THE EFFECT OF PAPER BIRCH (BETULA PAPYRIFERA MARSH) ROOT
REINFORCEMENT ON TERRAIN STABILITY IN BRITISH COLUMBIA
by
Kirstin Campbell
B. Sc. University of Victoria, 1998

THESIS SUBMITTED IN PARTIAL FULFILLMENT OF
THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE
m

NATURAL RESOURCES AND ENVIRONMENTAL STUDIES

©Kirstin Campbell, 2001
THE UNIVERSITY OF NORTHERN BRITISH COLUMBIA
August 2001

All rights reserved. This works may not be
reproduced in whole or in part, by photocopy or
other means, without the permission of the author.

Abstract
Management of paper birch in mixedwood stands is a sustainable forest management practice. In
addition to the ecological and economical benefits of mixedwoods, paper birch trees can
maintain or enhance slope stability. This thesis attempted to quantify the contribution of birch
root reinforcement in BC to slope shear resistance. The objectives of this thesis were to
determine the: 1) genetic variation in paper birch root reinforcement, 2) environmental variation
in root reinforcement between birch and pine, and 3) differences in root reinforcement between
birch and pine. The first study compared the contribution of birch and pine roots (from different
populations growing in three soil types) to soil shear resistance using two controlled environment
shear tests (Sonotube and Polytube Experiments). The second study (Tree Uprooting
Experiment) compared the vertical uprooting resistance of birch and pine growing in different
soil types at three field study sites. The third study (Genecology Experiment) determined the
variation of four birch populations growing at one location. Results from the tube experiments
found that the roots of birch and pine trees contributed to a significant increase in shear strength,
regardless of soil type. At a depth of 20-44 em, paper birch increased shear strength by as much
88%, while pine increased strength by as much as 61%. There was little variation in root
reinforcement among the six birch populations in the Sonotube Experiment, which suggested
that these trees were from one generalist population rather than six specialist populations. Soil
texture affected the root reinforcement of birch and pine in the Polytube Experiment~ both
species had the highest root reinforcement in coarse textured sand and the least root
reinforcement in medium textured silt. The limiting factor in root reinforcement, in this case, was
attributed to a lack of water and nutrients in the silt soil. In the Tree Uprooting Experiment, birch
trees had 50% greater resistance to uprooting than did pine trees. Small diameter birch and pine
at Aleza Lake had greater uprooting resistance than birch and pine at other field sites. However,
larger diameter trees at Gregg Creek and Red Rock had greater uprooting resistance than similar
size trees at Aleza Lake. Soil strength and moisture content may have accounted for the
uprooting resistance differences among diameter classes at Aleza Lake. Results from the
Genecology Experiment showed that the Skeena population had the greatest uprooting
resistance, and the greatest height, diameter, and root biomass compared to the other three
populations. The results from companion trials, and from the uprooting tests suggested that
Skeena trees represent a generalist population. In the same experiment, the nursery where the
trees were grown impacted uprooting resistance, even after five years growing in the field. The
results from this study reconfirmed the significant length of time nursery can affect field
performance. Significant findings arising from this thesis were that: 1) birch saplings have
greater root strength than pine across all soil types, 2) root system structure has an important role
in root reinforcement between tree species, 3) root reinforcement is maximized by birch and pine
when growing in freely drained, cohesionless sandy soil, and 4) further study of birch
genecology is needed to identify generalist, high performing populations such as Skeena.
Overall, managing for mixedwoods in BC has both ecological and economical benefits,
including enhanced slope stability.

l1

Table of Contents
ABSTRACT ........................................................................................................................................................... ll
TABLE OF CONTENTS.......••........................••.............•..•.............••••.•.•••••..•..............•......•••••...•......................•. ill
LIST OF FIGURES .............................................................................................................................................. VI
LIST OF TABLES ...•.....•...•..•.•••....•.••••.•••...•......•••......•.•••.••.......•...••.....••••••.....•••••••••••.••••..••....••..•..•.•.••.•..•.•..•.•• VIll
ACKNOWLEDGMENTS ..........•....••.••••••.•.••••.....................•..••••••••••••.•.•......••.....•...........•..•••.•••••••.•••...•••.•.••••••.•.. X
CHAPTER I INTRODUCTION AND LITERATURE REVIEW .•••.•••••••••••••••••••••••••••••••••••.••••••••••.•••••.••••••••••••• l
1.1 INIRODUCTION ......... ...... ........... .... ... .... ... ... ............ .. ... ..... ... ..... ..... .... ... ... .. ....... ... ..... ... .............................. ..... 1
1.1.1 Objectives ................ ...... .......................................................................... ............................................... 2
1.2 SURFACE EROSION .. ....................................... ... ....... ........ ..................... .... .................. ......... .. ....................... .. 2
1.2.1 Density and Spatial Distribution of Vegetation ............ ........................ ................................................... 2
1.2.2 Type of Vegetation ...... .... .......... ......... ................... .. ......................... ........... ................... ............. .... ... .... . 3
1.3 MASS FAILURE ............................. ... ... .... .. ...................... ................ ... .. ..... .. ......................................... ... ........ 4
1.3.1 Hydrological Effects of Vegetation ... ... ............ ... ... ................................... .......... ........... ..... .................... 5
1.3.2 Mechanical Effects- the Contribution ofRoots to Soil Shear Strength ......................... ............................ 7
1.3.3 Summary ofMass Stabi/ity........... ...... ........................... ................. ............. ........ .................... .............. /4
1.4 PAPER BIRCH ............ ... .... .... .... ... .. .. .. ...... .. .............. .... .................................................................................. 15
1. 4.1 Importance of Birch-Conifer Mixedwoods .. ................ .... .............. ..... ... ...... .......... ........ ... ......... .. .......... 16
1.4.2 Genecology ofPaper Birch ................................................................................................................... 17

