4.2 percent). Energy invested i n biomass (biocontent) averaged 37,203 2 Kcal/m (67 percent stem, 33 percent crown) and energy invested i n net primary production (production content) 2 averaged 13,064 Kcal/m (54 percent stem, 46 percent crown). Seventeen percent of production content was l o s t to tree-l i t t e r f a l l . The forest f l o o r energy turnover was 1.2 yrs. Denser stands were characterized by a narrower range of dimensional classes, a higher mortality, a greater current net primary production and f o l i a g e e f f i c i e n c y , a higher solar energy conversion rate but a s i m i l a r cumulative biomass to the less dense stands. Density-dependent growth models are hypothesized i n which denser stands achieve f u l l s i t e occupancy at a l a t e r stage than less dense stands. The potentials of alder as a f u e l and biomass-farm crop are discussed. i v . TABLE OF CONTENTS Page TITLE PAGE i ABSTRACT i i TABLE OF CONTENTS i v LIST OF TABLES v i i i LIST OF FIGURES x LIST OF APPENDICES x i i i LIST OF ABBREVIATIONS x i v ACKNOWLEDGEMENTS X V CH. 1 INTRODUCTION 1 A. REVIEW OF ECOLOGICAL LITERATURE 1 (1) DISTRIBUTION . . 1 <2) FOREST SUCCESSION 1 (3) BENEFICIAL EFFECTS ON THE FOREST ENVIRONMENT . . 3 (a) Nitrogen and S o i l F e r t i l i t y . . . 3 (b) B i o l o g i c a l Control 4 B. REVIEW OF BIOMASS LITERATURE 5 (1) SHORT ROTATION CONCEPTS 5 (2) BIOMASS AND PRODUCTIVITY OF RED ALDER\ . 5 C. THESIS OBJECTIVES . 1 1 CH. 2 DESCRIPTION OF AREA AND METHODS . . . . 12 A. THE STUDY AREA 12 B. THE METHODS 13 V . Page (1) FIELDWORK 13 (a) Sampling Techniques . . . . . . 13 (b) Leaf Areas 14 (c) Lesser Vegetation 15 (d) L i t t e r F a l l 15 (e) Branch Productivity 15 (f) C a l o r i c Content 16 (g) Light Penetration 16 (2) LABORATORY WORK 17 (a) Sample Trees 17 (b) Leaf Areas 17 (c) Lesser Vegetation 17 (d) L i t t e r F a l l . 17 (e) Branch Productivity 18 (f) C a l o r i c Content 18 (3) DATA ANALYSIS 20 (a) Sample Trees 20 Crown dry weights 20 Bole dry weights 21 Bole productivity 22 Branch productivity 23 Master-table 24 (b) Leaf Areas 25 (c) Lesser Vegetation 26 (d) L i t t e r F a l l 26 v i . Page (e) C a l o r i c Content 26 (f) S t a t i s t i c a l Tests 26 CH. 3 RESULTS AND DISCUSSION 27 A. BIOMASS AND PRODUCTION 27 (1) SAMPLE TREES . . . . . 27 (a) Master Table Construction 27 Bole dry weight 27 Bole production 28 Branch production . . . . . . . 28 (b) Deriving Regressions from the Master Table . . . 33 General 33 Wood and bark biomass 35 Wood and bark production i . . . . 37 Multiple-covariance analysis . . . . 37 Crown equations 48 Crown biomass 48 Crown production . . . . . . . . 50 (2) APPLICATION TO STAND 60 (a) Tree Measurements 60 (b) Biomass . 60 (c) Production 65 (3) LESSER VEGETATION . . . . . . . . . 69 (4) LITTER FALL AND LITTER ACCUMULATION . . . 74 (5) PRODUCTION AND PRODUCTIVITY PARAMETERS . . 81 v i i . Page B. ENERGY FLOWS 87 (1) CALORIC CONTENT 87 (2) ENERGY FLOWS AND EFFICIENCIES . . . . 92 (a) Flows of Energy . 92 (b) E f f i c i e n c i e s 95 CH. 4 CONCLUSIONS AND SUMMARY 97 A. CONCLUSIONS 97 (1) METHODOLOGY 97 (2) BIOMASS, PRODUCTION AND ENERGY FLOWS . . 98 B. SUMMARY 103 BIBLIOGRAPHY 107 APPENDICES . . . . . 126 v i i i . LIST OF TABLES Page Table 1 Biomass and Yields of Red Alder . . . 7 Table 2 Estimated Biomass and Yields of Red Alder In Western Oregon 8 Table 3 E f f e c t s of Stand Density on Biomass and Yields of Red Alder 9 Table 4 Average Radial Increment for the 8 Red Alder Total-Sample-Trees 29 Table 5 Radial Growth at 0. and 1.3m for the 72_ Red Alder Sample-Trees . . . . . . 30 Table 6 Summary S t a t i s t i c s for the 20 Red Alder Branch-Production-Sample-Trees . . . 31 Table 7 Master Table Sample-Tree S t a t i s t i c s Summary 34 Table 8 Potential Regression Equations for Red Alder Bole Biomass 35 Table 9 Estimating Equations for Red Alder Bole Biomass and Productivity . . . . . 39 Table 10 Pote n t i a l Regression Equations for Crown Biomass and Production . . . . . 49 Table 11 Estimating Equations for Red Alder Crown Biomass and Productivity 5^ Table 12 Differences Between the Maximum and Conditioned Models for Red Alder Crown Components 53 i x . Page Table 13 Mean Measurements, Above Ground Biomass and Net Production for 8-10 Yr Red Alder Ecosystems by 0.04 HA Plots 61 Table 14 Proportion of Branch Size Classes and Reproductive Parts f o r Red Alder Sample-Trees i n Crowded and Uncrowded Stands . . 66 Table 15 Understorey Above Ground Biomass, Net Production and Light Penetration for 8-10 Yr Red Alder Ecosystems 70 Table 16 Percent Species Composition of Understorey Biomass i n 8-10 Yr Red Alder 73 Table 17 L i t t e r F a l l Totals f o r 8-10 Yr Red Alder i n the F a l l of 1976 75 Table 18 Above Ground Biomass Accumulation Ratios f o r a Range of Forests 82 Table 19 Production and Productivity Parameters for 8-10 Yr Red Alder Ecosystems 83 Table 20 C a l o r i c Values i n 8-10 Yr Red Alder Ecosystem Components - S p a t i a l and Temporal Flows 88 Table 21 Above Ground Autotrophic Energy Flow i n 8-10 Yr Red Alder Ecosystems .* . . . . . 93 X . LIST OF FIGURES Page F i g . 1 The Range of Red Alder 2 F i g . 2 Three Dimensional Relationship Between Stem Wood Biomass and Biomass Indices for 8<to, 10 Yr Red Alder Sample Trees i n Crowded Conditions 40 F i g . 3 Three Dimensional Relationship Between Stem Bark Biomass and Biomass Indices f o r 8 to 10 Yr Red Alder Sample Trees i n Crowded Conditions 41 F i g . 4 Three Dimensional Relationship Between Stem Wood Biomass and Biomass Indices for 8 to 10 Yr Red Alder Sample Trees i n Uncrowded Conditions 42 F i g . 5 Three Dimensional Relationship Between Stem Bark Biomass and Biomass Indices for 8 to 10 Yr Red Alder Sample Trees i n Uncrowded Conditions 43 F i g . 6 Three Dimensional Relationship Between Current Stem Wood Production and Production Indices for 8 to 10 Yr Red Alder Sample Trees i n Crowded Conditions 44 x i . Page F i g . 7 Three Dimensional Relationship Between Current Stem Bark Production and Production Indices for 8 to 10 Yr Red Alder Sample Trees i n Uncrowded Conditions 45 F i g . 8 Three Dimensional Relationship Between Current Stem Wood Production and Production Indices for 8 to 10 Yr Red Alder Sample Trees i n Uncrowded Conditions . 46 F i g . 9 Three Dimensional Relationship Between Current Stem Bark Production and Production Indices for 8 to 10 Yr Red Alder Sample Trees i n Uncrowded Conditions . . . 4 7 F i g . 10 Three Dimensional Relationship Between Branch Biomass and Biomass Indices for 8 to 10 Yr Red Alder Sample Trees i n Uncrowded Conditions 54 F i g . 11 Three Dimensional Relationship Between Leaf Biomass and Biomass Indices for 8 to 10 Yr Red Alder Sample Trees i n Uncrowded Conditions 55 F i g . 12 Three Dimensional Relationship Between Current Branch Production and Production Indices for 8 to 10 Yr Red Alder Sample Trees i n Uncrowded Conditions 56 x i i . Page F i g . 13 Three Dimensional Relationship Between Branch Biomass and Biomass Indices for 8 to 10 Yr Red Alder Sample Trees i n Crowded Conditions 57 F i g . 14 Three Dimensional Relationship Between Leaf Biomass and Biomass Indices for 8 to 10 Yr Sample Trees i n Crowded Conditions . . . 58 F i g . 15 Three Dimensional Relationship Between Current Branch Production and Production Indices for 8 to 10 Yr Red Alder Sample Trees i n Crowded Conditions 59 F i g . 16 Frequency D i s t r i b u t i o n of Median Alder Per .0004 Ha Sub-Plot by Root-Collar Diameter Breast-Height Diameter and Height Class (Average a l l 8 Plots) 62 F i g . 17 Frequency D i s t r i b u t i o n of Median Alder Per .0004 Ha Sub-Plot by Root-Collar Diameter Breast-Height Diameter and Height Class for Each Plot 63 F i g . 18 Daily Rate of L i t t e r F a l l f or 8 to 10 Yr Alder During the F a l l of 1976 ( A l l 8 Plots) . . 77 F i g . 19 Daily Rate of L i t t e r F a l l for 8 to 10 Yr Alder During the F a l l of 1976 (For Each plot) 78 x i i i . LIST OF APPENDICES Page APPENDIX I L i s t of Common and Latin Names . . . 126 APPENDIX II Bomb Calorimetry 129 APPENDIX III Back-Transformation of Standard Errors i n the Logarithmic and Hyperbolic Form 133 Simple Correlation C o e f f i c i e n t s for Bole Biomass and Production . . . . 134 Simple Correlation C o e f f i c i e n t s for Crown Biomass and Production . . . 135 APPENDIX IV Multiple Covariance Analysis Between Crowded and Uncrowded Stands for Bole Components 136 Multiple Covariance Analysis Between Crowded and Uncrowded Stands f o r Crown Components J 138 Analysis of Variance on Red Alder Ecosystem C a l o r i c Values 139 APPENDIX V Three Dimensional Graph Computer Programme 139 x i v . LIST OF ABBREVIATIONS BAR biomass accumulation r a t i o cd crown depth cf correction factor cw crown width d3 diameter at 3 m dblc diameter base l i v e crown a 2h diameter Breast-height squared x height dw oven dry weight FAE foliage assimilation e f f i c i e n c y fw fresh weight hdc height to dead crown hlc height to l i v e crown h(t) t o t a l height LAI leaf area index LAR leaf area r a t i o NPP net primary productivity PAR photosynthetically active radiation PLAR production to leaf area r a t i o red root c o l l a r diameter r 2 h root c o l l a r diameter squared x height SCDI standing crop density index X V . ACKNOWLEDGEMENTS P a r t i a l support for t h i s thesis was made through a B.C. Forest Service grant, PC-006 to Dr. J.H.G. Smith and i s g r a t e f u l l y acknowledged. The advice and encourage-ment given by my supervisor, Dr. J.H.G. Smith made my task both possible and a pleasure. I would l i k e to thank Dr. G.F. Weetman of U.N.B. for i n i t i a l i n s p i r a t i o n , Dr. J.P. Kimmins whose many c r i t i c i s m s were a major source for continued i n s p i r a t i o n and Dr. P. Haddock for h i s many helpf u l comments. In addition I am indebted to Z. S r e j i c , D. Ganong and C. Smith for help with the f i e l d work, Paula Maisonville for help with dry-weighing and measuring disks, and j . McPhalen for help and time devoted to writing the three-dimensional computer programme. 1. CH.l. INTRODUCTION A. REVIEW OF ECOLOGICAL LITERATURE (1) DISTRIBUTION Red alder (Alnua rubra Bong.) can be found along the P a c i f i c Coast of North America from 60°N to 34°N (Fig. 1). I t i s r a r e l y more than 150 km from the coast or above an a l t i t u d e of 750 m, and requires at l e a s t 60 cm of r a i n each year (Worthington et a l . 1962, Plank 1971). Growth i s best on the wet a l l u v i a l lower v a l l e y slopes and v a l l e y bottoms and on seepage s i t e s at higher elevations (Newton et a_l. 1968), though f u l l e s t expression of production i s confined to western Washington and Oregon, between 5 and 10 km from the sea (Scott et a l . i n press). (2) FOREST SUCCESSION Red alder (hereafter c a l l e d alder) plays an important r o l e i n the succession of such species as Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), western redcedar (Thuja pliaata Donn ) and western hemlock (Tsuga heterophylla (Raf.) Sarg.). Alder i s a s e r a i species par excellence, quickly occupying areas disturbed by f i r e , erosion and logging (Worthington et a l . 1962). Man's interferences have engendered—albeit u n w i t t i n g l y — a l d e r ' s current status as the major commercial hardwood resource i n the P a c i f i c Northwest ( L i t t l e i n press). Seeds germinate i n profusion i n cool, moist 2. Figure 1. THE RANGE OF RED ALDER (Alnua rubra) Source: Plank 1971 3. bare mineral s o i l . (Newton et a l . 1968, Kenady et a l . i n press). As many as 3 m i l l i o n seedlings per hectare have been counted i n the early spring of the f i r s t year (Zavitkovski and Stevens 1972). I t i s common for alder to reach a height of 2 metres within 2 years, and to continue growth at 1% metres a year to the age of 13 to 20 years (Smith 1968). Although alder w i l l outgrow conifers over short time horizons, productivity f a l l s o f f at 10-15 years to be exceeded by conifer associates a f t e r 25-30 years (Bernstert,:1961) . , (3) BENEFICIAL EFFECTS ON THE FOREST ENVIRONMENT As a po t e n t i a l pure or mixed plantation crop, alder i s being recurrently buried and exhumed. The 'buriers' accuse alder of being a weed species of no economic value, whereas the 'grave-diggers' have c a p i t a l i z e d both on alder's ameliorating e f f e c t s on the forest environment and high growth rates. (a) Nitrogen and S o i l F e r t i l i t y Among alder's b e n e f i c i a l e f f e c t s are the a b i l i t i e s to f i x nitrogen v i a root nodule symbionts, to increase nitrogen c y c l i n g through l i t t e r f a l l , and to improve s o i l structure. A combined e f f e c t i s to enhance s o i l f e r t i l i t y — a n important a t t r i b u t e on nitrogen d e f i c i e n t s i t e s (Tarrant 1961, 1968). On i n i t i a l l y i n f e r t i l e s o i l s , dense stands of alder may add an annual average of 320 Kg/ha of nitrogen to the ecosystem during the f i r s t 15 years of growth (Newton et a l . 1968). When 4. compared to adjacent Douglas-fir stands there may be a three to f i v e f o l d increase i n nitrogen turnover (Tarrant e t a l . 1969, Gessel and Cole i n press). The rapidly decomposing leaves produce a r i c h mull humus layer (Tarrant and M i l l e r 1963) and bulk density i s lowered (Newton e t a l . 1968). The re s u l t i n g improved forest environment has been demonstrated to s i g n i f i c a n t l y increase the growth of Douglas-fir (Tarrant 1961, Berg and Doerken 1975, M i l l e r and Murray i n press). However, under a spectrum of present economic circumstances, Atkinson and Hamilton (in press) have shown that i t i s cheaper to a r t i f i c i a l l y f e r t i l i z e Douglas-fir rather than to intermix alder, though prospective increases i n f e r t i l i z e r and petroleum costs may invalidate t h i s argument, (b) B i o l o g i c a l Control Alder i s p o t e n t i a l l y useful as a b i o l o g i c a l control for Phellinus (Poria) w e i r i i (Murr.) Gilbertson, a root-rot of Douglas-fir and other western conifers (Li et a l . 1967, 1968). Various secondary organic compounds produced by alder have a l l e l o p a t h i c e f f e c t s on P. w e i r i i . The build-up of n i t r a t e nitrogen beneath alder stands (Bollen et a l . 1968) i n h i b i t s P. weirii—since the fungus lacks n i t r a t e reductase—and promotes antagonistic fungi such as Triahoderma v i r i d e Fr. and several Streptomyaetes 8pp.. Although a rotation of alder may cleanse the s i t e of root-rot, suppression of an outbreak i n mixed alder-conifer stands has not been convincingly demon-strated (Nelson et a l . i n press). 5. B. REVIEW OF BIOMASS LITERATURE (1) SHORT ROTATION CONCEPTS Other l i n e s of argument advanced by alder protagonists include the high biomass y i e l d s attained i n natural stands and the potentials for improvement. The apparent paradox of increasing f i b r e demands as supplies decrease has led to the advocacy of intensive, short-rotation plantations (Inman 1977). The idea gained ascendancy as sycamore "s i l a g e " (McAlpine et a l . 1966, Herrick and Brown 1967, Steinbeck et a l . 1972) and as mini-rotation forestry (Shreiner 1970). Indeed, Ribe (1974) concluded that short-rotation plantations w i l l play a dominant r o l e i n meeting projected wood d e f i c i t s i n the USA. The concepts of 'complete-tree u t i l i z a t i o n 1 (Young 1964), ' f u l l - f o r e s t u t i l i z a t i o n ' (Keays and Hatton 1975), 'biomass farms' (Howlett and Gamache 1977) and 'energy-plantations' (Szego et a l . 1972, Szego and Kemp 1973, Evans 1974, V a i l et a l . 1975, Szego 1976) are a l l manifestations of the concern f o r forest resource s c a r c i t y . (2) BIOMASS AND PRODUCTION OF ALDER As a short rotation species, alder i s a major candidate i n the P a c i f i c Northwest (Smith and DeBell 1973, Evans 1974, DeBell 1975, Howlett and Gamache 1977, DeBell et a l . i n press). A poten t i a l competitor, black cottonwood {Populus triohooarpa T. & G.) may achieve growth rates exceeding 12mt/ha/yr on 4 yr coppice cycles i n western 6. Washington (Heilman et a l . 1972), but planting and planting stock costs exceed the discounted value of the f i n a l harvest (Howlett and Gamache 1977). Work on alder by Smith (1968, 1972, 1973) for southwest B r i t i s h Columbia, DeBell (1972) for the lower Columbia River Valley i n Washington, Zavitkovski and Stevens (1972) f o r western Oregon, and by Smith and DeBell (1974) using data from a l l these areas has demonstrated the high biomass y i e l d s of natural stands. Tables 1,2 and 3 show that productivity peaks between 8 to 15 years. Upper l i m i t s of production i n t h i s age class are estimated as 64 mt/ha/yr (Smith 1973) and 20 mt/ha/yr (DeBell 2 1975). However, because plots were small (2x2 m ) and the bias of Smith and B e l l ' s investigations orientated to maximum y i e l d estimates, t h e i r r e s u l t s do not r e f l e c t natural growth over larger areas and are thought to overestimate biomass (Smith 1975). Zavitkovski and Stevens (1972) have estimated a net primary productivity between 10 and 15 years of 26 mt/ ha/yr (including roots), yet Table 2 shows that the mean annual above-ground increment i n the f i r s t 10 years was only 5.5 mt/ha/yr. Notwithstanding t h i s apparent discrepancy of estimates, Zavitkovski and Stevens also f a i l e d to recognize the e f f e c t s of d i f f e r e n t stand densities within f u l l y stocked conditions and the important r o l e t h i s has i n governing biomass. Smith and DeBell (1974) have shown i n stands younger than 4 years o l d that biomass may be greater i n the TABLE 1. BIOMASS GROWTH AND YIELDS OF RED ALDER Location Stand Stand Average Average Total Mean Annual Age Density Tree Height Tree DBH Biomass Biomass Increment (yrs) (stems/ha) (m) (cm) (Kg/ha) (Kg/ha/yr) Columbia R. Valley 1-2 122,000 1.8 - 5,700 3,811 it 3-4 60,000 3.4 - 13,300 3,811 II 5-7 39,000 5.2 - 43,000 7,173 II 8-11 14,000 10.1 - 187,400 19,727 II 12-14 13,000 8.8 - 128,219 9,863 Southwest B r i t i s h Columbia (poor site q u a l i t y ) 2 , 5 4 8 150,000 28,000 3.1 6.1 2.0 3.8 107,600 135,032 26,900 16,879 Southwest B r i t i s h Columbia (medium site q u a l i t y ) 3 , 5 3 5 8 150,000 28,000 14,000 3.1 6.1 9.2 2.0 3.8 6.9 107,601 134,500 312,256 35,867 26,900 39,032 Southwest B r i t i s h Columbia (good site 1,5 quality)^' 1.5 3.5 6.0 8.0 150,000 28,000 14,000 9,000 3.1 6.1 9.2 12.2 2.0 3.8 6.9 9.9 107,997 134,761 313,308 514,792 71,998 38,503 52,218 64,349 """Above-ground biomass only, excluding foliage. Oven-dry basis. 2 . Site index = 20m at 50 years. 3 Site index = 30m at 50 years. 4 . Site index = 40m at 50 years. •^Biomass estimates for Southwest B r i t i s h Columbia exclude branches. Sources: Lower Columbia River Valley - DeBell, 1975; Southwest British Columbia - estimates based on data i n Smith, 1973, and reported in Howlett and Gamache, 1977. 8. TABLE 2. ESTIMATED BIOMASS1 GROWTH AND YIELDS OF RED ALDER STANDS IN WESTERN OREGON Stand Stand Total Mean Annual Age Density Biomass Increment (yrs) (stems/ha) (Kg/ha) (Kg/ha/yr) 1 401,000 200 200 2 116,000 1,300 650 3 56,000 3,600 1,200 4 34,000 7,400 1,850 5 22,000 12,600 2,520 6 16,000 19,100 3,180 7 12,000 26,700 3,810 8 10,000 35,200 4,400 9 8,000 44,400 4,930 10 7,000 54,000 5,400 Above-ground biomass only, excluding f o l i a g e . Oven-dry b a s i s . Source: Estimates made with model developed by Zavitkovski and Stevens, 1972, and reported i n Howiett and ; Gamache, 1977. 