1. 5 PURPOSE OF THIS RESEARCH .... .... ... .... ... .... .... ...... ............................ ........................ .............. ........... ............ 19
1.6 TABLES AND FIGURES .... ........................... .. .................................................................................................. 22

CHAPTER 2 SHEAR STRENGTH OF SOIL PERMEATED WITH THE ROOTS OF PAPER BIRCH AND
LO DG EPO LE PINE .•.••.•.••.•.••....••••.••••••....••••.••.•••.••.•...•...•....••.....••.••....•.•••...••••....••...••••.•..••....•••••.....•••••.....•••..•• 23
2.1 INIRODUCTION ......... ... ........... ..................... ... .......... .... .. .. ....... ... ....... .............. .. ... ... .. .. ... ... ... .... ... ..... ......... ... 23
2.1.1 In Situ Tests .. .............................................................. ......... ...................................................... ........... 23
2.1.2 Laboratory Tests .................................... ........................... ......... .. .... ....... ... .. ......... .. .... .......... ....... ......... 24
2.1. 3 Effect of Soil Physical Properties on Root Reinforcement ..................................................................... 26
2.1.4 Shear Tests Using Paper Birch and Lodgepole Pine ............................................................................. 28
2 .2 METHODS ............................................................................ ..... .................................................................... 29

2. 2.1 Experimental Designs and Procedures........................... ....................................................................... 29
2.2.2 Shear Device .............. ........ ...... ... ..... .............. ...................................................................................... 33
2.2.3 Statistical Methods ............................................................................................................................... 36
2.3 RESULTS ....................................... ...................................................................................... ...................... .. .. 38
2.3.1 Sonotube Experiment ............................................................................................................................ 38
2.3.2 Polytube frperiment .. ............................. ..... .. .................. ........ ..... ...... ......... .......... ............................... 39
2.3.3 Residual Analyses ................ ............... ............. .............. ....................................................................... 41

2.4 DISCUSSION ... ... ..... ..... ..... .................. . ..... .. ... .... .... . ... ........ .. .......... .... .......... ... ....... .............................. ......... . 41

2 .5 TABLES AND FIGURES ........... ........ .. ....... .. .... ................................. .. .......... ... ... ...... ..... .... .... .... ..... .................. 47

CHAPTER 3 VERTICAL TREE UPROOTING OF PAPER BIRCH AND LODGEPOLE PINE: A CASE
STUDY OF THREE FIELD LOCATIONS .••••...••••...•.....••.••.•••••.••••••.••••••••••••••••••••••••••••••••••••••••••.....•••....•••......• 61
3.1 INIRODUCTION ......... ..... .... .. ......... .. ... ... ........ .... ...... ............. ...................... .......... ....... .................................. 61
3. 1.1 Tree Stability Analyses.............................................................. ............................ ............................... 62
3.1.2 Root Reinforcement of Paper Birch and Lodgepole Pine ..... ................... ......... ................................ ...... 63
3.2 METHODS ....... ......... ...... ... .... ............. ............... ........ ..... ...... .... .............. ...... ................................... . ..... .... .... 63
3. 2.1 Experimental Design and Procedures ......... .. ............................................. .. ............... .... ...................... 63
3.2.2 Statistical Methods ........................................................... ........................ ............................................ 67
3.3 RESULTS .. ........... ..... .... ..... ... ..... ......... .. ... .. ... ............ ........ ... ... .... ....... ....... .... ............ ...... .. ..... .. ...................... 69
3.3.1 Final Model Selection ..... ............................ ...... .................... ...... ........... .. .......... ...................... ............. 69
Ill

3.3.2 Results From Statistical Analyses ........ ........ ... ..... ....................... ... .... .... ... .. ........... ........ ...... ...... .... ....... 70
3.4 DISCUSSION .... .. ... .. ... ... ... ...... ...... ....... .... ..... .. ............... .. ............................. ... .. ... ..... ... .... ... .. .. .... ... ...... ... ....... 71
3 .5 FIGURES AND TABLES .......... .. ..... .... ..... ....... .. ...... ... .................................... ............. ... ...... .. .. .. ........... .. .... ...... 76