9 . TABLE 3. THE EFFECTS OF STAND DENSITY ON BIOMASS AND YIELDS OF RED ALDER Mean Crowding Stand Stand Total Annual Class Age Density Biomass Increment (yrs) (stems/ha) (Kg/ha) (kg/ha) Average 1 69,100 408 408 i t 2 42,000 2,136 1,068 •I • 3 34,600 5,719 1,906 II 4 17,300 5,273 1,318 Dense 1 121,000 1,081 1,081 2 367,900 18,728 9,364 i t 3 207,400 34,314 11,438 i i 4 102,500 31,298 7,825 Very Dense 1 780,20,0 4,965 4,965 H 2 446,900 22,751 11,376 t i 3 380,200 62,751 20,970 II 4 246,900 75,416 18,854 Above-ground biomass only, excluding f o l i a g e . Oven-dry b a s i s . Bark estimated at 15 percent of t o t a l biomass. Source: Estimates based on data i n Smith and DeBell, 1974 and reported i n Howiett and Gamache, 1977. 10. densest compared to average density stands (see Table 3). The question of whether these trends are as pronounced i n older stands remains unanswered. Increased productivity with increased stem crowding has been shown to e x i s t for a number of other tree species, including Abies balsamea (L.) M i l l (Baskerville 1965) and Cryptomeria japonioa (L.f.) D.Don (Takadi and Kawasaki 1966) . Research has also been undertaken on other parts of alder ecosystems, including l i t t e r f a l l (Zavitkovski and Newton 1971) and lesser vegetation (Henderson 1970). A t o t a l l y integrated study of an alder ecosystem i s lacking. There i s a paucity of data on c a l o r i c values. Reports i n the l i t e r a t u r e include 4,670 cal/g for bark (Harkin and Rowe 1971) and 4,440 cal/g for stem wood (Forest Products Research Society, reported i n Howlett and Gamache 1977). Detailed c a l o r i c analyses are a necessary prerequisite for computation of poten t i a l combustion performance and conversion e f f i c i e n c i e s of solar energy. Thus, a need exists for a study which w i l l estimate biomass and productivity of alder between 8 and 15 years based on representative p l o t sizes and over a range of densities within fully-stocked stands. A need exists for data on l i t t e r f a l l and lesser vegetation i n the same stands as biomass and production estimates were made. A need exists for adequate documentation of below-ground as well as 11. above-ground biomass and production. A need ex i s t s f o r detailed c a l o r i c analysis of alder ecosystems. C. THESIS OBJECTIVES In order to f i l l these gaps i n knowledge, the following thesis objectives were i d e n t i f i e d : (1) To provide estimates of the above-ground biomass,^" 2 net primary production and autotrophic energy-flows i n 8 to 10 year red alder ecosystems, growing i n the v i c i n i t y of the University of B r i t i s h Columbia, Vancouver, B.C. (2) To examine the ef f e c t s of d i f f e r e n t stand 3 . densities and s i t e s classes within f u l l y stocked conditions on the estimates i n objective (1). Below-ground estimates were excluded due to lack of time and manpower. Biomass: the t o t a l weight of a l l plant parts on a unit area at a given time (Whittaker et a l . 1975). Net primary production (NPP): that part of t o t a l or gross primary production of photosynthetic plants remaining a f t e r r e s p i r a t i o n of those plants (Whittaker et a l . 1975). Production refers to the accumulation while productivity expresses the same thing as a rate (Yapp 1972). Si t e classes: based on the s i t e index curves of Worthington et a l . (1960). F u l l y stocked conditions: stands with closed crown canopies. 12. CH.2. DESCRIPTION OF AREA AND METHODS A. THE STUDY AREA1 The study was undertaken i n the v i c i n i t y of U.B.C. in southwestern B r i t i s h Columbia. The area l i e s i n the Coastal Douglas-fir wet subzone (Krajina 1965, 1969). The climate i s Koppen C s f a type ( P a c i f i c mesothermal with mild winters). Temperatures range from 3°C i n January to 18°C in July, with 260 f r o s t - f r e e days (above 5°C). P r e c i p i t a t i o n averages over 100 cm per year, about 25 percent f a l l i n g between May and September. The elevation of the study s i t e s ranged from 80 to 125 m a . s . l . . S o i l parent materials are 300 to 500 feet thick deposits of Pleistocene g l a c i a l debris consisting of t i l l s , clays, gravels and sands. The s o i l s are mainly moderately a c i d i c , f r e e l y drained podsols with a loamy sand or sandy loam texture and stoney in c l u s i o n s . In some areas drainage i s impeded by impervious layers of clays and t i l l s giving perched water tables i n the summer leading to the formation of gleysols. A l l stands examined have developed on mineral s o i l s exposed a f t e r land clearance for road and housing developments. Composition i s uniform, 8 to 10 year Based on Norris 1971. age class red alder plus occasional i s o l a t e d or clumped occurences of paper b i r c h (Betula papyrifera Marsh), b i t t e r cherry (Prunus emarginata (Dougl.) Walp.) and willow (Salix lasiandra Benth.). The understorey, i f present, i s l a r g e l y composed of salmonberry (Rubus speotabilis Pursh) and, to a lesser extent t r a i l i n g blackberry (Rubus ursinus C. & S.). B. THE METHODS (1) FIELDWORK (a) Sampling Techniques In June and July 1976 four pairs of 0.04 ha square or rectangular main-plots were established. One of each p a i r was located i n a crowded closed-canopy stand, the other i n an adjacent less crowded closed-canopy stand. A range of s i t e types were chosen based on the s i t e index curves of Worthington et a l . (I960).* Each main-plot was divided i n t o one hundred 2x2 m sub-plots. In each sub-plot a l l l i v e and dead trees were recorded by species and dbh, or r o o t - c o l l a r diameter (red) i f under 1.3 m t a l l . For the tree of mean dbh i n each sub-plot (called the median tree) dbh, red, diam. at 3 m (d3), crown Good Poor = over 27 m at 50 yrs; Medium = = below 18 m at 50 yrs. 18-27 m at 50 yrs; 14. width (cw), height to dead crown (hdc), height to l i v e crown (hlc) and t o t a l height (h) were noted. Ten contiguous sub-plots were joined to form 10 grouped-plots i n each main-p l o t . The grouped-plot median tree of largest dbh ((called the sample^tree) was f e l l e d at r o o t - c o l l a r for stem analysis. The grouped-plot tree of average dbh would have been more desirable, but sampling techniques had to be t a i l o r e d f o r another study (see J.H.G. Smith i n press). Ten sample-trees were f e l l e d i n each main-plot except for one main-plot i n which only three were f e l l e d due to time constraints. Sample-tree branches were clipped o f f at the base. Boles were cut into 10 logs of equal length above 1.3m and two 0.65 m logs below t h i s height. F;resh weights of logs were recorded to the nearest 25 g. Discs, 3 cm thick, were cut at r o o t - c o l l a r and breast-height for a l l sample-trees and from the base of a l l 12 logs for the sample-tree of mean dbh i n each main-plot (hereafter c a l l e d the total-sample-tree). Branches were divided into 3 size classes: large (> 2 cm diam.), medium (0.6 cm > 2 cm diam.) and fi n e (<0.6 cm diam.). The f i n e branches included leaves. Each class was fresh-weighed to the nearest 25 g. Three sub-samples (A/ 25-100 g) were taken randomly from each s i z e class per sample-tree for dry-weighing, (b) Leaf Areas At two week i n t e r v a l s from June to November samples 15. of both sun and shade leaves were c o l l e c t e d from 2 co-dominant trees f e l l e d on an average density s i t e f or ca l c u l a t i o n of leaf-area-to-weight r a t i o s . (c) Lesser Vegetation In each main-plot, three %x% m quadrats were placed systematically along a diagonal transect. Above-ground minor vegetation was harvested and sorted by species. Clipping was done i n late August when i t was considered that maximum biomass occurred. (d) L i t t e r F a l l Two hx% m and two . / j x l m l i t t e r traps were s e l e c t i v e l y positioned i n each main-plot, two traps i n the le a s t dense and two traps i n the most dense parts. These were c o l l e c t e d at convenient (p>2-3 wk) in t e r v a l s from August to mid-December. (e) Branch Productivity Because data c o l l e c t e d during summer 1976 were inadequate for branch production estimation, 20 branch-sample- trees were f e l l e d i n February 1977. An approach used by Satoo (1968a) was adapted f o r t h i s purpose. Branch-sample-trees were s t r a t i f i e d by dbh classes within dense and less dense stands next to or within main-plots. Branches were clipped o f f just above the basal swelling and sorted by age-class. Current twigs were separated. Branches and current twigs were fresh-weighed to the nearest 5 g. Sub-sample discs 2-5 cm long for every branch and 20^100 g f o r current twigs 16. were taken for dry-weighing. (f) C a l o r i c Content Two co-dominant alder were f e l l e d i n mid-July, mid-September and mid-November i n an average density stand. Samples ( 50-200 g) of roots (1 m from tree butt), stem wood and bark at 1.3 m, branches, current twigs, leaves, s t r o b i l e s (female cones), catkins and p e r s i s t i n g s t r o b i l e s (female cones older than 1 growing season) were c o l l e c t e d f o r c a l o r i c content analyses. Samples from the forest f l o o r (L-layer) were c o l l e c t e d once i n September from a hxh m^  quadrant i n the centre of each main-plot. Lesser vegetation was bulked and analysed as ferns, mosses, herbs, grasses, conifers, and Rubus spp which were measured separately for current year and older tissues. (g) Light Penetration A Weston Illuminometer held above the minor vegetation was used to measure l i g h t penetration. On cloudless days from July through to September records were made almost simultaneously i n f u l l sunlight and i n the densest and most open parts of each main-plot. In September 1976 an attempt was made to use the technique.described by Friend (1961) using integrated photo-copying paper. However, a period of fog ruined the experiment and any chances of a repeat. 17. (2) LABORATORY WORK (a) Sample Trees A l l samples were sealed i n p l a s t i c bags and stored at 1-2°C. A l l measurements were made to the nearest 0.5 mm and 0.1 g for stem wood, stem bark, roots and branches, and 0.01 g for leaves and reproductive structures. Samples were oven-dried for 24 hrs at temperatures of 105°C for stem wood and stem bark, and 70°C for a l l other components. The width of annual rings and bark (inner and outer) were measured along an average radius on each bole d i s c . Bark and wood were separated and weighed fresh and dry. A b r i e f period of r e f r i g e r a t i o n ( 1 week) induced leaf abscission from the f i n e branch sub-samples. The fresh and dry-weights of large, medium and f i n e branches and leaves were recorded. (b) Leaf Areas Leaf area samples were photocopied, then dried and weighed. Leaf areas (one side only) were measured to the nearest ram^ by a s e l f - c o r r e c t i n g planimeter. (c) Lesser Vegetation Ground vegetation within each "quadrat was sorted by species and separated into current (leaves, flowers, annuals) and previous years' growth. (d) L i t t e r F a l l Total l i t t e r f a l l dry weight was recorded and the 18. proportions of leaves, twigs and sexual parts were established i n 10 randomly selected oven-dried sub-samples. (e) Branch Productivity Ring growth was measured on an average radius for the branch-sample-tree d i s c s . Fresh and dry weights were recorded separately for each d i s c . (f) C a l o r i c Content Ca l o r i c values were computed by burning samples i n a Parr 1341 plain-jacket oxygen bomb calorimeter. The standard procedures can be found i n the Parr Manual (1976) and are f u l l y explained i n A.S.T.M. methods D-240-64, D-3286-73 and E-144-64 (A.S.T.M. 1976). The s t r i c t u r e s of Golley (1961) and Leith (1968, 1975) on the determination of eco l o g i c a l e f f i c i e n c i e s were followed. C a l o r i c content was based on ash-containing matter. A l l materials were oven-dried at 70°C for 24 hours and ground i n a Wiley M i l l to 60 mesh-per-inch. Care was taken not to overheat during grinding. Three Ig r e p l i c a t e s for each sample were compacted i n a p e l l e t press and weighed to the nearest mg i n preweighed combustion cups. Because oven-dry material was d i f f i c u l t to compact, the moisture content was brought to 5 percent leaving a l l samples i n petri-dishes overnight i n a room with controlled r e l a t i v e humidity. 19. The calorimeter water-factor" 1* was standardized at the beginning of the experimental runs and again a f t e r 6 weeks, using s i x l g benzoic acid p e l l e t s . The best r e s u l t s were attained by placing the electrode wire immediately above—but not touching—the p e l l e t . One ml of d i s t i l l e d water was added to the bomb. Oxygen pressure was standardized to 30 Atmospheres. If combustion was incomplete a repeat run was made. Two hundred grams of fresh d i s t i l l e d water was used for each f i r i n g . The water was maintained at 1 to 2°C below room temperature by storing i n a cooler adjacent room. After f i r i n g , the bomb was flushed out with d i s t i l l e d water and the washings t i t r a t e d against 0.0725N NaC0 3 solution to correct for n i t r i c acid formation (at t h i s concentration 1 ml of solution used i n t i t r a t i o n equals one c a l o r i e ) . Readings were also corrected for r e s i d u a l electrode wire but not sulphuric acid formation due to the inordinate time required and the small gain i n accuracy achieved (Leith 1975) . A deviation of up to 3 percent between r e p l i c a t e s was accepted (Golley 1961). Computational d e t a i l s can be found i n Appendix I I . Water-factor: the number of c a l o r i e s necessary to rai s e the temperature of the water bath by 1 degree centigrade. 20. (3) DATA ANALYSIS (a) Sample Trees The data f o r 1 sample-tree were incomplete and therefore rejected. The objective of the analysis was to develop a master-table of s t a t i s t i c s f o r the 72 sample-trees on which to base predictive regression equations applicable to the median trees. The approach used i s c a l l e d 'dimension analysis' (Whittaker 1961, 1962, 1966; Whittaker and Woodwell 1971; Whittaker and Marks 1975) or 'allometry' (Kira and Shidei 1967, Satoo 1968a, 1968b); i t relates e a s i l y measured independent variables to a dependent variable by the l e a s t squares technique. and f r u i t s were calculated d i r e c t l y for each sample tree using the following formulae: Crown dry weights The dry-weight correction factors for branches, leaves n n (i) Z d i i = l n E f i i = l n n ( i i ) . EX. i = l EF. • i = l (i) 21. where d = sample dry-weight f = sample fresh-weight Xs = dry-weight correction factor F = t o t a l fresh-weight of crown components per tree X = t o t a l dry-weight of crown components per tree n = 1,2...72 (# sample trees) Bole dry weights Discs from a l l 12 logs were only available for the 8 total-sample-trees. A single correction factor f o r the percentage and dry-weight of wood and bark was derived for each of these trees by weighting the correction factor for each disc by the basal area formula as follows: I m n m n m :;n ( i i i ) . . . £ Z Z X. = Z Z Z d. Z Z Z d. i= l j=i k=l 1 : , K i = l j=l k=l X 3 K . i = l j=l k=l 1 3 K m n m Z Z Z f . . , Z Zd.., i = l j=l k=l 1 ] K i = l j=l 1 3 K I m n I m (iv) . .a. Z z Z Y. = z z F..- ( i i i ) i-1 j=l k=l 1 3 K i = l j=l 1 3 m n 1 m n I (v) . . . Z Z ( Z Y. .. ) = Z Z Z (y. ., 2) j=l k=l i = l 13k j = 1 h = 1 1 = 1 y i l k d section dry weight f = section fresh weight D section correction factor F = fresh weight of the log X = dry weight of the log y = t o t a l bole correction factor *• 1,2...12 (# sections per tree) m 1,2... 8 (# sample trees) n = 1,2 (# parts: wood or bark) Using Y as the dependent variable a regression equation was f i t t e d to the data from the 8 trees by the elimination procedure and used to estimate Y for the 72 sample-trees. Bole productivity The productivity of stem wood and stem bark was computed for the 8 total-sample-trees by weighting the production r a t i o for the 12 discs per tree by the basal area formula. The stem wood production r a t i o for each d i s c was calculated by the formula used at Brookhaven, U.S.A. (Whittaker and Woodwell 1968 p. 5): (vi) . . . AW=4^2 - ( r - i ) 2 7 / r 2 ( v i i ) . . . AWP = Z AW2 k=l k-Where AW = disc stem wood production r a t i o r = disc radius i = mean annual r a d i a l increment for 1974 and 1975 AWP = total-sample-tree stem wood production r a t i o I = 1,2...12 (# discs per t r e e ) . The r a t i o AWP was then correlated by regression analysis to the total-sample-trees and the resultant equation was used to estimate stem wood production i n the 72 sample-trees Bark growth f o r each of the 72 sample-trees was calculated d i r e c t l y by d i v i d i n g the dry weight of bark by the age of the tree. This i s probably an underestimate of current bark growth (Whittaker and Woodwell 1968). The method preferred at Brookhaven has been to multiply the dry weight of bark by the wood growth rate. This assumes that bark and stem growth are d i r e c t l y proportional. This did not appear to hold for the alder and was rejected, pending further analysis Branch production Branch wood plus bark production r a t i o s were calculated for branch discs using formula (vi) and averaged within branch age classes for each branch-sample-tree. Disc wood production was based on r a d i a l growth i n 1976. Because bark was d i f f i c u l t to separate, disc branch bark production was assumed to equal the bark contribution to branch radius 24. divided by branch age. The branch production r a t i o for each age c l a s s was m u l t i p l i e d by the branch dry weight for that age c l a s s , summed fo r each branch-sample-tree and added to the dry weight of current twigs. A branch production r a t i o was calculated for each branch-sample-tree by d i v i d i n g branch production by branch biomass. A regression equation using t h i s r a t i o as the dependent variable was computed for the 20 branch-sample-trees and applied to the 72 o r i g i n a l sample-trees a f t e r adjusting for differences i n growth between June-cTuly 1976 and February 1977. Master-table Combining the output from the above analyses a master-table was generated for the 72 sample-trees. Scattergrams were plotted to show the re l a t i o n s h i p between the dependent variables qf.biomass and production and a l l independent variables, and to help to i d e n t i f y 'outliers' (defined as an observation l y i n g 3 standard deviations from the regression line) which were rejected. Regression equations were f i t t e d using the elimination procedure. F i n a l equations were selected on the basis of standard error of estimate (SE) or estimated SE (SE e) and the multiple c o e f f i c i e n t of 2 determination (R ). Other considerations were: meaningful b i o l o g i c a l r e lationships, ease of field-measurement and a d d i t i v i t y within bole and crown components. Data were assigned to a crowded group (containing 40 sample-trees from 25. plots 2, 4, 5 and 9) and a less crowded group (containing 32 sample-trees from plots 1, 3, 6 and 10). (N.B. The terms crowded and dense are used synonymously, as are uncrowded and less dense)• The hypothesis that regression slopes were p a r a l l e l and intercepts coincident for the