CHAPTER 4 VERTICAL UPROOTING RESISTANCE OF PAPER BIRCH SEED SOURCES GROWN
UNDER DIFFERENT NURSERY CULTURES, FIVE YEARS AFTER PLANTING .................................... 86
4 . 1 INlRODUCTION ............................. ............. . ... ................. .. ... ... .. .. ... .. .. .. .... .... ...... .. .... ......... .... .... .................... 86

4.1.1 Birch Genecology Studies ............................... ...................................................................................... 8 7
4.1.2 This Study .. ...... .. ....... .... .. ........... ... ...... .... ... .... ... ........ .... .................... ..... ................. ................ .... .......... 88

4 .2 METHODS ..................................... .... ... ..... .... .. ... ... .... .. ........ ... .. ······... ................. ..... ..... ... ... ......... ....... ........... 89

4.2.1 Experimental Methods ...... .. ................... ....... ..... ...... ...... ... ........ ................... ..... ...... ...................... ........ 89
4.2.2 Statistical Methods ................................ ............. .......................................... ........................................ 91

4 .3 RESULTS ............ ..... ...... ....... ................ ....... .............. ........................ ....... ....... ............................... .......... .... . 92

4.3.1 Final Model Selection ........................................................................................................................... 92
4.3.2 Results from the Statistical Analyses ................................... .............................................. ....... ............. 93

4 .4 DISCUSSION ...................... ..... .. .......... ... .... ....... ... ..... ... .... ... .. ......... ........ .. ........ ....... .......... ............. .. ...... .. .... .. 94

4. 4.1 Seed Sources.................................................................................. ...... ...... .... .. ..... .............. .................. 94
4. 4. 2 Nursery and Stocktype ............................................................. ............................................................ . 9 7

4 .5 TABLES AND FIGURES ... .. ..... .... ........ .. .................... ... ............................. ...... .. ......... ..... .... .. .. .... ..... ... .. ... ....... . 99

CHAYfER 5 DISCUSSION, RECOMMENDATIONS, AND CONCLUSIONS ............................................ 104
5 . 1 DISCUSSION ..... ....... .. .. ....... .. .. ..... ... ... ... .... .... ... ......... .................. .... ...... .. ........... .. .... .................................... 104

5.1.1 The Effects ofEnvironment and Genetics on Root Reinforcement ....................................................... 104
5.1.2 Summary of Key Findings ....................................................................... ................... ........ ............ ..... 108
5.1.3 Experimental Design- A Review ofBenefits, Liabilities, and Future Directions................................... 108

5 .2 RECOMMENDATIONS ....... ..... ... ..... .. ........................... ..... .... ..... ....... .... ... .... ..... ............ ............... .. .... ... .. ....... 112
5.3 CONCLUSIONS ......... ......... ... ..... ........................ ... ........ .. ..... ...... ........ ....... .. ............. ..... ... ....................... ... ... 114

APPENDIX A METHODS FOR PROGRAMMING DATALOGGER AND LOADCELL .•...••...•••..••••••.•••.• 115
A. 1 SPECIFICATIONS ......................... .......... ..... ... .. ...... ....... ... ...... ..... ... ... ............ ... ... ........ ....... .... ..... ....... ..... ... . 115

A.l.l Loadcel/ ............... ....... .............................. ... .............. ................................ .. .... .................. .. ...... ........ 115
A. /.2 Datalogger ......................................................................................................................................... 115
A.l.3Batteries ............................................................................................................................................. ll5

A.2 PROGRAMMING .. ... ...... ... .. .............................................................. ..... ....... ... ...... ....................................... 115
A .3 ERROR OF THE LOADCELL .... .... ... ....... ....... ... ................. ........ .. ..... ...... ..... ... ..... .. .... ... .... ... ... ... ..... .. ..... ... ...... 117
A.4 BRIEF OVERVIEW OF HOW THE LOADCELL WORKS .. ... .... ... ... .... ....... .. ..... ... ....... ......... ... .. ... ... .... ....... .... ....... 117
A.5 TABLES AND FIGURES .. ...... ........ ....... ...... ....... ..... ..... .... .. ..... .. ......... .. .................. ........................................ 118

APPENDIX B ASSUMPTIONS OF ANALYSIS OF COVARIANCE ............................................................ 120
B . l METHODS TO TEST AsSUMPTIONS .. ............ ............................... ..... ..... .. ................ .. ............. ............. ......... 120

B.l .l Significant Covariate ... ....................................... ... ... ...................... ........ ......... ... ... ... .. ... .. .............. ..... 120
B./.2 Normally Distributed Covariate ........... .............................................................................................. 120
B./.3 Homogeneity of Slopes ...... ... ............. ............................................ .... ................................ ...... ........... 120
B./. 4 Equal Covariate Means ............................................................................................ ... ....................... 121

B .2 RESULTS : TuBE EXPERIMENT (CHAPTER 2)- SONOTIJBE EXPERIMENT .... ...... .... ......... .......... .... ....... ..... ...... .. 121

B.2.1 SignificantCovariate ...... ....................... .................................. .................. ......................................... /21
B.2.2 Normally Distributed Covariate ... ....... ...................... ............ ....... ..... .................... ............................. 122
B.2.3HomogeneityofSiopes ................ ...................... ................................................................................. l22
B. 2. 4 Equal Covariate Means ........ .... ........ .............. ............... ............. .... .... ......... .............. ..... .. ........ .... ...... 123

B .3 RESULTS : TUBE EXPERIMENT (CHAPTER 2)- POL YTIJBE EXPERIMENT .... .. .. .................................. .. .... ......... 124

B. 3.1 Significant Covariate ......... ............................ .. ....................... ....... ........ ...... .. ..... ................................ 124

B.4 RESULTS : FIELD TESTS ................. .... .... ... ..................................... .... ... .... ......................... ...... ...... ... ... ... .. ... 124

B.4.1 Normally Distributed Covariate ..... ........................ ........................... ... .............. .......... ..... ..... ............ 124
B.4.2 Significant Covariate .......... .......... ....... ............ .. ... ... ... ... ........................... ... ..... .... ............. ................. 124
B.4.3HomogeneityofSiopes .. ...................... .......... .. ... ..... .. .... ..... .. ....... ..... .... ..... .. .... ................................... l24
B.4.4 Equal Covariate Means .................................. ........................................... ......................................... 125

B.5 RESULTS : BIRCH G ENECOLOGY ... .. ...................... .......... .......... ............ ..... .. ....... ...... ... ... .... ........ .... .... .... ..... 126

B.5.1 Significant Covariate ........................ ... ... ....... .... .. .......... ... .......... ................. ........ .... .......... ........ ........ . 126
IV

B.-1.2 Normally Distributed Covariate ................ ... .. ..... .... .... .............. ............ .. .......................................... . 126
8.4.3 Homogeneity of Slopes ........... ........ ........ ....... .......... ..... .. ... ... ............ .. ....... .. .... .. ............... .. ........ ...... .. 126
B.-1.4 Equal Covariate Means .......................... .......... ...... ..................... ....... ..... .. .... ............ ........ ...... ....... ... . 12 7

B.6 TABLES AND FIGURES ...... ......... ..... .......... ................ .. ... .. ..... ...... ................ .. .. ... ...... ... ........ .. ... ......... .......... 129

APPENDIX C ASSUMPTIONS OF LINEAR ANALYSIS .............................................................................. 136
C.1 METHODS FOR TESTING THE ASSUMPTIONS ....... ... .. ........... ........ ... ... ....... .......... ... ... .. ............... ........ ....... .... 136

C././ Normal Distribution .... ................... ....... .......... ..... ................. ......... .. ....... ................. ....... .................. . 136

C. / .2 Homogeneous Variance and Independence of Residuals ......................... .... .... ............ ... .. ... ....... ........ 136

C .2 RESULTS: TUBE EXPERIMENTS (CHAPTER 2)- SONOTUBE EXPERIMENT ..... ........ .......... .. ... ........... .... ..... .... .. . 13 7

C.2./ Normal Distribution .................... ......... ....... ........ ........... ............. .. .................. ... ... ...... .. ... ........ ....... ... /3 7
C.2.2 Homogeneous Variance and Independence of the Residuals...................... ..................... .................... 137

C .3 RESULTS : TUBE EXPERIMENT (CHAPTER 2)- P OL YTUBE EXPERIMENT ..... ....... ....... ................. ... .. ...... ... .... ... 138

C.3./ Normal Distribution ....................... ..... ... ........................ ............................................. ....................... /38
C.3.2 Homogeneous Variance and Independence of the Residuals........ ..... ... ...... ........ ........... ............. .. ....... 138

C.4 RESULTS: FIELD STIJDY (CHAPTER 3) ... ................. ........ ...... ... ...... .. .. .... ..................... ......... ......... .. ... ... .... ... 139

C.4./ Normal Distribution ................. ........ .... ........ ..... ........ ...... ........ ..... ...... .... .. ....... ..... ....... ....... ....... ........ . 139
C.4.2 Homogeneous Variance and Independence of the Residuals ............................................................... 139

C.5 RESULTS : BIRCHGENECOLOGY(CHAPTER4) ... ..... ....... ... .. .... ...................... ........ ... ... .. .. .... ..... ... ... .............. 139

C. 5. I Normal Distribution ....................... ...... ............................ ............... ......... ............................. .... ......... 139
C.5.2 Homogeneous Variance and independence of the Residuals........... .. ...... ..... ... ............ .. ........ ... ........... /40