two groups was tested by multiple-covariance analysis. S i g n i f i c a n t differences led to the selection of d i f f e r e n t regression equations for the two groups. If i n the f i n a l regression equations the intercepts were negative they were conditioned to zero and the hypothesis that the conditioned and maximum models were not s i g n i f i c a n t l y d i f f e r e n t was tested. This adjustment was necessary to avoid predicting negative dry weights i n the smaller trees. The f i n a l regression equations were applied to the median tree i n each sub-plot, m u l t i p l i e d by the number of l i v e stems i n each sub-plot then summed and averaged f o r each main-plot and expressed as biomass or production per hectare. Ratio estimation was used to indicate the proportions of small, medium and large branches and reproductive parts. (b) Leaf Areas A single leaf-area-to-weight r a t i o (LAR) was calculated by pooling data for sun and shade leaves c o l l e c t e d during the summer and f a l l and corrected f o r p e t i o l a r weight. The dry weight of leaves i n each main-plot m u l t i p l i e d by the 26. LAR gave the leaf area index (LAI). (c) Lesser Vegetation Due to the uniform or systematically varying d i s t r i b u t i o n of lesser vegetation within main-plots and i t s small r e l a t i v e contribution to ecosystem biomass and production, data derived from the quadrats were assumed to adequately represent ground vegetation for the stand. Current productivity was estimated from current biomass (leaves, flowers, annuals) and older biomass divided by 4 . The d i v i s o r was selected subjectively as the time at which minor vegetation invades alder stands at U.B.C. (d) L i t t e r F a l l L i t t e r f a l l data were pooled within each main-plot and used to estimate trends over time and t o t a l s f or the summer and f a l l . (e) C a l o r i c Content Calor i c values were computed using standard formulae (see Appendix I I ) . Analysis of variance and Duncan's Multiple Range Tests were run on a l l components. (f) S t a t i s t i c a l Tests A l l s t a t i s t i c a l analyses were at the a=0.05 s i g n i -ficance l e v e l . For the total-sample-tree regression equations the dependent variables are i n the form of r a t i o s ; f o r the branch-production and sample-tree regression equations the dependent variables are i n the form of dry Kg's. For the independent variables, diameters are i n em's and a l l other measurements are in metres. CH.3. RESULTS AND DISCUSSION A. BIOMASS AND PRODUCTION (1) SAMPLE-TREES (a) Master Table Construction Bole dry weight The best predictive regression equations based on the correction factor for percent and dry weight of stem wood and stem bark f o r the 8 total-sample-trees were: ( v i i i ) . . . Y l = 0.919755 - 0.403548-1/Xl - 0.875788* 1/X2 - 0.235097*X3 R 2 = 0.971, SE(% of Y) = 1.3, N - 8, Y±SY1 = 0.389±.023 (iix ) . . . Y2 = 0.3164319 + 0.00952416'1/X4 + 4.67961'X4 R 2 = 0.952, SE(% of Y) = 3.0, N = 8, Y+SY2 = 0.065±.006 where Y l = stem wood percent and dry weight correction factor Y2 = stem bark percent and dry weight correction factor XI = stem wood correction factor for the disc at r o o t - c o l l a r X2 = stem wood correction factor f o r the dis c at breast-height 28. X3 = dbh X4 = stem bark correction factor for the di s c at breast-height Bole production The best predictive regression equation based on the stem wood production r a t i o f o r the 8 total-sample-trees was: (ix) . . . Y = 0.188869 + 0.585052'Xl r 2 « 0.900, SE(% of Y) = 5.6, N « 8, Y±Sy = 0.270+.039 Kg. where Y = stem wood production r a t i o XI = stem wood production r a t i o for di s c at breast-height raised to the t h i r d power Tables 4 and 5 show the data on which t h i s regression was based. The outermost r i n g was ignored since i t indicated only p a r t i a l growth i n 1976. Although r a d i a l increment shows some tendency to decline during 1975 and 1974, the volumetric contribution continues to increase, though at a decreasing rate, Branch production Table 6A summarizes the data for the 20 branch-sample-trees. Part 6B shows the contribution of each age class to branch biomass. The 1st year branches were small but TABLE 4. AVERAGE RADIAL INCREMENT FOR THE 8 RED ALDER TDTAL-SAMPLE-TREES Age - Rings from p i t h -:tion (yrs) 1 2 3 4 - Radial 5 growth 6 (cm) 7 8 9 12 2.1 .02 .24 .21 II 3.0 .06 .23 .31 .30 10 3.9 .10 .24 .48 .37 .34 9 4.4 .23 .41 .67 .44 .34 8 5.1 .12 .43 .49 .69 .42 .34 7 5.9 .05 .37 .6 .55 .69 .38 .28 6 6.3 .33 .48 .68 .52 .66 .35 .25 5 6.9 .13 .35 .66 .65 .50 .59 .34 .24 4 7.3 .03 .20 .47 .64 .60 .45 .61 .31 .24 3 2 8.0 .17 .36 .57 .67 .70 .47 .66 .37 .23 2 8.4 .31 .44 .53 .64 .70 .50 .62 .35 .25 I 1 9.0 .57 .56 .69 .79 .77 .53 .69 .40 .24 "measured at ground l e v e l > 'measured at 1.3 m TABLE 5. RADIAL GROWTH AT 0 AND 1. 3m FOR THE 72! RED ALDER SAMPLE TREES - Rings from p i t h -No. Pl o t Section Age 1 2 3 4 5 6 7 8 9 10 disks - Radial growth (cm) -A l l RC 9.2 .22 .38 .71 .56 .76 .79 .66 .53 .48 .08 72 BH 7.9 .22 .33 .63 .51 .69 .69 .63 .48 .38 1 RC 8.7 .13 .30 .84 .86 1.02 1.17 1.07 .91 .22 r 10 BH 7.8 .13 .30 .76 .76 .96 .96 .96 .36 10 2 RC 8.7 .41 .30 .71 .79 .76 .66 .38 .13 .15 10 BH 6.8 .25 .30 .71 .71 .61 .46 .46 10 3 RC 9.0 .25 .56 .91 .58 .84 .89 .76 .56 .36 10 BH 7.9 .23 .46 .69 .53 .74 .79 .69 .41 10 4 RC 8.6 .21 .30 .51 .30 .58 .51 .43 .33 .18 10 BH 7.0 .21 .30 .51 . 30 .55 .49 .38 .25 10 5 RC 9.2 .15 .30 .55 .43 .76 .79 .66 .51 .43 .03 10 BH 7.9 .15 .25 .49 .40 .63 .74 .58 .38 10 6 RC 10.0 .25 .38 .74 .53 .73 .83 .74 .81 .94 .41 10 BH 9.0 .23 .38 .63 .49 .63 .80 .74 .74 .53 10 9 RC 9.7 .30 .38 .69 .49 .74 .69 .38 .51 .60 .12 10 BH 8.5 .30 .36 .66 .46 .69 .63 .51 .41 .25 10 10 RC 10.0 .49 .53 .69 .43 .66 .69 .43 .53 .60 .07 3 BH 9.0 .38 .40 .58 .43 .61 .55 .16 .58 .28 3 CJ RC = ground l e v e l o BH = 1.3 m. 31. TABLE 6. SUMMARY STATISTICS FOR THE 20 RED ALDER BRANCH-PRODUCTION-SAMPLE-TREES A. Tree Parameters Branch Branch Sexual "I biomass NPP parts red dbh ht dblc h l c hdc cw (g) (g) (g) (cm) (cm) (m) (cm) (m) (m) (m) X 1593.5 610.1 74.4 8.23 6.31 8.77 4.45 5.18 3.84 2.05 SD 1473.0 565.2 178.6 3.34 2.60 2.18 1.91 2.05 2.93 0.73 sx 329.4 126.4 39.9 0.75 0.58 0.49 0.43 0.46 0.65 0.16 cv 92.4 92.6 24.0 40.6 41.2 41.2 43.0 39.5 76.4 35.5 B. Percentage D i s t r i b u t i o n of Branch Biomass by Age Class Age Class Percent Total Current twigs 24.7 1st yr branches 2.5 2nd yr branches 7.1 3rd yr branches 40.1 4th yr branches 22.2 5th yr branches 3.4-dblc = diam.'base l i v e crown. 32. numerous and constituted only 2.5 percent. The greater proportion of 2nd year branches were current twigs which accounts for the apparently low 7.1 percent. Third year branches, however, constituted 40.1 percent of t o t a l biomass. C h a r a c t e r i s t i c a l l y , alder displays a high branch angle to the stem (Scott et a l . i n press) which allows 3rd, and to a lesser extent 4th year branches (22.2 percent branch biomass) to survive. After 4 years l i g h t extinction i s severe; only 3.4 percent of branches remained a l i v e at 5 years. The r a t i o of branch production to branch biomass was 0.383 ± .110 (X±Sx) with a c o e f f i c i e n t of v a r i a t i o n (CV) of 28.7 percent. The equation used to predict branch production based on the 20 branch-sample^trees was: (x) . . . Y • 0.34124 + 0.0760293'Xl - 0.643049«X2 R 2 = 0.954, SE(% of Y)=19, N=20 Y±Sy = .610±.126 Kg where Y = branch production i n 1976 (Kg's) XI • r 2h/100 X2 = height to l i v e crown (hlc) The corrections for height growth and r o o t - c o l l a r growth between June-July 1976 and February 1977 were 3.3 percent and 3.1 percent respectively. 33. (b) Deriving Regressions from the Master Table Table 7 gives the f i n a l master table and Appendix III l i s t s the simple c o r r e l a t i o n c o e f f i c i e n t s . General Because the estimation procedure i s of fundamental importance i t i s appropriate to discuss some of the pros and cons of the various a l t e r n a t i v e s . Since Kittredge_ (1944), logarithmic regression equations have been widely used to predict the growth of trees and f o r e s t s . Logarithmic transformation reduces b i o l o g i c a l v a r i a b i l i t y so that the assumptions of regression analysis may be met. This w i l l be e s p e c i a l l y important for forests i n which dimensional v a r i a b i l i t y i s large (Whittaker and Marks 1975). In even-aged, evenly-spaced plantations, regression techniques may be rejected i n favour of the "mean-tree" approach i n which the biomass of the average tree per stand i s m u l t i p l i e d by the number of trees i n the stand. However, the use of d i f f e r e n t dimensions leads to the choice of d i f f e r e n t trees as "average," since a tree of average dbh may not be a tree of average height or crown length etc. ( A t t w i l l and Ovington 1968). Moreover, t h i s method gives l i t t l e extra stand information (Crow 1971). If regression techniques are applied to f a i r l y uniform stands then the use of logarithmic transformation may be unnecessary and hyperbolic (Ogawa et al.1965) or arithmetic approaches TABLE 7. MASTER TABLE RED ALDER SAMPLE-TREE STATISTICS SUMMARY N = 72 Mean Measurement X SD Min. Max. C.V. Red; (ob) cm 11.39 3.22 6.23 20.83 28.3 Dbh (ob) cm 8.66 2.38 4.83 17.53 27.5 CW (m) 2.89 0.68 1.83 4.57 23.4 Ht (m) 9.57 1.91 5.64 13.26 19.9 CD (m) 5.26 1.97 1.06 9.60 37.4 D3 , (cm) 4.44 2.26 1.02 10.41 50.8 Hdc (m) 1.41 1.08 0.00 3.96 76.8 Biomass (dry Kg/ha) Stem wood 11.13 7.13 2.22 39.67 64.0 Stem bark 1.87 1.11 0.46 7.19 59.4: Branches 4.55 4.45 0.48 31.88 99.3 small 1.55 1.87 0.04 14.85 120.8 medium 2.02 1.52 0.00 10.97 75.1 large 0.98 2.00 0.00 15.41 204.9 Leaves 1.77 1.34 3.74 7.27 75.6 Reproductive structures 0.13 0.17 0.0 0.84 130.2 Total bole 13.01 8.21 2. 75 48.89 63.1 Total orovm 6.45 5.73 1.24 39.9 88.8 Grand Total 19.46 13.01 4. 74 86.02 67.6 Current P r o d u c t i v i t y (dry Kg/ha/yr) Stem wood 2.81 1.67 6.62 8.37 59.4 Stem bark 0.28 0.17 0.07 1.08 59.4 Branches 1.29 0.83 2.41 4.82 64.6 Leaves 1.77 1.34 3.74 7.27 75.6 Reproductive structures 0.13 0.17 0.00 0.84 130.2 Total bole 3.09 1.84 0. 74 9.45 59.0 Total orown 3.06 2.03 0.90 12.10 66.5 Grand Total 6.28 3.86 1. 79 22.37 61.4 35. (Ovington et a l . 1967, Post 1970, Crow 1971) more appropriate. In addition, converting log estimates i n t o meaningful arithmetic units introduces serious errors (Zar 1968, Madgwick 1970, Beauchamp and Olson 1973), the corrections f o r which are s t i l l i n dispute (Baskerville 1972, Munro 1974). Wood and bark biomass Thus arithmetic, common logarithmic and multiple and simple l i n e a r regression models were tested, separately for stem wood and bark. Table 8 l i s t s the a l t e r n a t i v e s i g n i f i c a n t regression equation independent variables and descriptive s t a t i s t i c s , and Appendix III gives the formulae for transforming logarithmic and hyperbolic into arithmetic units. The logarithmic equations gave only a n e g l i g i b l y smaller SE e than the arithmetic equations, whereas hyperbolic transformation resulted i n a s u b s t a n t i a l l y increased SE e« Thus, to avoid the mistakes introduced when back-transforming logarithmic equations, the arithmetic equations were chosen. 2 2 The combination of d h/100, r h/100 was best for stem wood biomass but e s s e n t i a l l y too complex. Dropping h from the equation resulted i n only a small increase i n the SE 2 2 and decrease i n R . The independent variable d h/100 was 2 highly correlated to the stem bark biomass, whereas r h/100 was not s i g n i f i c a n t . To make the equations additive (Kozak 2 2 1970) both r h/100 and d h/100 were selected to predict stem TABLE 8. POTENTIAL REGRESSION EQUATIONS FOR RED ALDER BOLE BIOMASS N=72 A. BOLE WOOD BIOMASS Independent variables 2 2 d h, r h, h 2 2 d h,r h r 2 h T,2 2 R or r .979 .973 .949 SE or SE^ (Kg) E 1.058 1.182 1.622 2 2 log r h, log d h log d 2h log red, log dbh, log h log dbh, log h log dbh .981 .972 .984 .978 .932 1.157 1.563 1.046 1.382 2.495 l/,2, 1/ . d h, cd /d h .969 .968 2.011 1.292 BOLE BARK BIOMASS 2 2 1 d^h, r h d 2h, dbh d 2h .947 ,954 .943 .259 .241 .267 log dbh, log h log dbh log d 2h .945 .933 .942 .239 .241 .263 V d 2 h .926 .428 Note: P a r t i a l F-value i n s i g n i f i c a n t 2 2 2 d h and r h are divided by 100 Dependent variable(s) i n dry Kg's, diameters i n cm, a l l other measurements i n metres. 32. and stem bark biomass; the r e s u l t i n g equations can be found i n Table 9. Wood and bark production 2 2 To again achieve a d d i t i v i t y r h/100 and d h/100 were used to predict stem wood and bark production and proved to be highly s i g n i f i c a n t (see Table 9). Multiple-covariance analysis Multiple-covariance analysis revealed s i g n i f i c a n t differences between crowded and uncrowded groups f o r a l l but stem wood production (see Appendix IV). When s i g n i f i c a n t l y d i f f e r e n t , separate multiple l i n e a r equations were computed for each group. Because multiple regression r e l a t i o n s h i p between the dependent and independent variables i s a regression surface, p i c t o r i a l presentation of the data must be multi-dimensional. As t h i s d i f f i c u l t y has been side-stepped or ignored i n previous studies a computer programme was written to present graphically the regression surface and scatter of observed data (see Appendix V). Figures 2 to 9 show these r e l a t i o n s h i p s , separately for the crowded and uncrowded groups. Within each group the Y axis i s held constant so that the bark and wood are d i r e c t l y comparable. Notice that the Y axis i s much greater for the uncrowded stands due to the larger tree s i z e . The r e l a t i v e contribution of the independent variables i s at o 38. once e v i d e n t — f o r biomass d^h/100 i s more important and 2 for production r /100 i s more important. The regression equation at the base of each figure was the one used to predict t o t a l stand biomass and production for the crowded and uncrowded main-plots. 3 9 . TABLE 9. ESTIMATING EQUATIONS FOR RED ALDER BOLE BIOMASS AND PRODUCTIVITY N = 72 2 Dependent v a r i a h l p Intercept Regression Coefficients R SE(% of Y) (Kg) by Independent Variable R2H/100 D2H/100 Wood biomass 1.31625 + 0.346084 + 0.573351 .973 10.6 Bark biomass 0.370339 + 0.0227208 + 0.140593 .947 13.8 Wood and bark l m 6 Q 6 5 B 9 + 0.3688048 + 0.713944 .977 9.8 biomass Wood production 0.568826 + 0.10849 + 0.0801757 .929 16.0 Bark production 0.556119 + 0.0039432 + 0.02111046 .947 13.8 Wood and bark l . i 2 4945 + 0.1124332 + 0.1012803 .941 14.5 production Note: Dependent variable(s) i n dry Kg's, diameters i n cm, a l l other measurements i n metres. 40. 3 THREE DIMENSIONAL RELATIONSHIP BETWEEN STEM WOOD BIOMRSS RND BIOMASS INDICES FOR 8 TO 10 YR RED ALDER SAMPLE TREES IN CROWDED CONDITIONS DIAMETERS IN CM.HEIGHT IN M T=.729Z3Z*. 135Z61XD+1.0D4WXZ] . R2=.963 SE=.70BKG N=40 X=OBSERVEO DflTfl POINTS RCD=RDDT COLLRR 01RM I=L1NE JOINING OBSERVED DflTH RND REGRESSION SURFRCE FIGURE'-'3 THREE DIMENSIONAL RELATIONSHIP BETWEEN STEM BARK BIOMASS AND BIOMASS INDICES FOR B TO 10 YR RED ALDER SAMPLE TREES IN CROWDED CONDITIONS DIAMETERS IN CM.HEIGHT IN M T=.Z112B6+.D22926lXm.1734691X2) . RZ=.B99 5E=.209KG N-40 X-OBSERVED DATA POINTS RCD=R0OT COLLAR 01AM I =L1NE JOINING OBSERVED DATA AND REGRESSION SURFACE 42. to fM THREE DIMENSIONAL RELATIONSHIP BETWEEN STEM WOOD BIOMASS AND BIOMASS INDICES FOR B TO 10 YR RED ALDER SAMPLE TREES IN UNCROWDED CONDITIONS DIAMETERS IN CM.HEIGHT IN M Y=2.B3331t.3ZZ3378(Xn + .51BZ]4IXZ] . RZ=.356 SE=1.415KG N=32 X=OBSERVEO DATA POINTS RCD=ROOT COLLAR DIAM „_„„_ I =L1NE JOINING OBSERVED DATA AND REGRESSION SURFACE 43. THREE DIMENSIONAL RELATIONSHIP BETWEEN STEM BARK BIOMASS AND BIOMASS INDICES FOR B TO 10 YR RED ALDER SAMPLE TREES IN UNCROWDED CONDITIONS DIAMETERS JN CM.HEIGHT JN M r=.4B6164f.0Z0BB15IXl)O346n IXZ) . RZ=.9Z8 SE=.Z97KG N=3Z X=0B5ERVED DATA POINTS RCO-ROOT COLLAR DIAM I =LINE JOINING OBSERVED DATA AND REGRESSION SURFACE 44. 1 ^ J THREE DIMENSIONAL RELATIONSHIP BETWEEN CURRENT STEM WOOD PRODUCTION RND PRODUCTION INDICES FOR 8 TO 10 YR RED RLDER SRMPLE TREES IN UNCROWDED CONDITIONS DIAMETERS IN CM.HEIGHT IN H Y=».36BBZ6+.]OB491X1) + .OBO]757(XZ). RZ=.9Z9 SE».451KG N»72 X=DBSERVED DATA POINTS RCD=ROOT COLLAR DIAM INLINE JOINING OBSERVED DATA AND REGRESSION SURFACE FIGURE: 1  5UUn^' THREE 0IMEN5I0NRL RELATIONSHIP BETWEEN CURRENT STEM BARK PRODUCTION AND PRODUCTION INDICES FOR B TO 10 YR RED ALDER SAMPLE TREES IN UNCROWDED CONDITIONS DIAMETERS IN CM .HEIGHT IN M Y=.073077*.00311761XD + .020231X2) . RZ=.9ZB SE=.045KG N»3Z X=OBSERVE0 OATA POINTS RC0=R0QT COLLAR 01AM I =LJNE JOINING 0B5ERVED DATA AND REGRESSION SURFACE 46. 3 THREE-DIMENSIONAL RELATIONSHIP BETWEEN CURRENT STEM WOOD PRODUCTION AND PRODUCTION INDICES FDR 8 TO 10 YR RED ALDER SAMPLE TREES IN CROWDED CONDITIONS DIAMETERS IN CM.HEIGHT IN M Y=.36BBZ6+.)OB49lX])+.OBO]757lXZ) . RZ=.9Z9 Se=.431KG N»7Z X=OB5ERVED DRTH POINTS RCO=ROOT COLLAR 01AM l=LINE JOINING OBSERVED OATH AND REGRESSION SURFACE 47. / FIGURE: , 9 THREE DIMENSIONAL RELATIONSHIP BETWEEN CURRENT STEM BARK PRODUCTION AND PRODUCTION INDICES FOR B TO 10 YR RED ALDER SAMPLE TREES IN CROWDED CONDITIONS DIAMETERS IN CM.HEIGHT IN M Y=.03]6973*.003420BtXn*.0260534lXZ) . RZ=.B99 5E=.031KG N=40 X=OB5ERVED DATA POINTS RCD=RDOT COLLAR DIAM I =L1NE JOINING OBSERVED DATA AND REGRESSION SURFACE VIZ or U3 o T. CD CC a 48. Crown equations Because of the highly variable nature of crown biomass, data for 6 of the sample-trees were rejected as " o u t l i e r s " (>3 SD from the regression slope). The simple c o r r e l a t i o n c o e f f i c i e n t s can be found i n Appendix I I I . Crown biomass Separate multiple regressions were run for t o t a l crown, leaf and branch biomass. The following independent variables were considered: r 2h/100, d 2h/100, (r 2h/100) 2, (d 2h/100) 2, h l c , rcdxht, 2 2 dbhxht, red , dbh , ht/cw, cd/cw, cdxcw, redxed, dbhxcd, 2 cw x cd, cw. Table 10 l i s t s the a l t e r n a t i v e s i g n i f i c a n t multiple regression equations. Although the elimination procedure may not give the s t a t i s t i c a l l y perfect combination, i t at least provides a r a t i o n a l basis for the f i n a l choice. To ensure a d d i t i v i t y the independent variables that occurred most commonly were chosen. For t o t a l crown and leaf biomass, 2 d h/100 was the single most important independent v a r i a b l e . For branch biomass, red x cd was the major component? Cle a r l y , retention of a crown variable i n the equation i s b i o l o g i c a l l y r a t i o n a l , and, on the basis of the data i n Table 10, s t a t i s t i c a l l y reasonable. The crown-shape r a t i o , cd/cw 49. TABLE 10. POTENTIAL REGRESSIONS FOR CROWN BIOMASS AND PRODUCTION N=66 -TOTAL CROWN BIOMASS (includes reproductive organs) Intercept d 2h/100 hl c cd/cw 2 R or SE e regression c o e f f i c i e n t s . 2 r • % of Y 5.7003 + 0.74543 0.766703 - 1.432 .760 22.6 1.71535 + 0.661244 0.322507 .720 32.2 1.0441 + 0.565001 .689 33.6 BRANCH BIOMASS Intercept red: x:cd cd/cw d 2h/100 regression c o e f f i c i e n t s 1.70161 + 0.0544975 0.13309 + 0.185928 .760 32.2 2.97956 + 0.0845678 - 2.17132 .723 34.4 0.558951 + 0.0559838 .407 49.9 LEAF BIOMASS Intercept d 2h/100 ht/cw dbh x cw regression c o e f f i c i e n t s 1.11232 + 0.117303 - 0.241182 + 0.00733759 .704 28.3 1.23674 + 0.13580 - 0.225517 .680 29.3 0.512363 + 0.129765 .639 30.8 Note: A l l independent variables s i g n i f i c a n t (a = 0.05) Dependent v a r i a b l e i n dry Kg's, diameters i n cm, a l l other measurements i n metres. 