C .6 FIGURES AND TABLES·············· ····· ·····································
·····························
··········
·································141

APPENDIX D GRAPHS OF THE DATA (TOP SECTIONS) FOR THE SONOTUBE AND POLYTUBE
EXPERIMENTS (CHAPTER 2)........................................................................................................................ 156
D . 1 SONOTUBE EXPERIMENT ... .... ....... .... .... ...... .... ........... ................ ... .... .................. ... ...... .. ... ....... ... .... ..... ....... 156
D.2 POLYTUBE EXPERIMENT .... ..... .. ..... ... .. .... .. .... .... .. ..... .... ....... ....... ... ...... ...... .... ... .... .. ................................ .. ... 161

REFERENCES ................................................................................................................................................... 167

v

List of Figures
FIGURE 2-1 SONOTUBE EXPERIMENT. TUBE ASSEMBLY DESIGN .......... ... ..... ........ ...... ........... ............. ... .. .. .. ... .. ......... 48
FIGURE 2-2 SONOTUBE EXPERIMENT. DISTRIBUTION OF TREATMENT EFFECTS ON TilE PALETIES.
49
FIGURE 2-3 POL YTUBE EXPERIMENT. TUBE ASSEMBLY DESIGN ........................... ...... ........ ..... ............. ... ........ ... .. .. .. . 50
FIGURE 2-4 POL YTUBE EXPERIMENT. DIS1RIBUTION OF TREATMENT EFFECTS ACROSS THE PALETTES . .... ... .. .. .. ... ..... 51
FIGURE 2-5 TOP VIEW OF TilE DEVlCE USED IN BOTH TilE SONOTUBE AND POL YTUBE EXPERIMENTS TO SHEAR TilE
TUBES . ................. ....... ..... ............... .... ...... ... .. .. ..... ..... ...... ............. ...... ......... ....... ..... ...... ...... ... ... .... ............ .. . . 52
FIGURE 2-6 SIDE VIEW OF TilE DEVICE USED IN BOTH TilE SONOTUBE AND POL YTUBE EXPERIMENTS TO SHEAR TilE
TUBES ...... .................................................. ...... ...... .... ......... .. ... .... ......... ................................ .. ...... .. ....... ...... .. 52
FIGURE 2-7 DATA FROM TilE SONOTUBE EXPERIMENT, SHOWING THE MAXIMUM RESISTANCE (N) SELECTED OUT FOR
THE STATISTICAL ANALYSIS . .... .. ..... .. .... ...... .. ... ...... ................. ................. ........ ..... .......................................... 53
FIGURE 2-8 SONOTUBE EXPERIMENT. ADJUSTED LEAST SQUARE MEAN SHEAR RESISTANCE (KPA) AND STANDARD
ERROR FOR 6 BIRCH POPULATIONS OF SHEAR TESTS AT 0 .20 M (TOP SECTIONS) ... ... ...... .. .... ... .... ... .... .... ... ......... 54
FIGURE 2-9 POL YTUBE EXPERIMENT. MEAN ROOT BIOMASS (G) AND STANDARD ERROR IN TilE TOP SECTIONS (0-0.22
M) OF TUBE .. .. ... ...... ............. ................... .. ........... ........ ....... ..... ....... ....... .... .... .... ..................... ....................... 57
FIGURE 2-10 POL YTUBE EXPERIMENT. MEAN ROOT BIOMASS (G) AND STANDARD ERROR IN TilE MIDDLE SECTIONS
(0.22 - 0.44 M) OF TUBE .. ... ... ... ..... ... .. ... .......... ........ .... .... .......... ....... ... ... ....... .......... ..... .......... ... .. .. ... ..... .. ....... 58
FIGURE 2-11 POL YTUBE EXPERIMENT. MEAN ROOT BIOMASS (G) AND STANDARD ERROR IN TilE BOTTOM SECTIONS
(0.44- 0 .66 M) OF TUBE . ............ ..... ......... .... .... ......... ...... ....... ......... ..... ... ... ............................ .. ... .. ......... ... .. ... 58
FIGURE 2-12 POL YTUBE EXPERIMENT. COMBINED ROOT BIOMASS (G) OF TilE TOP, MIDDLE, AND BOTTOM TUBE
SECTIONS . .. ... ..... .... ..... ....... .. .. .. .... .... ..... ..... .... ... ... ... .. ... ...... .. .. .... ... ... ... ... .. ..... ..... ... .......... ........................ .... .. . 59
FIGURE 2-13 PERCENT SOIL MOISTURE OF TOP AND BOTTOM TUBE SECTIONS, BY SOIL TEXTURE . .... .......... .. .. ... .... ... .. 60
FIGURE 3-1 LocATION OF FIELD SITES ... .. ... ...... .. ...... .. ..... ...... .. .............. ..... ....... ...... .. ..... .. ........... ..... ....... ... .. .... ..... .. 77
FIGURE 3-2 TRIPoD AND WINCH SETUP FOR TilE VERTICAL UPROOTING OF PAPER BIRCH AND LODGEPOLE PINE ......... 78
FIGURE 3-3 SCATI"ERPLOT OF THE FIELD DATA: TREE RESISTANCE TO VERTICAL UPROOTING (KN) VERSUS TREE
GROUND LINE DIAMETER (CM) ... .. ..... .. ....... .. ..... ....... ... ........... ............................... ... .. ..... .. ..... .. ...... ....... ... .... ... 79
FIGURE 3-4 AVERAGE SOIL MOISTURE(%), BY JULIAN DAY, AT ALEZA LAKE, GREGG CREEK, AND RED ROCK . .. .. .. 80
FIGURE 3-5 SAMPLE OF DATA RECORDED BY TilE LOADCELL AND OATALOGGER .. .... ... ... ..... .. ................... ............. .... 81
FIGURE 3-6 SCATIERPLOT OF RESISTANCE TO VERTICAL UPROOTING (LOG 1RANSFORMED) AS RELATED TO TREE
GROUND LINE DIAMETER (LOG 1RANSFORMED) AT EACH FIELD LOCATION ......... ............. .. .... ..... ... ... ..... ... ... .... . 83
FIGURE 3-7 ROOT BIOMASS OBIAINED FROM VERTICAL UPROOTING (LOG 1RANSFORMED) AS A FUNCTION OF TREE
GROUND LINE DIAMETER (LOG 1RANSFORMED) AT EACH LOCATION ......................... ..... ...... . ... ... ...... ...... ... .... .. 84
FIGURE 4-1 SCATIERPLOT OF TREE RESISTANCE TO UPROOTING AND TREE GROUND LINE DIAMETER ........................ . 99
FIGURE 4-2 COMPARISON OF RESISTANCE AND DIAMETER BY NURSERY WHERE TilE TREES WHERE INITIALLY GROWN.
BARS REPRESENT AVERAGE HEIGHT, WITH STANDARD ERROR BARS . .. .......... ... .. .... .... .... ..... .... .. ... .. .. .. ..... ....... 101
FIGURE 4-3 COMPARISON OF AVERAGE HEIGHT IN 1999 (5 GROWING SEASONS) OF TilE SEED SOURCES AT 5 FIELD
TRIAL SITES IN BC .. .... ........ ... ...... ... .. .................. ... .... ..... .... ............ .. ............ ........ .... .. ...... .... ... .... ... ... .. ..... .... 103
FIGURE B-1 SONOTUBE EXPERIMENT. HISTOGRAM, FITI"ED WITH A NORMAL CURVE, OF MOISTURE CONTENT
(COVARIATE) . .. .... ... .. .......... .... ..... .... ..... .. .... ... ... .. ...... .. ... ... .... .. ..... ... ....... .... ... .... .. ... .... .... ... .... .... .. ........ .... ... .. 130
FIGURE B-2 FIELD STUDY. HISTOGRAM, FITTED WITH A NORMAL CURVE, OF TilE PROPOSED COYARIATE DIAMETER
(LOG 1RANSFORMED) .. ............. ........ .... .. ............. ....... .............. ...... ......... ..... ................. ... .. ............... .... ...... . 132
FIGURE B-3 GENECOLOGY STUDY. HISTOGRAM, FITTED WITH A NORMAL CURVE, OF THE COY ARIATE, DIAMETER .. 134
FIGURE C-1 SONOTUBE EXPERIMENT. HISTOGRAM FITTED WITH A NORMAL CURVE OF TilE RESIDUAL DATA
RESULTING FROM TilE ANCOV A FOR TilE TOP SECTIONS OF TilE TUBE . ... ........ .. ...... ...... ............. ........ ....... ... 141
FIGURE C-2 SONOTUBE EXPERIMENT. NORMAL PROBABILITY PLOT OF TilE RESIDUAL DATA RESULTING FROM TilE
ANCOV A FOR THE TOP SECTIONS OF THE TUBE .. ... .. ....... .. ..... ..... ... .. .... ... ..... ... .......... ....... ... ....... ...... ............ 141
FIGURE C-3 SONOTUBE EXPERIMENT. HISTOGRAM FITIED WITH A NORMAL CURVE OF TilE RESIDUAL DATA
RESULTING FROM TilE ANOV A FOR THE BOTI"OM SECTIONS OF THE TUBE ... ..... ...... ........ .. ... .. ... .. .. .. .. ............. 142
FIGURE C-4 SONOTUBE EXPERIMENT. NORMAL PROBABILITY PLOT OF THE RESIDUAL DATA RESULTING FROM THE
ANOV A FOR THE BOTI"OM SECTIONS OF THE TUBE .... .............. .. ........... ..... ..... ... .. .. .... ..................... ......... .... . 142
FIGURE C-5 SONOTUBE EXPERIMENT. PLOT OF RESIDUALS VERSUS ESTIMATE VALVES FROM THE ANCOV A FOR THE
TOP SECTIONS OF TUBE .... .. ...... ....... ........................... .................. ...... .. ........ .. ... ... ..................... .. ...... ....... .. ... 143
FIGURE C-6 SONOTUBE EXPERIMENT. PLOT OF RESIDUALS VERSUS ESTIMATE VALVES FROM THE ANOV A FOR THE
BOTI"OM SECTIONS OF TUBE ........................... ............................... ............ ........ .... ........... .............. ..... .. .... ... . 143
FIGURE C-7 SONOTUBE EXPERIMENT. SCATIERPLOT MATRIX OF SHEAR RESISTANCE (KPA) AND SOIL MOISTURE
CONTENT(%) BY TUBE SIZE .. .. .... .. .... ...... ............. ... .... ........ .. .... ............ ..... ... ...... .. .... ... .... .... .. ... ..... ........ ...... . 144