50. The crown-shape r a t i o , cd/cw featured i n both t o t a l crown and branch biomass, but was replaced by the tree height to crown width r a t i o (ht/cw) for le a f biomass. In a l l cases the simple l i n e a r regression was s t a t i s t i c a l l y i n f e r i o r to the multiple regression. The equation incorporating a 2 stem volume (d h/100) and a crown component (cd/cw) was selected. Resultant equations are i n Table 11. Crown production To make the equations additive, crown production regressions were based on the same independent variables as crown biomass and proved to be s i g n i f i c a n t (see Table 11). Multiple-covariance analysis and conditioning tests Multiple-covariance analysis between crowded and uncrowded sample trees revealed s i g n i f i c a n t differences i n the l e a f biomass-(see Appendix IV). Because of a negative intercept i n the branch production equation, maximum regression models were tested against conditioned regression models with intercepts set at zero. Table 12 shows that the maximum and conditioned equations d i f f e r e d at the 0.05 l e v e l for l e a f biomass i n the uncrowded group alone, but were the same at the 0.01 l e v e l . Thus, on the basis of the generally i n s i g n i f i c a n t difference between conditioned and maximum models, conditioned regressions were used to predict main-plot crown biomass and production. 51. TABLE 11. ESTIMATING EQUATIONS FOR RED ALDER CROWN BIOMASS AND PRODUCTIVITY N=66 Dependant v a r i a b l e Regression C o e f f i c i e n t s (Kg) Intercept by Independent Variables D H/100 CD/CW Total crown biomass 0.940575 + 0.566637 + 0.0484421 Branch biomass 0.429308 + 0.422831 + 0.0487709 Leaf biomass 0.487593 + 0.130159 + 0.01159 Tot a l crown NPP 0.445762 + 0.269168 + 0.104485 Branch NPP -0.418282 + 0.139012 + 0.0928939 R SE(% of Y) .689 .675 .639 .825 .851 .33.9 37.3 31.1 21.7 23.0 Note: Dependent variable(s) i n Kg's, diameters i n cm, a l l other measurements i n metres. 52. The regression surfaces, equations and scatter of observed data for the crowded and uncrowded sample trees are presented i n Figures 10 to 15. The graphs show the small contribution of the cd/cw variable which i s s i g n i f i c a n t only i n the branch production equation. The observed data are much more scattered about the regression surface than are the observations for the bole. The three-dimensional graphs are necessitated by the two independent variable multiple-regression equations. I t was f e l t that these graphs gave much more information than conventional methods of data presentation. TABLE 12. DIFFERENCES BETWEEN THE MAXIMUM AND CONDITIONED MODELS FOR RED ALDER CROWN COMPONENTS Equation Model DF SS MS . F Branches Conditioned 14 126.92684 Maximum 63 125.97984 1.99968 .474 NS Difference 1 .9488 .9488 Leaves Conditioned 27 7.085637 (uncrowded) Maximum 26 6.942494 .267019 .536 NS Difference 1 .143143 .143143 Leaves Conditioned 35 . 4.84813 (crowded) Maximum 34 4.222154 .124181 5.04 * Difference 1 .625975 .625976 Branch NPP Conditioned 64 4.83632 Maximum 63 4.827312 .076624 .118 NS Difference 1 .009008 .009008 NS = not s i g n i f i c a n t l y d i f f e r e n t * = s i g n i f i c a n t l y d i f f e r e n t a = 0.05 54. THREE DIMEN5I0NAL RELATIONSHIP BETWEEN BRRNCH BIOMRSS AND BIDMRSS INDICES FDR B TO ID YR RED ALDER SAMPLE TREES IN UNCROWDED CONDITIONS DlflMETER.5 IN CM.HEIGHT.DEPTH AND WIDTH IN M V=.439ZBaiX]) + .0ZZ6372lXZ) . RZ=.B7Z 5E=1 .4DBKG N=SB X=OB5ERVED DATA POINTS l=LINE JOINING OBSERVED DATA AND REGRESSION SURFACE 55. THREE DIMENSIONAL RELATIONSHIP BETWEEN LEAF BIOMASS RND BIOMASS INDICES FOR B TO 10 YR RED RLDER SAMPLE TREES I N UNCROWDED CONDITIONS DIAMETERS IN CM.HEIGHT.DEPTH RND WIDTH IN M T=.J45033lxm.)Z772HXZ) . RZ=.-q79 SE=.5]ZKG N=Z9 X=OB5ERVED DflTfl POINTS I -LINE JOINING OBSERVED DflTfl RND REGRESSION SURFACE FIGURE: 12 "*y*-lOBH ' THREE DIMENSIONAL RELATIONSHIP BETWEEN CURRENT BRANCH PRODUCTION AND PRODUCTION INDICES FOR B TO 10 YR RED ALDER SAMPLE TREES IN UNCROWDED CONDITIONS DIAMETERS JN CM.HEiGHT.DEPTH RND WIDTH IN M T=.1374081X1) + .07B95J91X2). R2=.BS0 SE=.Z75KG N=6B X-0B5ERVED DATA POINTS . . . . . I - L I N E JOINING OBSERVED DATA AND REGRESSION SURFACE 3: (-0 a oit-9 a " a FIGURE: 13. ^ b THREE DIMENSIONRL RELATIONSHIP BETWEEN BRANCH BIOMRSS RND BIOMASS INDICES FOR 8 TO 10 YR RED RLDER SAMPLE TREES IN CROWDED CONDITIONS D1RHETER5 IN CM.HEIGHT.DEPTH RND WIDTH IN H T - . 4 3 9 Z B 8 ( X l ) f . 0 2 Z 6 3 1 Z l X Z ] . RZ=.B7Z SE-1.40BKG N»Ofl X=08SEKVED DRTR POINTS I =L1NE JOINING OBSERVED DflTfl RND REGRESSION SURFACE 58. THREE DIMENSIONAL RELATIONSHIP BETWEEN LEAF BIOMASS AND BIOMASS INDICES FOR 8 TO 10 YR RED ALDER SAMPLE TREES IN CROWDED CONDITIONS DIAMETERS IN CM.HEIGHT.DEPTH RND WIDTH IN H T=.239145IX))+.02Z637ZIXZ). R2=.706 5£=.368KG N=37 X=OBSERVED DATA POINTS l=L]NE JOINING OBSERVED DATA AND REGRESSION SURFACE 59. m Gcc CD 12 UJ 3 OX C3 •7 , ^ **** FIGURE: 15 ^ / THREE DIMENSIONRL RELATIONSHIP BETWEEN CURRENT BRANCH PRODUCTION AND PRODUCTION INDICES FOR B TO 10 YR RED ALDER SAMPLE TREES IN CROWDED CONDITIONS DIAMETERS IN CM.HEIGHT.DEPTH AND WIDTH IN H T=. 13740BIX])*.07695191X2) . R2=.B50 5£=.275KG N=66 X=OS5ERV£D DRTA POINTS l = U N E JOINING OBSERVED DflTfl RND REGRESSION SURFRCE i2Y APPLICATION TO STAND Table 13 summarizes the data for a l l 8 plots obtained by applying the sample tree regression equations to a l l the median trees and multiplying by the number of 2 l i v e stems i n each 4m sub-plot. The table ranks the data by density and s i t e : the l e a s t dense and good si t e s to the l e f t and the most dense and poor s i t e s to the r i g h t . &a) Tree Measurements The number of l i v e stems ranged from 8,204 to 42,971 stems per hectare (sph) but decreased to 13,047 sph on the poorest p l o t r e f l e c t i n g among other factors, a lower s i t e capacity and differences i n seed a v a i l a b i l i t y and germination. The number of standing dead ranged from 5,239 to 16,729 sph and p a r a l l e l e d the increase i n stand density. Root-collar diameter, dbh, cw and height a l l decreased with increasing stand density. Figure 16 shows the frequency d i s t r i b u t i o n s of red, dbh and height classes for the median trees. The d i s t r i b u t i o n s are skewed, with more small trees and few large trees. Figure 17 compares paired dense and less dense p l o t s . The denser plots are characterized by higher and narrower, more peaked and less variable d i s t r i b u t i o n s . (b) Biomass Above-ground biomass averaged 82 mfc/ha. This gives a mean annual productivity of 9 mt/ha/yr which i s considerably less than the maximum estimates of Smith (1973) TABLE 13 . MEAN MEASUREMENTS, ABOVE GROUND BIOMASS AND NET PRODUCTION FOR 8-10 YR RED ALDER BY 0.04 HA PLOTS Mean Measurements - P l o t s ranked by d e n s i t y and s i t e -P l o t # 1 6 3 10 5 4 9 2 X Sx # l i v e s t e m s / h a 8 ,204 8,871 9 ,983 15,790 22,264 42,971 17,025 13,047 17,103 + 948 # dead s t e m s / h a 5 ,239 3,435 9,142 11,737 16,729 16,729 6,079 1,169 7,169 + 274 S i t e c l a s s G G G M M M-P P P M Red (cm) 8 .3 6 .8 5 .3 5 .6 4 .75 3.4 4 .6 4 .5 5.4 + .084 Dbh (cm) 6 .0 5 .5 4 .4 4 .6 3.5 2 .6 3.6 3.4 4 .2 + .065 CW (m) 3.2 2 .0 2.1 1.9 1.6 1.1 1.4 1.6 1.9 + .031 L i v e : D e a d r a t i o 1.6 2 .6 1.1 1.3 1.3 2.6 2.8 11.6 2.4 + 1.2 H l c (m) 5 .5 4 .9 4 .8 5.0 3.0 3.2 3.2 2.1 4 .0 + .072 Ht (m) 9 . 9 9 .4 9 .4 8.1 7.4 6.1 6.1 5 .6 7.8 + .465 BA (m 2 /ha) 25 .6 26.0 17 .8 23.5 19.0.1. 20.48 20.2 10.76 19.6 + .680 Biomass (dry Kg/ha) T o t a l 96 ,922 92,517 67 ,631 112,027 82 ,883 106,883 58,372 39,640 82,066 ± 1,839 Stem 62,347 57,124 42,817 73,016 42,902 54,528 32,134 21,926 48,349 ± 1,132 Stem bark 10,028 9,603 7,291 12,381 9,290 13,070 6,990 4,892 9,193 + 195 L e a f 6 ,579 7,325 5 ,230 7,961 6,672 7,083 4,083 3,032 6,070 ± 81 Branches 17,572 18,058 12,022 18,258 23,305 30,710 14,332 9,484 17,968 ± 440 R e p r o d u c t i v e o rgans 396 407 271 411 714 942 439 306 486 ± 12 C u r r e n t P r o d u c t i v i t y (dry K g / h a / y r ) T o t a l 28,737 28,015 20,029 32,315 35,952 40,831 25,125 17,802 28,601 + 650 Stem 14,531 12,793 9,301 15,803 18,701 19,347 13,863 10,134 14,309 + 343 Stem bark 1,505 1,442 1,096 1,860 1,393 1,960 1,049 733 1,380 + 29 L e a f 6 ,579 7,324 5,230 7,961 6,672 7,083 4 ,677 3,032 6,070 + 81 Branches 5,725 6,049 4,131 6,280 8,472 11,097 5,097 3,597 6,356 + 158 R e p r o d u c t i v e organs 396 407 271 411 714 942 439 306 486 + 12 Note : S i t e C l a s s G - Over 27m a t 50 y r s ; M - 18-27m a t 50 y r s ; P - Below 18m a t 50 y r s . (based on W o r t h i n g t o n e t a l . (1960) . Red r o o t c o l l a r d i a m . , CW = crown w i d t h , H l c = h e i g h t t o l i v e c rown. 62. F I G U R E : 1 6 F R E Q U E N C Y D I S T R I B U T I O N OF M E D I R N R L D E R P E R . 0 0 0 4 HR S U B P L O T BY R O O T - C O L L R R D I R M E T E R . B R E R S T - H E I G H T D I A M E T E R RND H E I G H T C L R S S R V E R R G E R L L 8 P L O T S N = 7 7 9 =1CM D B H C L R S S =1CM RCD C L R S S =1M H E I G H T C L R S S DBH(CM). RCDCCM) RND HEIGHT CM) CLRSSES 63. Figure 17: FREQUENCY DISTRIBUTION OF MEDIAN ALDER PER .0004 HA SUB-PLOT BY ROOT-COLLAR DIAMETER, BREAST-HEIGHT DIAMETER AND HEIGHT CLASS FOR EACH PLOT. 64. FlOJREilTF P10I.5 11.97 CDOVOED COlOITIIMS •ICIf D6H tXBSJ •icn RCO oust •IN HEIGHT OflSf ODMICMJ. RC01CH1 fiNO HEIGHIIN) CLASSES Figure 17 (Cont'd): FREQUENCY DISTRIBUTION OF MEDIAN ALDER PER .0004 HA SUB-PLOT BY ROOT-COLLAR DIAMETER, BREAST-HEIGHT DIAMETER AND HEIGHT CLASS FOR EACH PLOT. 65. and DeBell (1972) for 8 to 10 yr alder based on 4m plots of 64 mt/ha/yr and 20 mt/ha/yr, respectively. But i t i s greater than the r e s u l t s of Zavitkovski and Stevens (1972) 2 for 10 yr alder based on 50m plots of 5 mt/ha/yr. The average d i s t r i b u t i o n of biomass was 59 percent stem wood, 11 percent stem bark, 7 percent leaves, 22 percent branches and 1 percent reproductive parts. The large appropriation of biomass to branches indicates the strategy alder adopts i n gaining competitive advantages: not only must the t a c t i c s be for maximum v e r t i c a l growth but also for e f f e c t i v e domination of canopy space. Unexpectedly the denser stands were characterized by greater proportions of branch biomass than the less dense stands. Since expression of height growth i s r e s t r i c t e d by the large number of intensely competitive trees under dense conditions, more of the i n t e r - t r e e struggle i s v i a branch competition. This process i s f a c i l i t a t e d by the a b i l i t y of alder to grow branches at acute angles to the stem under dense conditions and to tole r a t e a good deal of branch inter-mingling. Table 14 shows that there are more smaller branches i n the denser p l o t s . In the less dense plots the treesr^ere more "open grown" with reduced branch competition, a greater v e r t i c a l branch angle and generally older, larger branches, (c) Production The estimate of current above-ground net primary TABLE 14. PROPORTION OF BRANCH SIZE CLASSES AND REPRODUCTIVE PARTS FOR RED ALDER SAMPLE-TREES IN CROWDED AND UNCROWDED STANDS A. Branches Ratio SX 1. Crowded small .387 + .044 n=-36 medium .561 + .090 large .052 + .041 2. Uncrowded small .335 + .050 n=29 medium .446 + .070 large .218 + .096 Reproductive Parts 1. Crowded .031 + .009 2. Uncrowded .023 + .013 67. production was a combination of the average annual stem production i n 1974 and 1975 and crown production for 1976. The l e a f production estimate assumes that peak leaf biomass occurred i n l a t e June and early July. The average net primary productivity was 28,601 Kg/ ha/yr of which 59 percent was stem wood, 11 percent stem bark, 7 percent leaves, 22 percent branches and 1 percent sexual parts. The statement that alder i s one of*the most productive cool-temperate hardwood species i s based on the following ranges for above-ground productivity: 9,000-15,000 Kg/ha/yr (Westlake 1963), 3,000-22,200 Kg/ha/yr (Art and Marks 1971), 6,000-25,000 Kg/ha/yr (Whittaker and Likens 1975) and 7,960-24,000 Kg/ha/yr (Whittaker and Marks 1975). Zavitkovski and Stevens (1972) also recorded a high above-ground net primary productivity of 22,200 Kg/ha/yr fo r alder between 10 and 15 yrs. But i s i s not known whether t h i s i s a t r u l y representative figure because t h e i r data were based partly on leaf l i t t e r f a l l which probably underestimates leaf production, and did not cover a range of densities within f u l l y stocked conditions. Production i n the U.B.C. plots was greater i n the denser stands, though cumulative biomass was s i m i l a r i n the less dense stands which suggests that intense competition i n the crowded conditions w i l l delay the i n f l e c t i o n point for productivity. The net primary production estimate makes no correction 68. for insect consumption and mortality loss during the growing season and i s therefore thought to be an underestimate. Both corrections are extremely time-consuming; the corrections f o r herbivory may be less than the errors i n the estimation of production (Hughes 1971). 69. (3) LESSER VEGETATION The above-ground lesser vegetation estimates were based on the terminal biomass which i s the dry weight of a l l plants i n a p l o t harvested at the same time, usually when the ent i r e complex reaches maximum biomass late i n the growing season (Odum 1960). In d i s t i n c t i o n , cumulative biomass i s the sum of weights of the i n d i v i d u a l species each harvested at t h e i r maximum. The terminal biomass w i l l thus underestimate, or i n the case of monoculture, equal the cumulative biomass (Odum 1960). The c o e f f i c i e n t s of v a r i a t i o n of 169 percent f o r biomass and 138 percent f o r production indicate that quadrat sizes were 2 perhaps too small (%m ) and too few i n number (3 per plot) to adequately account f o r the ranges i n dry weight. However, more intense sampling was l i m i t e d by time constraints. The average above-ground (or top) terminal biomass of the ground vegetation was 1255 Kg/ha and annual top production 590 Kg/ha/yr (see Table 15). This was equivalent to 1.5 percent of the overstorey biomass and 2 percent of the overstorey production. This top terminal biomass r e s u l t compares with those by Zavitkovski (1976) fo r early successional temperate hardwood understoreys of 1720 Kg/ha and of Henderson (1970) for 10 yr old red alder of 1000 Kg/ha. Despite the small contribution of ground vegetation to the t o t a l ecosystem biomass, i t plays an important role i n organic TABLE 15 . UNDERSTOREY ABOVE-GROUND BIOMASS, NET PRODUCTION AND LIGHT PENETRATION FOR 8-10 YR RED ALDER - P l o t s ranked by d e n s i t y and s i t e -P l o t # 1 6 3 10 5 4 9 2 Mean Sx CV% # l i v e o v e r s t o r e y s t e m s / h a 8,204 8,871 9,983 15,790 22,264 42,971 17,025 13,047 17,103 S i t e c l a s s G G G M M M-P • P P M L i g h t p e n e t r a t i o n 1 (% f u l l s u n l i g h t ) 6 .0 6 .0 2 .0 3 .0 6 .0 2 .0 2.0 4 . 0 4 . 5 + 2 . 3 U n d e r s t o r e y b iomass (dry Kg/ha) 3,241 1,944 124 296 2,471 583 593 790 1 , 2 5 5 ± 3 9 9 169 P e r c e n t o v e r s t o r e y b iomass 3.0 2 .0 0.1 0 .3 3.0 0 .5 1.0 2 .0 . 1 . 5 U n d e r s t o r e y p r o d u c t i o n 1,374 759 118 144 1,199 397 442 294 5 9 1 ± 1 7 0 138 (dry Kg/ha) P e r c e n t o v e r s t o r e y 5.0 3 .0 0 .5 0.4 3.0 0.1 2.0 2 .0 1 . 0 p r o d u c t i o n ' ' 'L ight p e n e t r a t i o n measured d u r i n g J u l y and August o 71. matter turnover and nutrient c y c l i n g . L i t t e r provided by dead ground vegetation i s r i c h i n important nutrients and rapidly available f o r decomposition (Gagnon et a l . 1958, Zavitkovski 1976). For the plo t s at U.B.C., the understorey contributed an extra 13 percent to the tree l i t t e r f a l l . Furthermore, Gessel and Cole (in press) have shown that ground vegetation i n a 38 year red alder stand accumulates three times more calcium, a t h i r d more phosphorous and a six t h as much nitrogen as the overstorey. The contribution of understorey to nutrient c y c l i n g i n 8 to 10 yr old alder i s probably less than t h i s though of undoubted importance to ecosystem development and i n t e g r i t y . 2 Eighteen species were recorded, averaging 5.6 spp/m . Table 16 ranks understorey biomass by species and shows the importance of the Rubus spp. (80%), e s p e c i a l l y R, s p e o t a b i l i s (61.8%), which i s often found i n association with red alder (Newton et a l . 1968, Franklin and Oyrness 1969, Henderson 1970). Although l i g h t i n t e n s i t y has l i t t l e e f f e c t on the germination of R. s p e o t a b i l i s (Henderson 1970), Table 15 shows that growth increased with increasing l i g h t penetration. I t appears that as the canopy deteriorates i n older stands, R. s p e o t a b i l i s biomass increases. This i s i l l u s t r a t e d by two 25 yr - o l d red alder stands at U.B.C. i n which the above-ground biomass of minor vegetation was 9463+9139 Kg/ha (X±Sx) aiid 5525±2314 (X+Sx) ; of t h i s , 98 percent and 100 percent was R. speotabilis» respectively. Conifer reproduction was present i n a l l stands but amounted to only 1.9 percent of understorey biomass. Most of these were young seedlings which suggests that alder delays considerably the successional replacement by co n i f e r s . The i n h i b i t o r y e f f e c t s of the dense shade on the development of conifers are exacerbated by competition with other lesser vegetation. TABLE 16. PERCENTAGE SPECIES COMPOSITION OF UNDERSTOREY BIOMASS IN 8-10 YR RED ALDER Plot # # l i v e overstorey stems/ha Site class Rubta tspz.cta.biLu> Rubin paAviitoiui Bfiyophytz. i>pp. Rubai usu>inu& HcUlCAAtiUA ip. Gnamminaz &pp. KtkynJum {zJULx.