VI

FIGURE C-8 SONOTIJBE EXPERIMENT. SCATTERPLOT MATRIX OF SHEAR RESISTANCE (KPA) AND SOIL MOISTURE
CONTENT(%} BY PLANT TYPE .... .................. ... ................................ .. .................. .... .......... ...... ... ........ .. .. ... .... 144
FIGURE C-9 SONOlUBE EXPERIMENT. SCATTERPLOT MATRIX OF SHEAR RESISTANCE (KPA) AND SOIL MOISTURE
CONTENT(%) BY POPULATION, WHERE POPLUATION 1 IS NQ-PLANT, POPULATION 2 IS PINE, AND POPULATIONS
3-8 ARE BIRCH AT ELEVATIONS 700-1200 . .. .... ..... ........... ... .............. ... .. ................. ... .... ... ............ .. .. ...... ....... 145
FIGURE C-1 0 POL YTIJBE EXPERIMENT. HISTOGRAM FITTED WITH A NORMAL CURVE OF RESIDUALS FROM TOP
SECTIONS .............. ................................................. .. .. .... .................... .. .... .... ... ............. ..... .. ... ... ..... .............. 145
FIGURE C-11 POL YTIJBE EXPERIMENT. HISTOGRAM, FITTED WITH A NORMAL CURVE OF RESIDUALS FROM BOTTOM
lUBE SECTIONS ... .... .. ........ .......... ....... ............. ............. .... .......... ............................. .... ..... .. .. ....... .... ............. 146
FIGURE C-12 POLYTIJBE EXPERIMENT. PROBABILITY PLOT FITTED WITH A LINE OF BEST FIT FOR THE TOP SECTIONS OF
lUBE ....................................................................... .......... .. .................... ...... ....... .. ...................................... 146
FIGURE C-13 POLYlUBE EXPERIMENT. PROBABILITY PLOT FITTED WITH A LINE OF BEST FIT FOR THE BOTTOM
SECTIONS OF lUBE ............ ............. .... ............. ................. ............. ... .... ... ... .............. ........... ................. .. ...... . 147
FIGURE C-14 POL YTIJBE EXPERIMENT. SCATTERPLOT OF RESIDUALS AGAINST ESTIMATE VALliES FOR THE TOP
SECTIONS OF TUBE ... ................................................... ...... .. ..... ... .............................................. ...... .. .. .. .. ... ... 147
FIGURE C-15 POL YTIJBE EXPERIMENT. SCATTERPLOT OF RESIDUALS AGAINST ESTIMATE VALUES FOR THE BOTTOM
SECTIONS OF TIJBE ............................ .... .... ... ..... ... ........................................... .................. ............................ 148
FIGURE C-16 FIELD STUDY. HISTOGRAM, FITTED WITH A NORMAL CURVE OF RESIDUALS FROM THE ANCOV A
ANALYSIS IN THE FIELD TESTS ..... ... ........ .... ....... ....... ... .................... ............................. ..... ........................... 148
FIGURE C-17 FIELD STUDY. NORMAL PROBABILITY PLOT OF RESIDUALS FROM THE ANCOV A ANALYSIS IN THE FIELD
TESTS . ............... .. .... ... ................................................... .. .............................................. ..... ... ..... ......... ........ 149
FIGURE C-18 FIELD STUDY. RESIDUALS VERSUS ESTIMATE VALUES FROM ANCOV A. .. ... .... ......... ... .. .. ..... ... ..... .. ... 149
FIGURE C-19 FIELD STUDY. SCATTERPLOT MATRIX OF DIAMETER (LOG TRANSFORMED) AND RESISTANCE (LOG