- fizmina. Tana.czX.um nutatti Tiuaa. hzteAophyZZa Gcailthciia. ihaZlon PoZyA&Uchum minimum SaLLx laAtiandna Thuja pLLcata. Sambucui laccmo&a - Plots ranked by density and s i t e - i 1 6 3 10 5 4 9 2 X Avg. 8,204 8,871 9,983 15,790 22,264 42,971 17,025 13,047 G G G M M M-P P P - Percent spp. composition of understorey biomass by plot -77.47 70.35 4.89 18.72 86.48 3.28 51.63 56.09 68.10 9.16 21.16 7.78 7.06 6.28 45.31 30.44 16.45 6.48 2.07 3.95 27.70 1.83 32.36 2.72 4.83 8.14 29.47 12.39 2.68 4.54 94.79 1.58 3.55 2.65 0.70 7.87 2.16 28.97 1.68 0.14 16.98 1.30 2.80 0.90 1.38 1.37 0.53 2.22 0.54 0.01 0.02 0.32 0.13 0.02 0.07 0.07 6.39 0.53 7.78 0.45 Note: Avg. i s based on average of a l l pooled data 74. (4) LITTER FALL AND LITTER ACCUMULATION Table 17 shows that the average l i t t e r f a l l between August and December i s 4454 Kg/ha. Of t h i s , 92.4 percent was leaves (CV=15.6 percent), 6.9 percent branches (CV=36.3 percent) and 0.7 percent reproductive structures (CV=87.5 percent). This r e s u l t l i e s within the ranges c i t e d by Bray and Gorham (1964) for young deciduous temperate forests of 3500 to 5000 Kg/ha. However, i t i s less than the estimate of Zavitkovski and Newton (1971) fo r 10 year old stands of red alder i n western Oregon of 8100 Kg/ha, 70 percent of which was leaves, 28 percent branches and 2 percent catkins. The higher t o t a l and greater proportions of branches and reproductive structures i n t h e i r study r e s u l t s from sampling throughout the year. L i t t e r production showed l i t t l e v a r i a t i o n between plo t s , with a range of from 3019 to 5713 Kg/ha. Generally, once forest canopies have closed, l i t t e r production i s independent of stem density (Bray and Gorham 1964). Although Zavitkovskiand Newton (1971) found that s i t e productivity had l i t t l e e f f e c t on alder l i t t e r - p r o d u c t i o n , there does appear to be a diminution i n p l o t 2, the poorest s i t e studied,» The l e a f - l i t t e r value of 4115 Kg/ha was about 32 percent less than the leaf production regression estimation. There are few studies comparing leaf l i t t e r and leaf production i n the same fo r e s t . Whittaker and Woodwell (1969) TABLE 17. LITTER FALL TOTALS FOR 8-10 YR RED ALDER IN THE FALL OF 1976 - Plots ranked by density and s i t e -P l o t # 1 6 3 10 5 4 9 2 Mean # l i v e overstorey stems/ha 8,204 8,871 9,983 15,790 22,264 42,971 17,025 13,047 17,103 Si t e c l a s s G G G M M M-P P P M L i t t e r f a l l (dry Kg/ha) 4,7.75 4,746 4,790 5,713 4,545 3,514 4,527 3,019 4,454 Sx of l i t t e r f a l l (dry Kg/ha) 311 92 423 330 743 157 214 186 187 Percent underestimation of l e a f production 32 40 39 34 27 54 11 8 32 recorded an underestimation of 28 percent i n an oak-pine forest at Brookhaven, USA. Although they gave no explanation, t h i s presumably r e s u l t s from i n t r i n s i c and e x t r i n s i c changes in leaf mass before l e a f f a l l (Bray and Gorham 1964). I n t r i n s i c changes include r e s p i r a t i o n and translocation of materials from leaf into branch and stem tissues before abscission. E x t r i n s i c changes include herbivory and uneven s e t t l i n g due to wind gusts. In addition, the underestimates i n Table 17 are compounded by lack of measurement of l e a f f a l l before August and aft e r early December. The d a i l y rate of l i t t e r f a l l i s summarized i n Figure 18 for a l l plots and i n Figure 19 for each p l o t . A constant rate was assumed between c o l l e c t i o n dates. The area under the histograms represents cumulative l i t t e r f a l l . On average, over half of the l i t t e r f e l l during November. In plots 1, 2, 3, 4 and 6 the l i t t e r f a l l rate during August and early September was higher than or at least equal to the rate from mid-September to mid-October. This i s due to the shedding of green leaves. A s i m i l a r early peak i n green-leaf f a l l was reported for Alnus glutinasa i n Holland during July (Witkamp and van der D r i f t 1961). This phenomenon was most pronounced i n the less dense plots which suggests that variations i n microclimate are important. For instance, greater i n t e r n a l stand r e s p i r a t i o n within the denser plots would lead to the production of more exothermic 77. FIGURE: 18 DRILY RRTE OF LITTER FALL FOR B TO 10 YR RLDER DURING THE FRLL DF 1976.[RLL B PLDTS1 cr. a: CO CC a cc UJ in uj>n f— (X CC - J i n _J(M £ 5 AUGUST SEPTEMBER OCTOBER NOVEMBER DECEMBER MONTH RND DRY OF COLLECTION 78. FIGUREi 19A ORILY RATE OF LItlER FULL FOR B 10 10 TR ULCER DURING THE FALL DF 1976.(PL01.II 3_ 8 i l e j S § FIGURE* 19B DRILY RRIE OF LITTER FRLL FOR 8 TO 10 YR flLOEB OURING THE FRLL DF 1976.(PL0T.2) HUHJSI SEPTEHOtt OCTOBER KOVEWLR MONTH RND DRY OF COLLECTION ~ i T 1 7. 7l. 1 t. StPTtNBO* OCTOBER NOVEMBER MONTH RND DRY DF COLLECTION FIGURE: 19C DRILY RATE OF LITTER FRLL FOR 8 TO 10 YR RLDER DURING THE FRLL DF 1976.(PL0T.3I FIGURES 19D DRILY RRTE DF LITTER FRLL FOR 8 TO 10 YR RLDER DURING THE FRLL OF 1976. IPLOTM) Si s 5 s 5 AUGUST StPTEHBXR CCTOKJI HOVCntJtR MONTH BNO DAT OF COLLECTION WGU5T KPIEKO DCIMCJT HOVD1SCJI MDNTH AND DRY OF COLLECTION 10. receive* FIGURE 19: DAILY RATE OF LITTER FALL FOR 8 TO 10 YR ALDER DURING THE FALL OF 1976 (FOR EACH PLOT) 79. FIGURE> 19E DRILY RATE OF LITTER FULL FOR B TO 10 YR OLDER DURING THE FALL DF 1976.IPL0T«61 FIGURE* 19F DAILY RATE OF LITTER FALL FDR 8 TO 10 YR RIDER DURING THE FALL OF I97G.IPLDT»SI 9 , 8 I K S er a. B1 SEPTE.iBER OCTOBCJ? HOVEHBER MONTH AND DRY OF COLLECTION AUGUST &EPIEWER OCTOBER MOVEHSEK MONTH RND DAY OF COLLECTION FIGURE: 1*3 DAILY RATE OF LITTER FALL FOR 8 TO 10 YR ALDER DURING THE FALL OF 1976.tPLOT.10) FIGURE: 19H DAILY RATE OF LITTER FALL FOR 8 TO 10 YR BLOER OURING THE FALL OF 1976.tPLOT.91 Si da 5EPTEH3CR OCTOBER NOVEMBER 0ECER5ER MONTH AND DAY OF COLLECTION RUCUST SEPTEMBER OCTOBER NOVEMBER MONTH AND DRY OF COLLECTION 10. OECEMOEH Figure 19 (cont'd): DAILY RATE OF LITTER FALL FOR 8 TO 10 YR ALDER DURING THE FALL OF 1976 (FOR EACH PLOT) 8 0 . energy which would tend to delay the onset of c r i t i c a l temperatures c o n t r o l l i n g leaf abscission. The rapid decline i n l i t t e r f a l l rate at the end of the l a s t c o l l e c t i o n period resulted from incomplete l i t t e r c o l l e c t i o n . Some of the terminal leaves persisted t i l l l a t e December when manpower was unavailable for c o l l e c t i o n . The accumulation of a l l undecomposed l i t t e r on the ground (L horizon) i n early September amounted to 5811.9±910.9 Kg/ha (X±Sx). Zavitkovski and Newton (1971) noted that l i t t e r accumulates rapidly during the f i r s t 5 years a f t e r establishment, reaching an equilibrium around 6 years. After t h i s time, l i t t e r f a l l w i l l approximate l i t t e r decomposition. The r a t i o of l i t t e r accumulation to l i t t e r f a l l of 1.3 on the study s i t e s indicates a high r a t i o of organic matter turnover and energy l i b e r a t i o n (Rodin and B a s i l e v i c 1968). 81. (5) PRODUCTION AND PRODUCTIVITY PARAMETERS Parameters of production and productivity are summarized i n Table 19. The biomass accumulation r a t i o (BAR) expresses the r a t i o of the standing crop to the annual net primary productivity (Whittaker et a l . 1975), and has been used as an index of succession (Whittaker 1966, Woodwell 1967). The study plots showed an average BAR of 2.86 Kg/Kg. Low BAR's and hence early peaks i n productivity are t y p i c a l of early s e r a i species. Table 18 gives the BAR's for a range of highly productive pioneer tree species and compares them with a climax coye-rrforest. Although the 9 year alder at U.B .C. compares favourably with the -most productive of the other c i t e d species, the BAR i s not as low as that recorded for 10 yr alder i n western Oregon of 2.08 Kg/Kg (Zavitkovski and Stevens 1972). The BAR ranges from 3.33 Kg/Kg on the l e a s t dense to 2.61 Kg/Kg on the most dense plots (see Table 19). This implies that the denser stands are more productive r e l a t i v e to t h e i r biomass. The delay i n maximum net primary productivity induced by high i n i t i a l competition i n the dense stands and a l l e v i a t e d by improving s o i l conditions may be p a r t l y responsible. The leaf area index (LAI) refers to the area of leaves per unit area of ground surface and i s a measure of the photosynthetic and hence productive capacity of the fores t -Table 18. ABOVE-GROUND BIOMASS ACCUMULATION RATIOS FOR A RANGE OF FORESTS SPECIES MEAN AGE YRS Acacia mLLu&ijna 4 VlavwA pemylvanica 6 Alnui labia. 9 Alnu& nubia 10 CiyptomeAixi japonica i i Ca&tanopiiA caipidata. 12 Piunai pe.ru> ytvanica 14 Alnui labia 25 LUUode.ndA.on tiatipi^eJia. 2 9 Mature cove-forest 2 2 2 LOCATION BAR Kg/Kg SOURCE Japan 2.28 New Hampshire, USA 2.17 UBC, B.C. 2.86 Western Oregon, USA 2.08 Japan 3.34 2.53 Japan New Hampshire, USA 5.10 Western Oregon, USA 7.00 Gt. Smokey Mts., USA 9.1 Gt. Smokey Mts., USA 45.6 Tadaki 1965 Marks 1971 This study Zavitkovski and Stevens 1972 Tadaki and Kawasaki 1966 Kan et al . 1965 Marks 1971 Zavitkovski and Stevens 1972 Whittaker and Marks 1975 Whittaker and Marks 1975 TABLE 19. PRODUCTION AND PRODUCTIVITY PARAMETERS FOR 8-10 YR RED ALDER ECOSYSTEMS - Plots ranked by density and s i t e -Pl o t # 1 6 3 10 5 4 9 2 Mean # l i v e overstorey stems/ha 8,204 8,871 9,983 15,790 22,264 42,971 17,025 13,047 17,io: S i t e c l a s s G G G M M M-P P P M BAR (Kg/Kg) 3.33 3.28 3.36 3.46 2.30 2.61 2.31 2.23 2.86 LAI (m2/m2) 8.28 9.22 6.59 10.02 8.40 8.92 5.88 3.81 7.64 PLAR (g/m2) 349.0 304.0 304.0 329.0 428.0 458.0 427.0 467.0 374.0 FAE (Kg/Kg) 4.37 3.82 3,83 4.06 5.30 5.76 5.37 5.87 4.90 SCDI (Kg/m3) .98 .98 .72 1.39 1.11 1.74 .96 .71 1.06 Notes BAR = Above ground biomass accumulation r a t i o : (biomass/net primary production) LAI = Leaf area index: (leaf wt/m ) x (surface area/Kg or 12.59 m2/Kg f o r red alder) PLAR = Production to l e a f area r a t i o : (net production (g/m2)/LAI) FAE = Foliage a s s i m i l a t i o n e f f i c i e n c y : (net production/leaf weight) SCDI = Standing crop density index: (standing biomass (Kg/m2)/av. ht. standing crop (m)) oo LO 84. community. The average of 7.64 m*/m^  obtained i s high for temperate deciduous forests which generally l i e within the 2 2 range of 4 to 6 m /m (Whittaker 1966). For example, a pioneer species i n eastern USA, Prunus pensylvanica L. had 2 2 a LAI of 6.1 m /m at age 6 yrs at the time of i t s f u l l e s t s i t e occupancy (Marks 1971). The denser plots at CiB.C.have.higher LAI's. Because net primary production i s also greater i n the denser p l o t s , photosynthetic capacity continues to increase with increasing l e a f area in d i c a t i n g f u l l e r s i t e u t i l i z a t i o n . The production to leaf area r a t i o (PLAR) i s the r a t i o 2 of net primary production to the LAI. The average of 374 g/m per year obtained i s again high f o r temperate hardwood 2 communities which generally range from 170 to 230 g/m per year (Whittaker 1966). The foliage assimilation e f f i c i e n c y (FAE) i s a si m i l a r parameter to the PLAR but i s more widely reported i n the l i t e r a t u r e (often as the net assimilation r a t e ) . I t relates net primary production to leaf weight. Bray and Gorham (1964) c i t e d an average of 3.7 Kg/Kg per yr for European and North American temperate forests. Fujimoto and Yamamoto (1967) determined a r a t i o of 6.9 Kg/Kg per yr i n 4-year-old stands of Acacia dealbata Link i n Japan. Zavitkovski and Stevens (1972) computed 4.65 Kg/Kg per yr f o r b i r c h stands i n B r i t a i n , 2.82 Kg/Kg per yr f o r the deciduous forests 85. of the Great Smokey Mts., 5 Kg/Kg per yr for the deciduous forests of the Western P a c i f i c and 4.04 Kg/Kg per year for 10-15 yr red alder i n western Oregon. The average for the study plots at U.B.C was 4 « 9 K9/ K9 P e r Y e a r which indicates a high f o l i a g e photosynthetic e f f i c i e n c y . Generally the fo l i a g e i n denser plots was more e f f i c i e n t . One explanation for t h i s i s based on the theories of Horn (1971, 1975) on secondary forest succession. The denser alder approach the mono-layered leaf arrangement with predominantly shade-leaves the shade preventing the development of more layers. In the less dense plots multi-layered canopy arrangements with sun and shade-leaves are favoured by greater l i g h t penetration. The leaf strategy induced by intense competition i n the denser stands appears to be optimal for productivity, the greater number of sun-leaves being more e f f i c i e n t . I t i s hypothesised that as i n t e r - t r e e competition declines i n the less dense stands a many-layered, sub-optimal arrangement develops. Another explanation may be a greater nocturnal buildup of s o i l generated C0 2 i n the i n t e r i o r of the more protected denser stands which would impart a photosynthetic premium over the less dense stands (Hellmers 1964). The standing crop density index (SCDI) rel a t e s the above-ground biomass to the height of the standing crop. I t was used by Kira and Shidei (1968) to describe stand 86. s p a t i a l occupancy i n terms of the apparent density of stand matter. They indicated a range of 1.0 to 1.5 Kg/m^ i n fully-stocked stands i n the Western P a c i f i c which was independent of height over a range of ages. However, Zavitkovski and Stevens (1972) recorded an index for red 3 alder of from 0.3 to 0.92 Kg/m which was p o s i t i v e l y correlated to stand height over a range of ages. The stands at U.B.C. 3 3 averaged 1.06 Kg/m and ranged from 0.98 Kg/m i n the le a s t 3 dense to 1.74 Kg/m i n the most dense p l o t s . Thus, space i s more f u l l y occupied i n the denser stands and i s negatively related to stand heightewithin the same age-class. The denser stands are more e f f i c i e n t at occupying space. 87. B. ENERGY FLOWS (1) CALORIC CONTENT Results (Table 20, Appendix IV) show that s i g n i f i c a n t v a r i a t i o n e x i s t s , both s p a t i a l l y and temporally between alder ecosystem components. Analysis of variance (ANOVA) by the randomized complete block design revealed a s i g n i f i c a n t i n t e r a c t i o n between component parts and the months of July, September and November. This was caused by the variable nature of male catkins and female cones (strobiles) which were i n the early stages of development. The c a l o r i c content for catkins increased over the 3 months to become the most energy-rich component. The s t r o b i l e s showed an i n i t i a l l y high value i n July, possibly due to the coating of a sticky exudate but c a l o r i c content decreased i n September af t e r the exudate had v o l a t i l i s e d and rose i n November, presumably due to the development of seeds. Some of t h i s v a r i a t i o n was l i k e l y experimental due to the small size and d i f f i c u l t y of c o l l e c t i o n i n July and thus the c a l o r i c values for the sexual structures should be re-tested for t h i s month. ANOVAR by completely randomized design within each of the three months showed a s i g n i f i c a n t v a r i a t i o n among the components. Application of Duncan's Multiple Range Test r e v e a l e d t h a t c e r t a i n components tended to form homogeneous sub-sets over time. The three separate groupings were: (1) bark, leaves and twigs, (2) roots and stems, and (3) branches. TABLE 20 . CALORIC VALUES IN 8-10 YR RED ALDER ECOSYSTEM COMPONENTS - SPATIAL AND TEMPORAL FLOWS ( c a l o r i e s / g , 3 r e p l i c a t e s ) ( X ± SD) 1. SPATIAL A . O v e r s t o r e y JULY (x = 4636.1 ± 300.4) Roots Stem wood Stem wood Stem wood O l d cones C a t k i n s Branches Leaves Stem bark Stem b a r k Twigs S t r o b i l e s Stem bark dbh top base base dbh t o p 4229 4399 4402 4406 4415 4534 4585 4752 4758 4787 4824 5068 5314 SEPTEMBER (x = 4640.2 226.3) S t r o b i l e s Stem wood Roots B r a n c h e s dbh 4362 4438 4450 4537 NOVEMBER (x = 4712.8 ± 229.2) Roots Stem wood S t r o b i l e s B r a n c h e s dbh 4382 4429 4547 4692 B. U n d e r s t o r e y (x = 4267.6 + 269) F e r n s Mosses H e r b s / G r a s s e s Rubus c u r r e n t Rubus o l d C o n i f e r s e e d l i n g s 3996 4080 4145 4209 4422 4755 C . Ground L a y e r Humus l i t t e r l a y e r T r e e l i t t e r f a l l 4517 4976 2. TEMPORAL ( A l l 3 months) (x = 4668 ± 240) Roots Stem wood dbh B r a n c h e s S t r o b i l e s Stem bark dbh Leaves Twigs C a t k i n s 4354 4422 4605 4659 4785 4799 4831 4879 Stem bark Leaves Twigs C a t k i n s dbh 4736 4748 4758 5065 Stem bark Twigs Leaves C a t k i n s dbh 4833 4883 4898 5037 N . B . L i n e j o i n s homogeneous s u b s e t s (Duncan's M u l t i p l e Range, a = 0.05) 89. Generally, c a l o r i c values tended to increase with height i n the tree, a phenomenon also noted by Golley (1961), Ovington (1961), Madgwick (1970), Jordan (1971) and Nemeth (1973). The d i s t r i b u t i o n of photosynthetically active, energy-rich young tissue p a r t l y accounts for t h i s . The high bark values are mainly due to greater contents of fixed carbon and extractives (Corder 1971) as well as to leaching of low-energy soluble carbohydrates by r a i n wash (Nemeth 1973). There was an o v e r a l l increase i n c a l o r i c values over time. The pooled means for July and September were not s i g n i f i c a n t l y d i f f e r e n t but November values were s i g n i f i c a n t l y higher. This i s thought to indicate gross conversion of simple sugars to starches and other storage products with the onset of winter. The understorey also showed s i g n i f i c a n t v a r i a t i o n between species groups. Notably the resinous conifer seedlings and older,smore l i g n i f i e d Rubus tissues exhibited higher c a l o r i c values. No s i g n i f i c a n t differences were found between the mean values for mosses, herbs and grasses or current Rubus tissues, though the mean for ferns was s i g n i f i c a n t l y lower. This indicates l i t t l e v a r i a t i o n i n the net primary production of the lesser vegetation. The tree-leaf l i t t e r f a l l c a l o r i c value was not s i g n i -f i c a n t l y d i f f e r e n t from the tree-leaf value i n November, but both 90\ were s i g n i f i c a n t l y higher than t r e e - l e a f values i n July and September. The tree-leaf l i t t e r f a l l value was unexpectedly high because translocation of chemical energy i n t o tree tissues p r i o r to abscission together with removal of highs energy organic constituents by f o l i a r leaching of the senescent leaves while on the tree (Morgan and Turkey 1964) would tend to reduce the energy content. However, Hughes (1971) found that leaves of Alnua glutinosa i n N.E. England also f e l l i n an energy enriched condition. Though no explanation was given i t i s known that leaves may be used as excretory mechanisms for secondary compounds which would tend to increase the c a l o r i c value (Thomas 1970). A number of researchers have recorded v a r i a t i o n i n botanically s i m i l a r material over both time and space (Long 1934, Golley 1961, B l i s s 1962, Johnson and Robel 1968, Leith and Pflanz 1968, Malone 1968, Madgwick 1971, L e i t h 1975). Most estimates i n the l i t e r a t u r e have, however, been based on standard values and not from d i r e c t measurements of the community i n question (see f o r instance Whittaker and Woodwell 1969, Zavitkovski 1976) . This practise may be j u s t i f i e d when estimating the energy content of large areas such as biomes i n which the errors of biomass estimates surpass those from the use of detailed c a l o r i c values (NewbOld 1967, Thomas 1970). Also, c a l o r i c analyses are extremely time consuming. However, energy represents the 91. s t a r t i n g point for ecosystem metabolism and functioning. By merely adopting generalized dry-raatter-to-energy conversion factors r e s u l t s w i l l be oversimplified and misleading. Leith (1968) argued that i t i s preferable to apply an accurate secondary estimate (energy) to a primary estimate (biomass) rather than to impose a constant error (standard energy value). Ovington and Heitkamp (1960) and Ovington (1961) pioneered detailed forest energy studies, but data did not begin to accumulate u n t i l the l a t e 1960*s with the onset of the International B i o l o g i c a l Programme (IBP) (Ovington and Lawrence 1967, Leith 1968, Madgwick 1970, Peterson et a l . 1970, Thomas 1970, Hughes 1971, Jordan 1971, Satchell 1971, Reiners 1972, Nemeth 1973). Cal o r i c values based on oven-dry .ash-containing matter are best for studying eco l o g i c a l e f f i c i e n c y (Ovington and Lawrence 1967, Leith 1975). But, the more ash the lower the c a l o r i c value and the wider the range between a l l ecosystem tissues (Madgwick 1970) . If the data presented here were re-calculated on an ash-free basis the c a l o r i c values would be higher and less v a r i a b l e . However, because the oven-dry basis represents the true energy value and not the i n t r i n s i c value of the organic material, the correction for ash-content was not made. Thus, some of the v a r i a t i o n may be due to component ash-content differences. 92. (2) ENERGY FLOWS AND EFFICIENCIES (a) Flows of Energy Table 21 gives energy flows and conversion e f f i c i e n c i e s . The t o t a l c a l o r i c value of the above-ground biomass (called 2 the above-ground biocontent) averaged 3,203 Kcal/m , of which 57 percent was stem wood, 8 percent leaves, 22 percent branches and 1 percent sexual parts. This agrees with the p a r t i t i o n i n g of biomass except that the percentage for bark and leaves are both 1 percent greater due to higher c a l o r i c content. In general, the biocontent was similar on dense and less dense plots though was much reduced on the poorest p l o t , p l o t #2. The energy value f o r the average tree weighted by biomass (called the above-ground composite-tree) amounted to 4.53 Kcal/g and varied l i t t l e between plots (SD=0.015 Kcal/g, CV=3 percent). This agrees with the only other available composite-tree data for a temperate hardwood: 4.52 Kcal/g for 15 year o l d Cornus florida L. (Thomas 1970). Energy invested i n above-ground net primary production (called the above-ground production content) averaged 2 13.064 Kcal/m with a heavy appropriation of energy to branches and leaves both of 22 percent. Energy loss from the above-ground ecosystem through l i t t e r f a l l amounted to 6 percent of above-ground biocontent and 17 percent of above-ground production content. Hughes (1971) showed l i t t e r f a l l energy content for a 100 yr old 21 . ABOVE-GROUND AUTOTROPHIC ENERGY FLOWS AND EFFICIENCIES IN 8-10 YR RED ALDER ECOSYSTEMS ( a l l v a l u e s = Kcal /m2) Plot # # l i v e o v e r s t o r e y s t e m s / h a S i t e c l a s s B i o c o n t e n t T o t a l Stem Stem bark L e a v e s B r a n c h e s R e p r o d u c t i v e s t r u c t u r e s P r o d u c t i o n c o n t e n t T o t a l Stem Stem b a r k L e a v e s B r a n c h e s R e p r o d u c t i v e s t r u c t u r e s U n d e r s t o r e y B i o c o n t e n t P r o d u c t i o n c o n t e n t L i t t e r l a y e r L i t t e r f a l l S o l a r c o n v e r s i o n  e f f i c i e n c i e s PAR  d u r i n g A p r i l - O c t - P l o t s ranked by d e n s i t y and s i t e -% 0 * „ 6 3 1 0 5 4 9 2 Mean D i s t r i b u t i o n 8,204 9,983 9 ,983 15,790 22,264 42,971 17,025 13,047 17,103 G G G M M M-P P P M 43810 41884 30601 50641 37698 48367 26613 18008 37203 27570 25260 18934 32288 18971 24112 14210 9696 21380 4798 4595 3489 5924 4445 6254 3345 2341 4399 3157 3515 2510 3820 3202 3399 2244 1455 2913 8092 8316 5536 8408 10732 14142 6600 4367 8274 193 198 132 201 348 460 214 149 237 57 12 8 22 1 13133 12846 9191 14791 16388 18647 11437 8092 13064 6426 5657 4113 6988 8270 8555" 6130 4481 6327 720 690 534 890 667 938 502 351 660 3157 3515 2510 3820 3202 3909 2244 1455 2913 2637 2786 1902 2892 3901 5295 2347 1656 2917 193 198 132 201 348 460 214 . 149 237 1399 846 55 123 1067 242 253 347 542 580 324 52 61 504 166 186 128 250 .— - - - - - - 2625 2376 2362 2383 2843 2262 1748 2253 1502 2216 3.0% 2.9% 2.0% 3.3% 3.7% 4.2% 2.6% 1.8% 2.9% 49 5 22 22 2 % t r e e s t r a t u m 2 2 PAR = p h o t o s y n t h e t i c a l l y a c t i v e r a d i a t i o n 94. AInus glutinosa-Betula pendula Roth forest i n England was 40.6 percent of the above-ground production content. Thomas (1970) worked on a 15 yr-ol d Cornus florida stand i n Tennessee, U.S.A. and recorded a l i t t e r f a l l energy debt to above-ground production content of 17 percent. Thus young, highly productive se r a i species seem to be characterized by a smaller r e l a t i v e loss of above-ground production content to l i t t e r f a l l and greater rates of energy incorporation into tree t i s s u e s . In a s i m i l a r fashion the denser alder plots at U.B.C. l o s t less of the above-ground production content to l i t t e r f a l l (8 percent loss from the densest and 18 percent loss from the l e a s t dense p l o t ) . This implies that succession i s more advanced i n the less dense p l o t s . Data available j u s t i f y the statement that the energy flux i n 8 to 10 yr old alder ecosystems i s rapid compared to other cool-temperate angiosperms. The t r e e - l i t t e r f a l l energy 2 content of 2216 Kcal/m i s much higher than the value reported 2 for Quercus petraea L i e b l . i n NW England of 1863 Kcal/m (Carlise et a l . 1966) or an Alnus glutinosa-Betula pendula forest i n NE England of 1450 Kcal/m 2 (Hughes 1971). S i m i l a r l y , the average l i t t e r layer c a l o r i c content indicates only 1.2 yrs of energy accumulation p r i o r to secondary trophic l e v e l a s s i m i l a t i o n . (b) E f f i c i e n c i e s Data c o l l e c t e d at u.B.C{Monthly Radiation Summary, Environment Canada) indicates that the average incident net solar r a d i a t i o n between A p r i l and October for 1974 to 1976 2 was about 89000 Langleys (1 Langley=lcal/cm ). of t h i s , 50 percent l i e s within the photosynthetically active (PAR) or v i s i b l e wavelength 4000& to 7000A* (Szeicz 1974). E f f i c i e n c y calculations were based on above-ground ecosystem production and net PAR during the growing season. Table 21 shows the average e f f i c i e n c y of 2.9 percent and the range of 1.8 to 4.2 percent. Using the same parameters Loomis and Williams (1963) calculated an upper t h e o r e t i c a l ' l i m i t ' of 12 percent. In a review, Hellmers (1964) recorded a range of 2.2 to 3.5 percent for forests, but most forest communities tend to have e f f i c i e n c i e s of 1 to 2 percent (Wassink 1968). If losses due to evaporation, r e f l e c t i o n and transmission etc. are accounted for then e f f i c i e n c i e s would be increased sub s t a n t i a l l y (Bray 1961). Moreover, e f f i c i e n c i e s would be increased by at l e a s t 20 percent i f roots were included (Bray 1963). The highest conversion e f f i c i e n c y shown by a natural North American forest outside t h i s study i s 3.17 percent for Liriodendron tulipifera i n Tennessee (Jordan 1971). The extremely high solar energy conversion e f f i c i e n c i e s of 8 to 10 yr alder at u.B.C. are due i n part to the i n t e r a c t i o n of b i o l o g i c a l and geographical 96. factors. Geographically there i s a trend towards higher wood production e f f i c i e n c i e s at higher l a t i t u d e s where l i g h t i s l i m i t i n g (Jordan 1971). As the l i g h t i n t e n s i t y from f u l l sunlight decreases, photosynthetic e f f i c i e n c y increases (Hellmers 1964). The species e f f i c i e n c y data used i n the above comparisons were obtained from generally more southerly l a t i t u d e s . No s i m i l a r study could be found which compared solar conversion e f f i c i e n c i e s with the number of stems per unit area. Table 21 shows that the denser stands are generally much more e f f i c i e n t than the less dense stands, suggesting among other things that c r i t i c a l leaf-mass and arrangement as well as i n t e r n a l stand micro-environments ( i . e . C0 2 b u i l d up and increased N 2 fixation) are maximized i n the struggle for l i g h t and space. E f f i c i e n c y continued to increase with increasing stem crowding which indicates that a c r i t i c a l upper l i m i t to stand density had not been reached i n the study p l o t s . 97. CH.4 CONCLUSIONS AND SUMMARY A. CONCLUSIONS (1) METHODOLOGY The regression estimations are biased i n the sense that sample-trees did not represent the f u l l range of dimensions within the study p l o t s . The se l e c t i o n of the largest sample-trees i n each grouped-plot (0.004 ha) means that the suppressed trees are ignored. C l e a r l y , i f a l l trees were growing i n equal proportions l i t t l e error would r e s u l t . However, the greater the number of suppressed trees the greater the l i k e l i h o o d of overestimation. But sampling had to be compromised for other analyses (see J.H.G. Smith i n press). The agreement of data presented i n t h i s study with those of Zavitkovski and Stevens (1972) and lower values i n comparison with the re s u l t s of Smith (1968) and Smith and DeBell (1974) for dense alder stands implies that the equations may be used with some degree of confidence. The precision of the regression estimations may be questioned for some of the component equations. In p a r t i c u l a r , 2 the crown regressions were based on R ^ 0.479 and SE^37 percent of Y. The dilemma i s that the inherent v a r i a b i l i t y of crown components m i l i t a t e s against s t a t i s t i c a l p r e c i s i o n , yet i t i s important to obtain reasonable estimates of crown biomass to give meaningful data on the parameters of ecolo g i c a l production 98. (Kittredge 1944). That many researchers achieve high R and low SE values i n t h e i r regression equations i s testament, not so much to the prec i s i o n , as to the wide range of dimensional size classes covered—often with few data i n each c l a s s (Nemeth 1973). The Inclusion of the crown parameter i n the multiple regression may also be challenged. However, Smith (1971) has indicated that equations dealing with crown components as well as the main stem are desirable as a basis for generalizations concerning the basic b i o l o g i c a l processes c o n t r o l l i n g tree growth, and thus may also be used i n stand and tree modelling. U n r e l i a b i l i t y may r e s u l t from basing some of the sample-tree regression equations on data derived from t o t a l -sample-tree regression estimation. Such practises of re-estimation are, however, common i n production studies. For instance, branch biomass i s often related to the regression of dry-weight on branch basal diameter, summed for the tree and then re-estimated from more e a s i l y measured parameters (Whittaker and Woodwell 1970). Constraints of time and money make such approaches inescapable. (2) BIOMASS, PRODUCTION AND ENERGY FLOWS This study ignores the contribution of roots to organic matter and energy turnover. The conventional 0.2 forest root/shoot production r a t i o i s currently thought to give an underestimate (Whittaker and Marks 1975), though t h i s remains to be tested i n alder ecosystems. A recurrent theme throughout t h i s study has been an examination of the e f f e c t s of density and s i t e on biomass, production and energy flows. It i s recognized that a range of environmental and genetic factors controls the expression of these att r i b u t e s within any one stand. Merely ranking plots by number of stems and imputed height at 50 years ignores the synecological complexity of forested ecosystems. Nonetheless, by focusing on these issues i t was hoped to reveal how alder can be manipulated to provide plantations managed on 8 to 10 year rotations. Larson (1962) argued that control over stand density was the foresters* most powerful method for orchestrating wood y i e l d and q u a l i t y . This th e s i s lacks the temporal aspect which would give data on stand dynamics. However, i t was shown that the extremely dense stands were currently more productive, both i n terms of mass and energy than the less dense stands, though"theyJshowed a s i m i l a r cumulative biomass. Because productivity continued to increase with excessive stem crowding i t i s thought that the upper l i m i t s to density and hence productivity were not reached i n the study p l o t s . It was also argued that the denser stands were successionally less advanced which implies that maximum productivity would not be r e a l i z e d t i l l a l a t e r stage i n stand 100. development. An hypothesis put forward f o r the 'UvJBVG. stands .is based on the a p r i o r i assumption that, at l e a s t on the good and medium s i t e s , i n i t i a l germination success and stocking were s i m i l a r . On the better q u a l i t y s i t e s intense competition would produce massive i n i t i a l mortality, rapid crown closure and early s i t e optimization. This strategy would favour the fewer, more vigorous trees which would respond at maximum growth rates i n the race for l i g h t and space. However, because t h i s process i s e s s e n t i a l l y density-dependent, the dominant trees would early on achieve f u l l s i t e occupancy at the expense of competitor trees. With t h i s reduction i n competition, growth would switch to a slower, density-independent phase. On the less favourable s i t e s more smaller trees would grow to begin with at sub-optimal rates. But, as stand conditions were improved by the alder (e.g. increased N 2 f i x a t i o n , C0 2 build-up, s o i l improvement), the superior genotypes would be able to express dominance, producing an optimal, density dependent growth phase. Hence, y i e l d s under both crowded and uncrowded conditions would tend to be sigmoid but with growth of the denser stands approaching, or even surpassing the productivity i n the less dense stands because i n t e r ^ fcree,competition would be maintained for longer. An al t e r n a t i v e hypothesis i s based on the assumption that i n i t i a l germination and seeding conditions were better on 101. the 'denser' s i t e s . Then the vast number of small trees would have to pass through a period of extreme competition and excessive mortality which would r e s u l t i n an i n i t i a l l y reduced stand growth. In the less dense stands, poorer i n i t i a l seeding would mean that the trees could pass d i r e c t l y into the density-dependednt, maximum y i e l d phase. Gordon (1973) reasoned that the id e a l i n d i v i d u a l plantation type (called the ideotype) should e f f e c t i v e l y occupy space allocated rather than compete for i t . This implies elimination of stand mortality, an expensive drain on the ecosystem i n terms of r e s p i r a t i o n , and attempting to induce maximum growth rates on the remaining stems which would be achieved i n nature only under intense competition. It remains to be seen how alder responds to these circumstances. Bernsten (1961) and Warrack (1964) have shown that alder responds poorly to thinning. C l e a r l y , a mix of the dense and less dense developmental phases i s desirable so that maximum growth i s induced on fewer stems and as quickly as possible. In addition, a better understanding of the a e t i o l o g i c a l r e l a t i o n s h i p between increased N 2 f i x a t i o n , l eaf surface area, photosynthetic e f f i c i e n c y , i n t e r n a l stand CC^ build-up and f i b r e y i e l d s i s needed (Gordon i n press). The exceptionally high productivity and e f f i c i e n c y displayed by red alder gives i t a poten t i a l as a biomass or 102. energy plantation crop. The future of alder for energy supplies ( s o l i d , l i q u i d and gaseous) has been examined elsewhere (N.J. Smith i n press). It was shown that the land base required to f u e l power-stations i n meeting B.C.'s 1981 energy needs by conventional d i r e c t - f i r i n g would amount to 21 percent of B.C. at 8.5 mt/ha/yr and 8 percent of B.C. at 22.5 mt/ha/yr. Even under advanced 1990 combined-cycle technology the area needed would be 12 percent of B.C. at 8.5 mt/ha/yr and 4 percent of B.C. at 22.5 mt/ha/yr. In the l i g h t of alder's limited e c o l o g i c a l amplitude and competing land uses i t was concluded that only small-scale energy plantations for subsidiary u t i l i t y supplies on marginal land or energy-subsisting l o c a l communities on Vancouver Island seemed p r a c t i c a l . The term 'biomass-farm' was preferred since i t did not imply y i e l d appropriation to any p a r t i c u l a r market but retained s u f f i c i e n t f l e x i b i l i t y to s a t i s f y a range of s o c i e t a l wants. A spectrum of products was envisaged, including 'muka' from f o l i a g e (Keays and Barton 1975), chemicals (Marshall et a l . 1975), food ( P i r i e 1968), fuelwood, pulp (Hrutfiord i n press) and shelter (Gordon i n press). 103. (B) SUMMARY (1) Eight 0.04 ha plots were established during June and July 1976 i n naturally seeded 8 to 10 yr old red alder stands near U,B,C J rBriti6h^oI-\iaibia under closed-canopy conditions over a range of stem densities and s i t e types. Above-ground biomass and net primary production were estimated for the overstorey by multiple l i n e a r regressions and f o r the understorey by biomass to area r e l a t i o n s h i p s . L i t t e r f a l l was measured i n l i t t e r traps from August to December. Detailed c a l o r i c analyses were ca r r i e d out by bomb calorimetry. (2) The number of l i v e stems per ha at 8 to 10 yrs increased from 8,204 on good s i t e s to 42,971 on medium s i t e s . The number of dead stems per ha increased from 5,239 on good s i t e s to 16,729 on medium s i t e s . Stand dimensions i n crowded plots showed higher and narrower, more peaked frequency d i s t r i b u t i o n s . (3) Above-ground overstorey biomass at 8 to 10 yrs averaged 82 mt/ha and ranged from 40 mt/ha to 112 mt/ha. Net above-ground overstorey productivity averaged 28,601 Kg/ ha/yr and ranged from 17,802 Kg/ha/yr to 40,831 Kg/ha/yr. (4) Lesser vegetation displayed an average above-ground terminal biomass of 1,255 Kg/ha (range: 124 Kg/ha - 3,241 Kg/ha) and an annual productivity of 591 Kg/ha/yr (range: 118 Kg/ 104. ha/yr - 1,374 Kg/ha/yr) . This was equivalent to 1.5 percent of the overstorey biomass and 2 percent of the overstorey production. Light penetration through the overstorey ranged from 1 to 6 percent f u l l - s u n l i g h t and d i r e c t l y controlled understorey vegetation. Rubus speotabilis constituted 68 percent of the understorey biomass and required at lea s t 6 percent f u l l - s u n l i g h t before growth was s i g n i f i c a n t . Conifer reproduction was present i n a l l plots but constituted only 1.9 percent of understorey biomass. (5) L i t t e r f a l l averaged 4,454 Kg/ha (range: 3,019 Kg/ha - 5,713 Kg/ha). Of t h i s , 92.4 percent was leaves, 6.9 percent branches and 0.7 percent reproductive structures. L e a f - l i t t e r f a l l underestimated leaf production by 32 percent. Most l i t t e r f e l l at the end of October and during November. The undecomposed l i t t e r layer represented 1.3 yrs accumulation. (6) Low biomass accumulation r a t i o s (av. 2.86 mt/mt) 2 2 and r e l a t i v e l y high values f o r leaf area index (av. 7.64 m /m ), 2 production to leaf area r a t i o (av. 374 g/m ), fol i a g e assimilation e f f i c i e n c y (av. 4.9 mt/mt) and standing crop 3 density index (av. 1.06 Kg/m ) indicate that red alder i s one of the most productive cool-temperate hardwood species. The most dense s i t e s were e s p e c i a l l y e f f i c i e n t . Productivity continued to increase with increasing density and leaf-area, 2 2 though 10m /m probably represents the optimal mass. 105. (7) The above-ground 'composite-tree' averaged 4.53 Kcal/g ash-containing t i s s u e . Component parts showed s i g n i f i c a n t v a r i a t i o n within trees and over time. C a l o r i c values generally increased with height i n the tree and during the f a l l . (8) E f f i c i e n c i e s of conversion of v i s i b l e net radiation during the growing season averaged 2.9 percent with a range of 1.8 to 4.2 percent. The densest stands were the most e f f i c i e n t . These values approach the upper l i m i t s reported for e ither a g r i c u l t u r a l crops or forest communities. (9) The energy accumulated i n biomass (biocontent) 2 4 averaged 37203 Kcal/m (x 10 =Kcal/ha). Of t h i s , 55 percent was stem wood, 12 percent stem bark, 8 percent leaves, 22 percent branches and 1 percent reproductive parts. Energy incorporated as primary production (production content) 2 averaged 13064 Kcal/m (no correction for herbivory or m o r t a l i t y ) . Of t h i s , 49 percent was stem wood, 5 percent stem bark, 22 percent leaves, 22 percent branches and 2 percent sexual parts. Some 17 percent of production content was l o s t through t r e e - l i t t e r f a l l . (10) A hypothetical stand model i s presented which relates biomass and production on a density-dependent basis. Intense competition on the best s i t e s w i l l lead to early peaks 106. i n productivity, while medium s i t e s w i l l achieve maximum yi e l d s l a t e r i n stand l i f e . Poor s i t e s w i l l not l i k e l y maintain competitive between-tree vigour. (11) Stands managed on the basis of 8 to perhaps 12 years w i l l maximize f i b r e y i e l d s . Potentials e x i s t f o r alder based energy or biomass farms. The high e f f i c i e n c i e s of alder warrant that i t be grown not only on marginal land but as a competitive crop i n i t s own ri g h t on a short rot a t i o n , intensive basis. Data presented are for natural stands. The prospects of improved y i e l d s under managed conditions are impressive, but care should be taken i n extrapolating the data presented here to other areas. 107. BIBLIOGRAPHY Art, H.W. and P.L. Marks. 1971. A summary table of biomass and net annual primary production i n forest ecosystems of the world. In H.E. Young (ed.) IUFRO Forest Biomass Studies, pp. 3-34. Working group on forest biomass studies Sect. 25: Y i e l d and growth. L i f e S c i . and Agric. Exp. Stn., Univ. Maine, Orono. A.S.T.M. 1974. Standards for bomb calorimetry and combustion methods. Reprint from Annual Book of A.S.T.M. Standards. Parr Ihstru C o•» Moline, 111.. 49 p.. Atkinson, W.A. and W.I. Hamilton, i n press. The value of red alder as a source of nitrogen i n Douglas-fir stands. In D. Briggs et a l . (%d.) Alder u t i l i z a t i o n and management. Proc. V.W. Conf., Ocean Shores, Washington, 1977. A t t w i l l , P.M. and J.D. Ovington. 1968. Determination of forest biomass. For. S c i . 14:13-15. Baskerville, G.L. 1965. Dry matter production i n immature balsam f i r stands. Forest S c i . Monograph 9. 42 p.. Baskerville, G.L. 1972. Use of logarithmic regressions i n the estimation of plant biomass. Can. J . For. Res. 2:49-53. Beauchamp, J . J . and J.S. olson, 1973. Correction for bias i n regression estimates a f t e r logarithmic transformation. Ecol. 54: 1403-1407. 108. Berg, A. and A. Doerken. 1975. Natural f e r t i l i z a t i o n of a heavily thinned Douglas-fir stand by understorey red alder. Res. Note 56. Forest Res. Lab., C o r v a l l i s , Oregon. Bernsten, CM. 1961. Growth and development of red alder compared with conifers i n 30 yr-ol d stands. U.S. Forest Serv. P a c i f i c N.W. Forest and Range Exp. Stn. Res. Pap. 38. 19 p.. B l i s s , L.C. 1962. C a l o r i c and l i p i d content of alpine tundra plants. Ecol. 43:753-757. Bollen, W.B. and K.C. Lu. 1968. Nitrogen transformation i n s o i l s beneath red alder and c o n i f e r s . In J.M. Trappe et a l . (ed.). Biology of alder, pp. 141-148. Proc. N.W. S c i . Assoc. 1967 Meeting. Bray, J.R. 1961. An estimate of a minimum quantum y i e l d of photosynthesis based on ecological data. P i . Physiol., Lan., 36:371-3. Bray, J.R. 1963. Root production and estimation of net productivity. Can. J . Bot. 41:65-72. Bray, T.R. and E. Gorham. 1964. L i t t e r production i n forests of the world. Adv. Ecol. Res. 2: 101-157. C a r l i s l e , A., A.H. Brown and E.J. White. 1966. L i t t e r f a l l , l eaf production and the e f f e c t s of d e f o l i a t i o n by Tortrix viridana i n a s e s s i l e oak (Quercus petraea) woodland. J . Ecol. 54:65-85. 109. Corder, S.E. 1976. Properties and uses of l a r k as an Energy source. Res. Paper 31, For. Res. Lab. Oregon State Univ., C o r v a l l i s , Oregon. 21 p.. Crow, T.R. 1971. Estimation of biomass i n an even-aged stand-regression and 'mean tree' techniques. In H.E. Young (ed.) IUFRO Forest Biomass Studies, pp. 35-48. Working group on forest biomass studies. Sect. 25: Y i e l d and growth. L i f e S c i . and Agric. Exp. Sta., Univ. Maine, Orono. DeBell, D.S. 197 2. Potential productivity of dense, young thickets of red alder. Forest Res. Note No. 2. Crown Zellerbach. 7p.. DeBell, D.S. 1975. Short-rotation culture of hardwoods i n the P a c i f i c Northwest. Iowa J . Res. 49: 345-352. DeBell, D.S., R.F. Strand and D.L. Reukema. i n press. Short-r o t a t i o n production of red alder: some options for future forest managers. In D. Briggs et a l . (ed.) Alder u t i l i z a t i o n and management. Proc. U.W. Conf. Ocean Shores, Washington, 1977. Evans, R.S. 1974. Energy plantations - should we grow trees for power-plant fuel? Dept. Env., Can. Fori. Serv., Wtn. For. Prod. Lab. Info. Report VP-X-12. 15 p.. Franklin, J.F. and C.T. Dyrness. 1969. Vegetation of Oregon and Washington. U.S. P a c i f i c NW Forest and Range Exp. Sta., Portland. Res. Paper PNW-80, 216 p.. 110. Friend, D.T.C. 1961. A simple method of measuring integrated l i g h t values i n the f i e l d . Ecol. 42: 577-580. Fujimori, T. and K. Yamamoto. 1967. Productivity of Acacia dealbata stands. J . Jap. For. Soc. 49: 143-149. Gagnon, J.D., A. Lafond, and P.L. Amlot. 1958. Mineral nutrient content of some forest plant leaves and of the humus layer as related to s i t e q u a l i t y . Can. J . Bot. 36: 209-220. Gessel, S. and D. Cole. i n press. A comparison of alder and Douglas-fir nutrient c y c l i n g . In D. Briggs et a l . (ed.) Alder u t i l i z a t i o n and management. Eroc. U.W. Conf., Ocean Shores, Washington, 1977. Golley, F.B. 1961. Energy values of ecological materials. Ecol. 42: 581-584. Gordon, J.C. 1975. The productive p o t e n t i a l of woody plants. Iowa J . Res. 49: 267-74. Gordon, J.C. i n press. B i o l o g i c a l components of alder y i e l d improvement. In D. Briggs et a l . (ed.) Alder u t i l i z a t i o n and management. Proc. U.W. Conf., Ocean Shores, Washington, 1977. Harkin, J.M. and J.W. Rowe. 1971. Bark and i t s possible uses. USDA Forest Service Res. Note FPL-091. Forest Products Lab., Madison, Wisconsin. Heilman, P.E., D.V. Peabody J r . , D.S. DeBell and R.F. Strand. 1972. A test of close-spaced, short-rotation culture of black Cottonwood i n the P a c i f i c Northwest. Can. J . For. 111. Res. 2: 456-459. Hellmers, H. 1964. An evaluation of the photosynthetic e f f i c i e n c y of f o r e s t s . Q. Rev. B i o l . 39: 249-57. Henderson, J.A. 1970. Biomass and composition of the understorey vegetation i n some Alnus rubra stands i n western Oregon. M.S. Thesis. Oregon State Univ., C o r v a l l i s . 64 p.. Herrick, A.M. and C L . Brown. 1967. A new concept i n c e l l u l o s e production - s i l a g e sycamore. Agr. S c i . Res. 5: 8-13. Horn, H.S. 1971. The Adaptive Geometry of Trees. Princeton Univ. Press. Horn, H.S. 1975. Forest succession. S c i . Am. 234 (3): 90-98. Howlett, K. and A. Gamache. 1977. S i l v i c u l t u i r a l biomass farms. V o l . I I : The biomass pote n t i a l of short-rotation farms. MITRE Technical Report #7347, Vol . I I . METREK Div i s i o n . 136 p.. Hrutfiord, B. i n press. Alder as a pulp species. In D. Briggs et a l . (ed.) Alder u t i l i z a t i o n and management. Proc. U.W. Symp, Ocean Shores, Washington. 1977. Hughes, M.K. 1971. Tree biocontent, net production and l i t t e r f a l l i n a deciduous woodland. Oikos 22: 62-73. Inman, R.E. 1977. S i l v i c u l t u r a l biomass farms. Vol. I: Summary MITRE Technical Report #7347 Vol. I. METREK Div i s i o n . 62 p.. 112. Johnson, S.R. and Robel, R.J. 1968. C a l o r i c values of seeds from four range s i t e s i n northeastern Kansas. Ecol. 49: 956-961. Jordan, C F . 1971. Productivity of a t r o p i c a l forest and i t s r e l a t i o n to a world pattern of energy storage. J . Ecol. 59: 127-142. Kan. M., H. Saito, and T. Shidei. 1965. Studies of the productivity of evergreen broad leaved fore s t s . B u l l . "Kyoto Univ. For. 37: 39-48. Keays, J.L. and G.M. Barton. 1975. Recent advances i n foliage u t i l i z a t i o n . Can. For. Serv. Info. Report VP-X-137. 94 p.. Keays, J.L. and J.V. Hatton, 1975. The implication of f u l l -f orest u t i l i z a t i o n on world wide supplies of wood by year 2000. Pulp and Paper International, June, 1975. (Reprint). Kenady, R.M. i n press. Natural and a r t i f i c i a l regeneration of alder. In D. Briggs et al^. Alder u t i l i z a t i o n and management. Proc. U.W. Conf., Ocean Shores, Washington, 1977. Kira, T. and T. Shidei. 1967. Primary production and turnover of organic matter i n d i f f e r e n t forest ecosystems of the Western P a c i f i c . Jap. J . Ecol. 17: 70-87. Kiittredge>~J. 1944. Estimation of the amount of fol i a g e of trees and stands. J . For. 42: 905-12. 113. Kozak, A. 1970. Methods for ensuring a d d i t i v i t y of biomass components by regression analysis. For. Chron. 46: 402-404. Krajina, V.J. 1965. Biogeoclimatic zones and c l a s s i f i c a t i o n of B r i t i s h Columbia. In V.J. Krajina (ed.) Ecol. of Western N. Am. 1: 1-17. K r i j i n a , V.J. 1969. Ecology of forest trees i n B r i t i s h Columbia. In V.J. Krajina (ed.) Ecol. of Western N. Am. 2: 1-146. Larson, P.R. 1962. A b i o l o g i c a l approach to wood q u a l i t y . TAPPI 45: 443-448. Lei t h , H. 1968. The determination of plant dry-matter production with s p e c i a l emphasis on underground parts. In F.E. Eckardt (ed.) Functioning of t e r r e s t r i a l ecosystems at the primary production l e v e l . Natural Resource Research 5: 53-64. Proc. Copenhagen Symp. 1965. Par i s . UNESCO. Leit h , H. 1975. Measurement of c a l o r i c values. In H. Lei t h and W.H. Whittaker (ed.) Primary productivity of the biosphere, pp. 201-215. Springer Verlag. Ecol. Studies 14. Lei t h , H. and B. Pflanz. 1968. The measurement of c a l o r i f i c values of b i o l o g i c a l material and determination of ecological e f f i c i e n c y . In F.E. Eckardt (ed.) Functioning of t e r r e s t r i a l ecosystems at the primary production l e v e l . Natural Resources Research 5: 233-242. Proc. 114. Copenhagen Symp. 1965. P a r i s . UNESCO. L i , C.Y., K.C. Lu, J.M. Trappe and W.B. Bollen. 1967. Selective nitrogen a s s i m i l a t i o n by Porta weirii. Nature (London) 213: 814. L i , C.Y., K.C. Lu, J.M. Trappe and W.B. Bollen. 1968. Enzyme systems of red alder and Douglas-fir i n r e l a t i o n to i n f e c t i o n by Poria weirii. In J.M. Trappe et a l . (ed.) Biology of alder, pp. 241-250. Proc. N.W. S c i . Assoc. 1967 Meeting. L i t t l e , G. i n press. Supply of western alder stumpage, i t s quantity and q u a l i t y , 1976-1996. In D. B r i g g s et al_. (ed.) Alder management and u t i l i z a t i o n . Proc. U.W. Conf., Ocean Shores, Washington, 1977. Long, F.L. 1934. Application of calorimetric methods to tecological research. Plant Physiol. 9: 323-337. Loomis, P.R. and W.A. Williams. 1963. Maximum crop productivity: an estimate. Crop S c i . 3: 67-72. McAlpine, R.G., G.L. Brown, A.M. Herrick and H.E. Ruark. 1966. "Silage" sycamore. Forest Farmer 26: 6-7. Madgwick, H.A.I. 1970. C a l o r i c values of Pinus virginiana as affected by time of sampling, tree age and p o s i t i o n i n stand. Ecol. 51: 1094-1097. Madgwick, H.A.I. 1971. The accuracy and precision of estimates of the dry matter of stems, branches and f o l i a g e i n an o l d - f i e l d Pinus virginiana stand. In 115. H.E. Young (ed.) IUFRO Forest Biomass Studies, pp. 105-112. Working group on forest biomass studies. Sect. 25. Y i e l d and growth. L i f e S c i . and Agric. Exp. Sta., Univ. Maine, Orono. Malone, CR. 1968. Variation i n c a l o r i c equivalents for herbs as a possible response to environment. B u l l . Torrey Bot. Club 95: 87-91. Marks, P. 1971. The r o l e of Prunus pensylvanioa L. i n the rapid revegetation of disturbed s i t e s . Ph.D. thesis, 119 p.. New Haven, Yale Univ.. Marshall, J.E., G. Petrick, H. Chan. 1975. A look at the economic f e a s i b i l i t y of converting wood into l i q u i d f u e l . Info. Report E-X-25. Env. Canada. For. Service. 32 p.. M i l l e r , R.E. and M.D. Murray, i n press. The e f f e c t s of red alder on growth of Douglas-fir. In D. Briggs et ,al. (ed.) Alder u t i l i z a t i o n and management. Proc. U.W. Conf., Ocean Shores, Washington. 1977. Morgan, J.F. and H.B. Tukey J r . 1964. Characterization of leachate from plant f o l i a g e . Plant Physiol. 39: 590-593. Munro, D.D. 1974. Use of logarithmic regression i n the estimation of plant biomass: discussion. Can. J . For. Res. 4:149. Nelson, E.E., E.M. Hansen, C Y . Lui and J.M. Trappe, i n press. Role of red alder i n ameliorating conifer s i t e s infested with Phellinue (Poria) w e i r i i . In D. Briggs et a l . 116. (ed.) Alder u t i l i z a t i o n and management. Proc. U.W. Conf., Ocean Shores, Washington. 1977. Nemeth, J.C. 1973. Dry matter production i n young l o b l o l l y (Pinus taeda L J and slash pine (Pinus elliottoi Engelm.) plantations. Ecol. Monog. 43: 21-41. Newbould, P.J. 1967. Methods for estimating the primary production of for e s t s . I.B.P. Handbk #2. Blackwell S c i e n t i f i c Pub., Oxford and Edinburgh. 60 p.. Newton, M., B. El-Hassen and J. Zavitkovski, 1968. Role of red alder i n western Oregon forest succession. In J.M. Trappe et a l . (ed.) Biology of alder, pp. 73-84. Proc. N.W. S c i . Assoc. 1967 Meeting. Norris, D.J. 1971. The University Endowment Lands. Report for Forestry 404, U.B.C.....,45..p.-... Odum, E.P. 1960. Organic production and turnover i n old-f i e l d succession. Ecol. 41: 34-49. Odum, E.P. 1971. Fundamentals of Ecology. Saunders, Toronto. Third E d i t i o n . 574 p.. Ogawa, H., K. Yada, K. Ogino, and T. Kir a . 1965. Comparative ecological studies of three main types of forest vegetation i n Thailand. I I . Plant biomass. Nature and L i f e i n S.E. Asia 4: 49-80. Ovington, J.D. 1961. Some aspects of energy flow i n plantations of Pinus Sylvester is ii . Ann. Bot. N.S. 25: 12-20. 117. Ovington, J.D., W.G. Forest, and J.S. Armstrong. 1967. Tree biomass estimation. In H.E. Young ;(ed.) Symposium on primary productivity and mineral cy c l i n g i n natural ecosystems, pp. 4-31. Ecol. Soc. Am., Univ. Maine Press, Orono, Maine. Ovington, J.D. and D. Heitkamp. 1960. The accumulation of energy i n forest plantations i n B r i t a i n . J . Ecol. 48: 639-646. Ovington, J.D. and D.B. Lawrence. 1967. Comparative chlorophyll and energy studies of p r a i r i e , savannah, oakwood, and maize ecosystems. E c o l . 48: 515-524. Parr Manual. 1976. Instructions for the 1341 p l a i n jacket oxygen bomb calorimeter. Manual no. 147. Parr Instru. Co., Moline, 111.. 23 p.. Peterson, E.G., Y.H. Chan and J.B. Cragg. 1970. Above ground standing crop, leaf area, and c a l o r i c value i n an open clone near Calgary, Alberta. Can. J . Bot. 48: 1459-1469. P i r i e , N. 1968. Food from the f o r e s t s . New S c i . 21: 420-422. Plank, M.E. 1971. Red Alder. U.S. Dept. Agric. For. Serv. Pub. No. 215. 7 p.. Post, L.J. 1970. Dry-matter production of mountain maple and balsam f i r i n northwestern New Brunswick. Ecol. 51: 548-550. 118. Reiners, W.A. 1972. Structure and energetics of three Minnesota f o r e s t s . E c ol. Monogr. 42: 71-94. Ribe, J.H. 1974. A review of short rotation f o r e s t r y : with comments on the prospect of meeting future demands for forest products. Misc.. Pub. #160. L i f e S c i . and Agric. Exp. St., Univ. Maine, Orono. 51 p.. Rochow, J . J . 1974. Estimates of above-ground biomass and primary productivity i n a Missouri Forest. J . Ecol. 62: 567-577. Rodin, L.E. and N.I. Basilevic*. 1968. World d i s t r i b u t i o n of plant biomass. In F.E. Eckardt (ed.) Functioning of t e r r e s t r i a l ecosystems at the primary production l e v e l . Natural Resource Research 5: 45-52. Proc. Copenhagen Syrap. 1965. Pari s . UNESCO. Sat c h e l l , J.E. 1971. F e a s i b i l i t y study of an energy budget for Meathop Wood. In P. Duvigneaud (ed.) Productivity of forest ecosystems. Ecol. and Conservation 4: 619-630. Proc. Brussels Symp. 1969. Pari s . UNESCO. Satoo, T. 1968a. Materials f o r the study of growth i n stands. 7. Primary production and d i s t r i b u t i o n of produced dry matter i n a plantation of Cinnamomwm camphor a. B u l l . Tokyo Univ. Forestry. 64: 241-75. (Japanese summary). Satoo, T. 1968b. Primary production r e l a t i o n s i n woodlands of Pinus desniflora* In. H.E. Young (ed.) 119. Symposium on productivity and mineral c y c l i n g i s natural ecosystems, pp. 52-80. Ecol. Soc. Am., Univ. Maine Press, Orono, Maine. Schreiner, E.J. 1970. Mini-rotation forestry. USDA For. Serv. Res. Paper 174. 32p.. Scott, D;^MV, w« Ferguson, G. Hoyer, and M. Newton, i n press. Alder s i t e requirements and productivity. In D. Briggs et a l . (ed.) Alder u t i l i z a t i o n and manage-ment. Proc. U.W. Conf., Ocean Shores, Washington, 1977. Smith, J.H.G. 1968. Growth and y i e l d of red alder i n B r i t i s h Columbia. In J.M. Trappe et a l . (ed.) Biology of alder, pp. 273-286. Proc. N.W. S c i . Assoc. 1967 Meeting. Smith, J.H.G. 1971. Bases for sampling and simulation i n studies of tree and stand weights. In H.E. Young (ed.) IUFRO Forest Biomass Studies, pp. 131-149. Working group on forest biomass studies. Sect 25: Y i e l d and growth. L i f e S c i . and Agric. Exp. Sta., Univ. Maine, Orono. Smith, J.H.G. 1972. Tree siz e and y i e l d s i n juvenile red alder stands. U.B.C. Fac. For., Vancouver, B.C. Mimeo. 35 p.. Smith, J.H.G. 1973. Biomass of some young red alder stands. In H.E. Young (ed.) IUFRO Forest Biomass Studies 120. pp. 401-410. Working party on mensuration of the forest biomass. L i f e S c i . and Agric. Exp. Sta., Univ. Maine, Orano. Smith, J.H.G. 1975. Use of small plots can overestimate upper l i m i t s to basal area and biomass. Can. J . For. Res. 5: 503-505. Smith, J.H.G. i n press. Growth and y i e l d of red alder; e f f e c t s of spacing and thinning. In D. Briggs et a l • (ed.) Alder u t i l i z a t i o n and management. Proc. U.W. Conf. Ocean Shores, Washington, 1977. Smith, J.H.G. and D.S. DeBell. 1973. Opportunities for short rotation culture and complete tree u t i l i z a t i o n of northwestern tree species. For. Chron. 49: 1-4. Smith, J.H.G. and D.S. DeBell. 1974. Some e f f e c t s of stand density on biomass of red alder. Can. J . For. Res. 4: 335-340. Smith, N.J. i n press. Potentials of red alder as a source of energy. In D. Briggs e t a l . (ed.) Alder manage-ment and u t i l i z a t i o n . Proc. U.W. Conf., Ocean Shores, Washington, 1977. Steinbeck, K., R.G. McAlpine and J.T. May. 1972. Short-rotation culture of sycamore: a status report. J. For. 70: 210-213. Szego, G. 1976. Design, operation and economics of the energy plantation. In- Proc. Capturing the sun through 121. bioconversion. pp. 217-240. Wash. Centre f o r Metropolitan Studies, Washington, D.C. Szego, G.C., J.A. Fox and D.R. Eaton. 1972. The energy plantation. Paper No. 729168, Intersoc. Energy Convers. Eng. Conf., Proc. 7th Conf., San Diego, C a l i f . . Szego, G.C. and C.C. Kemp. 1973. Energy forests and f u e l plantations. Chemtech. 3:275-284. Szeicz, G. 1974. Solar ra d i a t i o n for plant growth. J . App. Ec o l . 11: 617-636. Tadaki, T. 1965. Studies on production structure of forests (VIII). Productivity of an Acacia mollissima stand i n higher stand density. J . Jap. For. Soc. 47: 384-391. Tadaki, Y. and Y. Kawasaki. 1966. Studies i n the production structure of for e s t s . IX. Primary productivity of a young Cryptomeria plantation with excessively high stand density. J . Jap. For. Soc. 48: 55-61. Tarrant, R.F. 1961. Stand development and s o i l f e r t i l i t y i n a Douglas-fir-red alder plantation. For. S c i . 7: 238-246. Tarrant, R.F. 1968. Some ef f e c t s of alder on the forest environment. In. J.M. Trappe et a l . (ed.) Biology of alder . p. 193. Proc. N.W. S c i . Assoc. 1967 Meeting, Washington. (Abstr.). 122. Tarrant, R.F. 1972. The role of alder i n improving s o i l f e r t i l i t y and growth of associated trees. In -A.B. Berg (ed.) Managing young forests i n the Douglas-fir region 3: 17-34. B i o l . Colloq., School For., O.S.U., C o r v a l l i s , Oregon. Tarrant, R.F., E.C. Lu, W.B. Bollen, and J.F. Franklin. 1969. Nitrogen enrichment of two forest ecosystems by red alder (Alnua rubra). U.S.D.A. Forest Serv. Res. Pap. PNW-76, 8 p. P a c i f i c Northwest Forest & Range Exp. Portland, Oregon. Tarrant* R.F. and R.E. M i l l e r . 1963. Accumulation of organic matter and s o i l nitrogen beneath plantations of red alder and Douglas-fir. Proc. S o i l S c i . Soc. Amer. 27: 231-234. Thomas, W.A. 1970. Energy turnover by dogwood Cornus ftorida L. trees. Oikos 21: 71-75. V a i l , C.W., M.D. Fraser and J.F. Henry. 1975. Higher productivity through energy plantations. Amer. Soc. Agric. Engineers. Winter Meeting, Chicago, 111. Paper no. 75-7502. 6 p.. Warrack, G.C. 1964. Thinning e f f e c t s i n red alder. Research Report, B.C.F.S., V i c t o r i a . 8 p.. Wassink, E.C. 1968. Light energy conversion i n photosynthesis and growth i n plants. In. F.E. Eckardt (ed.) Functioning of t e r r e s t r i a l ecosystems at the primary 123. production l e v e l . Natural Resources Research 5: 53-64. Proc. Copenhagen Symp. 1965. Pa r i s . UNESCO. Westlake, D.F. 1963. Comparison of plant productivity. B i o l . Rev. 38: 385-425. Whittaker, R.H. 1961. Estimation of net primary production of forest and shrub communites. Ecol. 42: 177-180. Whittaker, R.H. 1962. Net production r e l a t i o n s of shrubs i n the Great Smokey Mountains. Ecol. 44: 176-182. Whittaker, R.H. 1966. Forest dimensions and production i n the Great Smokey Mountains. Ecol. 47: 103-121. Whittaker, R.H. 1975. Communities and ecosystems. MacMillan 2nd Ed. 385 p.. Whittaker, R.H., G.E. Likens, and P.L. Marks. 1975. Scope and purpose of t h i s volume. In, ' H. L e i t h and R.H. Whittaker (ed.) Primary productivity of the biosphere, pp. 3-6. Springer Verlag. E c o l . Studies 14. Whittaker, R.H. and P.L. Marks. 1975. Methods of assessing t e r r e s t r i a l productivity. In H. Leith and R.H. Whittaker (ed.) Primary productivity of the biosphere, pp. 55-188.Springer Verlag. Ecol. Studies 14. 124. Whittaker, R.H. and G.M. Woodwell. 1968. Dimension and production r e l a t i o n s of trees and shrubs i n the Brookhaven Forest, New York. J . Ecol. 56: 1-25. Whittaker, R.H. and G.M. Woodwell. 1969. Structure, production and d i v e r s i t y of the oak-pine forest at Brookhaven, New York. J . Ecol. 57: 155-174. Whittaker, R.H. and G.M. Woodwell. 1971. Measurement of net primary production of fo r e s t s . In P. Duvigneaud (ed.) Productivity of forest ecosystems. E c o l . and Conservation 4: 159-175. Proc. Brussels Symp. 1969. P a r i s , UNESCO. Witkamp, M., and van der D r i f t . 1961. Breakdown of forest l i t t e r i n r e l a t i o n to environmental fa c t o r s . Plant and S o i l . 15: 295-311. Woodwell, G.M. 1967. Radiation and the patterns of nature. S c i . 156: 461-470. Worthington, N.P., F.A. Johnson, G.R. Staebler and W.J. Lloyd. 1960. Normal Y i e l d Tables for Red Alder. U.S. For. Serv. PNW For. and Range Exp. Sta. Res. Paper 36. 31 p.. Worthington, N.P., R.H. Roth and E.E. Matson. 1962. Red alder, i t s management and u t i l i z a t i o n . U.S. Dept. Agric. Misc. Pub. 881. 44 p.. Yapp, W.B. 1972. Production, p o l l u t i o n , protection. Wykeham Pub. (London) Ltd. Science Series 19. 183 p.. 125. Young, H.E. 1964. The complete tree concept - a challenge and an opportunity. Proc. Soc. Amer. For.: 231-233. Zar, J.H. 1968. Calculation and miscalculation of the allometric equation as a model i n b i o l o g i c a l data. Bioscience 18: 1118-1120. Zavitkovski, J . 1976. Ground vegetation biomass, production, and e f f i c i e n c y of energy u t i l i z a t i o n i n some northern Wisconsin forest ecosystems. E c o l . 57: 694-706. Zavitkovski, J . and M. Newton. 1971. L i t t e r f a l l and l i t t e r accumulation i n red alder stands i n Western Oregon. Plant and S o i l s . 35: 257-268. Zavitkovski, J . and R.D. Stevens. 1972. Primary productivity of red alder ecosystems. Ecol. 53: 235-242. 126. APPENDIX I 127. LIST OF COMMON AND LATIN NAMES Acacia mollisaima W i l l d . Acacia dealbata Link Alnua glutinosa (L.) Gaertn. Ainus rubra Bong. Athyrium felix-femina (L.) Roth. Be tula papyrifera Marsh Betula pendula Roth. Castanopsis cuepidata Schottky Cryptomeria japonica (L.f.) D.Don Gaultheria shallon Pursh Holcu8 lanatu8 L. Hylocomium splendens Hewd. laothecium atoloniferum Brid. Liriodendron tulipifera L. Phellinu8 (Pbria) weirii (Murr.) Gilbertson Polystricftum munitum (Kaulf.) P r e s l . Populus trichocarpa T.& G. Prunu8 emarginata (Doug.) Walp. Prunus pensylvanica (L.) P8eudot8uga menziesii (Mirb.)Franco Quercus petraea L i e b l . Black wattle S i l v e r wattle Black, alder Red alder Lady-Fern Paper bir c h S i l v e r birch Japanese evergreen chinkapin Japanese red cedar S a l a l Velvet grass Moss sp. Moss sp. Tulip-tree Laminated wood-rot Sword-fern Black cottonwood : B i t t e r cherry Pin cherry Douglas-fir Sessile oak 128. Rubus parviflora Nutt. Rubus speotabilis Pursch, Rubus ursinus C.& S. Salix laeiandra Benth. Sambuous raoemosa T.& G . Stokesiella praelonga (Hewd.)Robins. Tanacetum nutallii T.& G. Thuja plioata Donn Triohoderma viride Fr. Tsuga heterophylla (Raf.) Sarg. Thimbleberry Salmonberry T r a i l i n g blackberry Willow Red elderberry Moss sp. Chicken sage Western red ceder. Fungal sp. Western hemlock 129. APPENDIX I I 130. APPENDIX II BOMB CALORIMETRY Standardization of bomb Hm + e, + e~ w = i £ t W = water factor (cal/°F or cal/°C) H = combustion heat of benzoic acid m = max of benzoic acid i n grams t = net corrected temperature r i s e e^ = correction for n i t r i c acid formation e^ = correction for heat of combustion of the f i r i n g wire i n c a l s . For bomb 1108-101A7637 and calorimeter 1341-3054 W»1344 cal/°F (31 March, 1971). Latest W=1373±3 cal/°F (n=6) (23 Nov., 1976) . Gross combustion heat tW - e, - e_ Hg = where t=tc-ta-r. (b-a)-r.(c-b) 3 m 1 2 Hg = gross heat of combustion m = mass of combusted material i n grams t = temperature at time of f i r i n g , corrected for thermometer error t c = temperature at time c, corrected for thermometer error 131. = rate (units/minute) of temperature r i s e i n 5 mins before f i r i n g r 2 = rate (units/minute) of temperature r i s e i n 5 mins a f t e r time c a = time of f i r i n g b = time when temperature r i s e reaches 60% of t o t a l c = time when temperature r i s e becomes constant N.B. Temperature readings on thermometer should be corrected by the stem factor v i z . - difference between reading and actual temperature. The best method for computing temperature r i s e i s to measure temperature to the nearest 0.005°F at 1, 3 and 5 mins before f i r i n g . Then for 45, 60, 75, 90 and 105 sees aft e r f i r i n g to nearest 0105°F. Then for 5, 6...n mins a f t e r f i r i n g to nearest 0.005°F where n i s temperature at which r i s e becomes steady or when temperature ceases to r i s e . For red alder t h i s was usually between 12 and 14 minutes. 132. APPENDIX I I I 133. Formulae for back-transformation of standard errors i n the logarithmic and hyperbolic form Logarithmic 2 2(Y.-Y.) S E = = e n-m-1 observed Y anti-logarithm of estimated Y no. observations no. independent variables Hyperbolic y = _ i i (a+b-l/x) where x = observed data Y.= observed ,Y where = Y. = l n = m = 134. SIMPLE CORRELATION COEFFICIENTS FOR BOLE BIOMASS AND PRODUCTION BY INDEPENDENT VARIABLES. n = 72 Total Wood Bark To t a l Wood Bark biomass biomass biomass production production production Red .944 .942 .926 .934 .928 .926 Dbh .958 .953 .960 .932 .922 .960 Cw .666 .670 .620 .668 .668 .620 Ht .849 .857 .770 .871 .875 .770 Cd .318 .315 .326 .360 .360 .327 D3 .571 .574 .535 .530 .526 .534 Hdc .308 .303 .333 .247 .236 .333 R 2h/100 .940 .974 .942 .944 .959 .939 D 2h/100 .972 .973 .971 .964 .971 .971 135. SIMPLE CORRELATION COEFFICIENTS FOR CROWN BIOMASS AND PRODUCTION BY INDEPENDENT VARIABLES. N = 66 Tota l Branch Leaf Total Branch biomass biomass biomass production production Red .832 .820 .810 .932 .956 Dbh .841 .828 .822 .897 .872 Cw .677 .677 .630 .681 .657 Ht .688 .688 .639 .761 .805 Cd .243 .250 .206 .249 .268 D3- .385 .379 .376 .494 .565 Hdc .164 .148 .205 .186 .143 R2h/100 .934 .909 .771 .926 .986 D2h/100 .801 .792 .780 .907 .917 H/C . 380 .374 .369 .458 ( R 2 h ) 2 .700 .693 .675 .953 ( D 2 h ) 2 .782 .772 .749 .900 Rcdxht .808 .804 .773 .964 Dbhxht .813 .808 .778 .904 Red 2 .816 .804 .798 .976 Dbh 2 .802 .832 .829 .887 Ht/CW -.061 -.057 -.053 .077 CdxCW2 .393 .386 .404 .438 Cd/CW -.170 -.168 -.165 -.110 CdxCW .539 .553 .475 .535 Rcdxcd .633 .639 .589 .713 Dbhxcd .627 .631 .587 .647 Leaf (as f o r l e a f biomass) 136T APPENDIX IV MULTIPLE COVARIANCE ANALYSIS BETWEEN CROWDED AND UNCROWDED STANDS FOR RED ALDER BOLE COMPONENTS ( r ^ (crowded) = 40, n 2 (uncrowded) = 32) a. Stem Wood Biomass b. Stem Bark Biomass Source of V a r i a t i o n DF SS MS F Slopes Residual f o r model with common surface 68 86.5508 Residual f o r u n r e s t r i c t e d model 66 76.6304 1. 116107 Difference 2 9.9204 4. 96021 4. 272 * Intercept Residual f o r model with common surface 69 96.4055 and i n t e r c e p t Residual f o r model with common surface 68 86.55081 1. 27281 Difference 1 9.85474 9. 85474 7. 743 * DF SS MS F 68 4.64307 .06828 66 4.19064 .0634945 2 .452429 .226214 3.563 * 69 4.64305 68 4.64307 .0682803 .002 NS 1 .00015 .00015 c. Stem Wood NPP d. Stem Bark NPP Source of V a r i a t i o n DF SS MS F Slopes Residual f o r model with common surface 68 13.3373 Residual f o r u n r e s t r i c t e d model 66 12.6915 .192296 Difference 2 .645721 .322861 1 .679 NS Intercept Residual f o r model with common surface and in t e r c e p t 69 14.0161 Residual f o r model with common surface 68 13.3373 .196136 Difference 1 .678787 .678787 3 .461 NS DF SS MS •F 68 .104313 66 .0940806 .00142546 2 .0102323 .00511616 3 .589 * 69 .104321 68 .104313 .00153401 0 .006 NS 1 .00000858 .00000858 MULTIPLE COVARIANCE ANALYSIS BETWEEN CROWDED AND- UNCROWDED STANDS FOR CROWN COMPONENTS (n^ (crowded) 37, (uncrowded) = 29) Branch Biomass b. Leaf Biomass Source of Variation DF SS MS F : DF . :. ss MS F Slopes Residual for model with common surface 62 119.449 62 12.8059 Residual for unrestricted model 60 108.613 1 .81022 60 11.1648 0 .186079 4 .410 * Difference 2 10.8357 5 .41784 2 .993 NS" 2 1.64114 0 .82057 Intercept Residual for model with common surface and intercept 63 125.977 63 13.9859 Residual for model with common surface 62 119.449 1 .92659 62 12.8059 0 .206547 Difference 1 6.52846 6 .52846 3 .389 NS 1 1.17996 1 .17996 5 .713 * Branch NPP Source of Variation DF SS MS F Slopes Residual for model with common surface 62 4 .81615 Residual for unrestricted model 60 4 .55772 0 .075962 Difference 2 0 .258426 0 .129213 1.701 NS Intercept Residual for model with common surface and intercept 63 4 .82756 Residual for model with common surface 62 4 .81615 0 .0776798 Difference 1 0 .0114136 0 .0114136 0.147 NS NS * a not s ignif icant ly different significantly different 0.05 00 ANALYSIS OF VARIANCE ON RED ALDER ECOSYSTEM CALORIC VALUES COMPARISON OF CALORIC VALUES IN: .'(I) JULY (4) (5) Source DF Sum SQ Mean SQ F-value Treatment 13 3496200 268940 36.939 Error 28 203860 7280.7 Total. 41 3700100 SEPTEMBER Source DF Sum SQ Mean SQ F-value Treatment 7 1160300 165750 153.17 Error 16 17315 1082.2 Tota l 23 1177600 NOVEMBER -Source DF Sum SQ Mean SQ F-value Treatment 7 1202400 171770 458.36 Error 16 5995.9 374.74 Tota l 23 ALL THREE MONTHS Source DF Sum SQ Mean SQ F-value Treatment 7 2385400 340780 92.909 Months 2 76972 38486 10.493 TxM 14 1452100 103720 28.279 Error 48 1760600 3667.8 To t a l 71 4090600 LESSER VEGETATION Source DF Sum SQ Mean SQ F-value Treatment 5 1169000 233810 45.664 Error 12 61442 5120.2 To t a l 17 1230300 * = s i g n i f i c a n t l y d i f f e r e n t a = 0.05 140. APPENDIX V 141. 1 C Three dimensional computer programme 2 C Written by Jim McPhalen and Nick Smith, May 1977 3 C Uses UBC Plot subroutines 4 C Suggested r o t a t i o n : THETA=20 5 C PHI =330 6 C To get out of rotation subroutine use command:-99 7 Real X(50), Y(50), Z(50), C(3) Data R/.17453293E-1/ 9 C 10 C Orgin of p l o t . 11 C 12 XREF=8. 13 YREF=3. 14 CALL DASHLN (0.25, 0.25, 0.25, 0.25) 15 C 16 C Scale factors (inches/unit) 17 C 18 XSC=.458 19 YSC=.681 20 ZSC=-1.335 21 C(1)=0.0 22 C(2)=.439288 23 C(3)=.0226372 24 C 25 C Read data 142. 26 C 27 XMIN=9999. 28 YMIN=9999. 29 ZMIN=9999. 30 XMAX=0. 31 YMAX=0. 32 ZMAX«=0. 33 N=l 34 101 Read(4,100,End=991 X(N), Z (N) , Y(N) 35 100 Format (3F7.3) 36 IF(X(N) .GT. XMAX) XMAX=X (N) 37 IF(Y(N) .GT. YMAX) YMAX=Y(N) 38 IF(Z(N) .GT. ZMAC) ZMAX=Z (N) 39 IF(X(N) ,LT. XMIN) XMIN=X(N) 40 IF(Y(N) .LT. YMIN) YMIN=Y(N) 41 IF(Z(N) .LT. ZMIN) ZMIN=Z(N) 42 N=N+1 43 GO TO 101 44 99 CONTINUE 45 N=N-1 46 401 CONTINUE 47 CALL SYMBOL (XREF-3.0,YREF-.42, 0.14, 'FIGURE:',0.0,7) 48 CALL SYMBOL (XREF-3.0,YREF-.7,0.14,'THREE DIMENSIONAL RELATIONSHIP BETWEEN BRANCH BIOMASS AND',0.0,571 1 4 3 . 4 9 C A L L S Y M B O L ( X R E F - 3 . 0 , Y R E F - . 9 8 , 0 . 1 4 , ' B I O M A S S I N D I C E S F O R 8 T O 1 0 Y R R E D - A L D E R S A M P I J E T R E E S I N ' , 0 . 0 , 5 6 1 5 0 C A L L S Y M B O L ( X R E F - 3 . 0 , Y R E F - 1 . 2 6 , 0 . 1 4 , ' C R O W D E D C O N D I T I O N S ' , 0 . 0 , 1 8 1 5 1 C A L L S Y M B O L ( X R E F - . 5 , Y R E F - 1 . 2 6 , 0 . 1 0 5 , * D I A M E T E R S I N C M , H E I G H T , D E P T H A N D W I D T H I N M E T R E S ' , 0 . 0 , 4 8 1 5 2 C A L L S Y M B O L ( X R E F - 2 . 0 , Y R E F - 1 . 5 4 , 0 . 1 0 5 , ' Y = 4 3 9 2 8 8 ( X l ) + . 0 2 2 6 3 7 2 ( X 2 ) . R 2 = . 6 7 2 S E = 1 . 4 0 8 K G N = 6 6 ' , 0 . 0 , 5 1 ) 5 3 C A L L S Y M B O L ( X R E F - 2 . 0 , Y R E F - 1 . 8 2 , 0 . 1 0 5 , ' X = O B S E R V E D D A T A P O I N T S R C D = R O O T C O L L A R D I A M ' , 0 . 0 , 4 5 ) 5 4 C A L L S Y M B O L ( X R E F - 2 . 0 , Y R E F - 1 . 9 6 , 0 . 1 0 5 , ' 1 = L I N E J O I N I N G O B S E R V E D D A T A A N D R E G R E S S I O N S U R F A C E ' , 0 . 0 , 5 1 ) 5 5 W R I T E ( 6 , 1 0 2 ) 5 6 1 0 2 F O R M A T ( ' D E N T E R R O T A T I O N . ( T H E T A , P H I ) ? ) 5 7 C A L L F R E A D ( ' S C A R D S * , ' 2 Y R : ' , T H E T A , P H I ) 5 8 I F ( T H E T A . E Q . - 9 9 . ) G C T O 4 0 4 5 9 C 6 0 C P L O T A X E S . 6 1 C 6 2 C A L L P L O T ( X R E F , Y R E F , 3 ) 6 3 C A L L T R A N S ( X M A X , 0 . , 0 . , P H I , T H E T A , X S C , Y S C , Z S C , X R E F , Y R E F , X T , Y T ) 144. 64 XX=XT-XREF 65 YY=YT-YREF 66 XINCH=SQRT(XX*XX + YY*YY) 67 SCALE=XMAX/XINCH 68 IXINCH=IFIX(XINCH) 69 XINCH=FLOAT(IXINCH) 70 RAD=ATAN(YY/XX) 71 DEG=RAD/R 72 CALL AXIS(XREF,YREF,*(DBH SQUARED X HEIGHT)/100. (XI)',-31,XINCH,DEG,0.,SCALE) 73 XX=XINCH*COS(RAD) 74 YY=XINCH*SIN(RAC) 75 XX=XREF*XX 76 YY=YREF+YY 77 CALL PLOT(XX,YY,3) 78 CALL PLOT(XT,YT,2) 79 CALL PLOT(XREF,YREF,3) 80 CALL TRANS(0.,0.,ZMAX,PHI,THETA,XSC,YSC,ZSC, XREF,YREF,XT,YT) 81 Xl=XT 82 Y1=YT 83 XX=XT-XREF 84 YY=YT-YREF 85 XX=ABS(XX) 86 YY=ABS(YY) 87 XINCH=SQRT(XX*XX + YY*YY) 145. 88 SCALE=-ZMAC/XINCH 89 DEG=AT ANY(YY/XX)/R 90 DEG=-DEG 91 CALL AXIS(XT,YT,'(CROWN DEPTH/CROWN WIDTH.(X2)1, -29,XINCH,DEG,ZMAX,SCALE) 92 CALL PLOT(XREF,YREF,3) 93 CALL PLOT(XT,YT,2) 94 CALL PLOT(XREF,YREF,3) 95 XX=XMAX*XSC+XREF 96 CALL TRANS(XMAX,0.,ZMAX,PHI,THETA,XSC,YSC,ZSC, XREF,YREF,XT,YT) 97 X3=XT 98 Y3=YT 99 CALL AXIS(XX,YT,'DRY WEIGHT (KILOGRAMS).(Y)', -26,YSC*YMAX,90.,0.,1./YSC) 100 C 101 C RETURN TO ORGIN. $02 C 103 CALL .PLOT(XREF,YREF,3) 104 YY=C(1) 105 CALL TRANS(0.,YY,0.,PHI,THETA,XSC,YSC,ZSC,XREF, YREF,XT,YT) 106 X4=Xt 107 X4=YT 108 XX4=XT 109 YY4=YT :i46. 110 CALL PLOT(XT,YTf2) 111 C 112 C PLOT SIDE 1 OF PLANE. 113 C 114 YY=C(1) + C(2)*XMAX 115 ZZ=0. 116 XX=1XMAX 117, CALL TRANS (XX , YY, ZZ, PHI, THETA ,XSC , YSC, ZSC, XREF, YREF,XT,YT) 118 XX2=XT 119 YY2=YT 120 CALL PLOT(XT,YT,2) 121 XSAVE=XT 122 YSAVE=YT 123 CALL TRANS(XX,0.,0.,PHI,THETA,SCS,YSC,ZSC, XREF,YREF,XT,YT) 124 CALL PLOT(XT,YT,2) 125 C 126 C PLOT PORTION OF "HIDDEN" AXIS. 127 C 128 XX1=XT 129 YY1=YT 130 CALL TRANS(XMAX,0.,ZMAX,PHI,THETA,XSC,YSC,ZSC, XREF,YREF,XT,YT) 131 XX3=XT 132 YY3=YT 147. 133 S1=(YY3-YY1)/(XX3-XX1) 134 S2=(YY2-YY4)/(XX2-XX4) 135 C0NST=YY2*YY1 136 XT=C0NST/(S1-S2) 137 YT=YY1+X1*XT 138 XT=XT+XX1 139 CALL PLOT(XT,YT,2) 140 CALL PLOT(XX3,4) 141 CALL PLOT(XSAVE,YSAVE,3) 142 C 143 C PLOT SIDE 2 OF PLANE. 144 C 145 YY=C(1) + C(2)*XMAX + C(3)*ZMAX 146 ZZ=ZMAX 147 XX=XMAX 148 CALL TRANS (XX,YY,ZZ,PHI,THETA,XSC,YSC,ZSC,XREF, XT,YT) 149 CALL PLOT(XT,YT,2) 150 XSAVE=XT 151 YSAVE=YT 152 CALL PLOT(XX3,YY3,4) 153 CALL PLOT(XSAVE,YSAVE,3) 154 C 155 C PLOT SIDE 3 OF PLANE. 156 C 148. 157 YY=C(1) + C(3)*ZMAX 158 XX=0. 159 ZZ=ZMAX 160 CALL TRANS(XX,YY,ZZ,PHI,THETA,XSC,ZSC,XREF,YREF, XT,YT) 161 CALL PLOT(XT,YT,2) 162 X2=XT 163 Y2=YT 164 XSAVE=XT 165 YSAVE=YT 166 CALL TRANS(0.,0.,ZMAX,PHI,THETA,XSC,YSC,ZSC, XREF,YREF,XT,YT) 167 CALL PLOT(XT,YT,2) 168 C 169 C PLOT PORTION OF "HIDDEN" AXIS. 170 C 171 S1=(Y3-Y1)/(X3-X1) 172 S2=(Y4?Y2)/(X4-X2) 173 CONST=Y2-Yl 174 XT=CONST/(Sl-S2) 175 YT=Y1+XT*S1 176 XT=XT+X1 177 CALL PLOT(XT,YT,2) 178 CALL PLOT(X3,Y3,4) 179 CALL PLOT(XSAVE,YSAVE,3) 149. 180 C 181 C PLOT SIDE 4 OF PLANE. 182 C 183 XX=0. 184 YY=X(1) 185 XX=0. 186 CALL TRANS(XXfYY,ZZ,PHI,THETA,XSC,YSC,ZSC, XREF,YREF,XT,YT) 187 CALL PLOT(XT,YT,2) 188 C 189 C PLANE IS PLOTTED. NEW PLOT OBSERVATIONS. 190 C 191 DD 400 1=1,N 192 XX=XK1) 193 YY=Y(1) 194 ZZ=Z(1) 195 CALL TRANS(XX,YY,ZZ,PHI,THETA,XSC,YSC,ZSC, YREF,XT,YT) 196 CALL SYMBOL(XT,YT,.07,4,0.,-1) 197 CALL PLOT(XT,YT,3) 198 YY=C(1)+C(2)*X(1) + C(3)*Z(1) 199 CALL TRANS(XX,YY,ZZ,PHI,THETA,XSC,YSC,ZSC, XREF,YREF,XT,YT) 200 CALL PLOT(XT,YT,2) 201 400 CONTINUE 150. 202 CALL MAXMX(XX) 203 XX=XX+3 204 CALL PLOT(XX,0.,-3) 205 GO TO 401 206 404 CONTINUE 207 CALL PLOTND 208 RETURN 209 END 210 C 211 C 212 SUBROUTINE TRANS(X,Y,Z,PHI,THETA,XSC,YSC,ZSC, XREF,YREF,XT,YT) 213 CATA R/.17453293E-1/ 214 DATA SPHI,STHETA/-1.E99,-1.E99/ 215 C 216 C SUBROUTINE TO ROTATE A PLANE ABOUT ITS AXES. 217 C 218 CALCULATE CONSTANTS. 219 C 220 C R.H. CO-ORDINATE SYSTEM - Z COMING "OUT" OF THE PAGE. 221 C 222 C ROTATION: 223 c (1) THETA - CLOCKWISE ABOUT X-AXIS 224 C (2) PHI - CLOCKWISE ABOUT Y-AXIS 225 C 151. 226 IF(PHI,EQ. SPHI .AND. THETA .EQ. STHETA ) GO TO 10 227 SPHI=SIN(R*PHI) 228 CPHI=COS(R*PHI) 229 STHETA=SIN(R*THETA) 230 CTHETA=COS(R*THETA) 231 A11=CPHI 232 A13=SPHI 233 A21=STHETA*SPHI 234 A22=CTHETA 235 A23=STHETA*CPHI 236 SPHI=PHI 237 STHETA=THETA 238 10 239 C 240 C ROTATE. 241 C 242 XX=X*XSC 243 YY=Y*YSC 244 ZZ=Z*ZSC 245 XT=A11*XX+A13*ZZ+XREF 246 YT=A21*XX+A23*ZZ+A22*YY+YREF 247 RETURN 248 END 

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