TRANSFORMED) BY PLANT TYPE ............................ ............... ................. .. .. ... ................................. ... ... ......... 150
FIGURE C-20 FIELD STUDY. SCATTERPLOT MATRIX OF DIAMETER (LOG TRANSFORMED) AND RESISTANCE (LOG
TRANSFORMED) BY LOCATION .................................. .. ........ ...... ........... ...... ..... .... ...... .... ........ ........... ........... .. 150
FIGURE C-21 FIELD STUDY. SCATTERPLOT MATRIX OF DIAMETER (LOG TRANSFORMED) AND RESISTANCE (LOG
TRANSFORMED) BY NUMBER OF STEMS ................................................. ....... ............................... ....... ... ........ 151
FIGURE C-22 FIELD STUDY. SeATTERPLOT MATRIX OF DIAMETER (LOG TRANSFORMED) AND RESISTANCE (LOG
TRANSFORMED) BY VEGETATION DENSITY .. .. ... ..... .. .... ....... .............. .. ............ ........ .......... ....... ...... ..... .... ..... .. 151
FIGURE C-23 GENECOLOGY STUDY. HISTOGRAM FITTED WITH A NORMAL CURVE OF THE RESIDUALS RESULTING FROM

THE ANCOV A. ...... ... ...... ....................... ....... ..... ... .. ..................................................................................... 152
FIGURE C-24 GENECOLOGY STUDY. PROBABILITY PLOT FITTED WITH A LINE OF BEST FIT OF THE RESIDUALS

RESULTING FROM THE ANCOV A. ........................................ ... .................................................... ................. 152
FIGURE C-25 GENECOLOGY STUDY. SCATTER PLOT OF THE RESIDUALS VERSUS ESTIMATE VALUES FROM THE

ANCOVA............ .... .. ...... ........... ......... .. ............ .... .. .. ... ... .................................... ...... ................................. 153

FIGURE C-26 GENECOLOGY STUDY. SCATTERPLOT MATRIX OF RESISTANCE TO VERTICAL UPROOTING (LOG
TRANSFORMED) AND TREE GROUND LINE DIAMETER (LOG TRANSFORMED) ACROSS SEED SOURCES ............ .... 153
FIGURE C-27 GENECOLOGY STUDY. SCATTERPLOT MATRIX OF RESISTANCE TO VERTICAL UPROOTING (LOG
TRANSFORMED) AND TREE GROUND LINE DIAMETER (LOG TRANSFORMED) ACROSS STOCKTYPES . .. ... .. .... ..... .. 154
FIGURE C-28 GENECOLOGY STUDY. SCATTERPLOT MATRIX OF RESISTANCE TO VERTICAL UPROOTING (LOG
TRANSFORMED) AND TREE GROUND LINE DIAMETER (LOG TRANSFORMED) ACROSS NURSERIES .............. ....... 154
FIGURE C-29 GENECOLOGY STUDY. SCATTERPLOT MATRIX OF RESISTANCE TO VERTICAL UPROOTING (LOG
TRANSFORMED) AND TREE GROUND LINE DIAMETER (LOG TRANSFORMED) ACROSS PRUNING TREATMENTS . .. 155

VII

List of Tables
TABLE 1-1 MEAN INDIVIDUAL ROOT TENSILE SlRENGTH (:MPA) OF CONIFER TREES AND BROADLEAF TREES AND
SHRUBS ..... .. ....................... ... ................................ ............................... ... .... .. ............. ...... .. .......... .................. 22
TABLE 2-1 RESULTS FROM WALDRON ( 1977) AND WALDRON ET AL. ( 1983) WHICH SHOW THE EFFECT OF SOIL TYPE
ON ROOT REINFORCEMENT ..................... ..... ..... ........ ....... .................... ............ .......................... .... .... .............. 4 7
TABLE 2-2 SONOTUBE EXPERIMENT. HEIGHT AND DIAMETER OF THE PAPER BIRCH AND LODGEPOLE PINE TREES AT
THE TIME OF PLANTING, AND AT THE TIME OF SHEARING ... ................................................................. ... ... ..... ... 48
TABLE 2-4 SONOTUBE EXPERIMENT. RESULTS FROM ANCOV A OF SHEAR TESTS AT 0 .20 M (TOP SECTIONS) . ......... .. 53
TABLE 2-5 SONOTUBE EXPERIMENT. RESULTS FROM ANOV A OF SHEAR TESTS AT 0 . 50 M (BOTTOM SECTIONS) ........ 54
TABLE 2-6 SONOTUBE EXPERIMENT. COMPARISON OF ADJUSTED LEAST SQUARE MEAN SHEAR RESISTANCE (KPA) AND
ROOT REINFORCEMENT BY PLANTING TYPE OF SHEAR TESTS AT 0 .20 M (TOP SECTIONS). SHEAR RESISTANCE
FOLLOWED BY THE SAME LETTERS WERE NOT STATISTICALLY DIFFERENT ............... .. ...... ..... ... ........ ...... ... ........ 54
TABLE2-7 POLYTUBEEXPERIMENT. RESULTS FROMTHEANOVA OF SHEAR TESTSAT0.22 M(TOPSECTIONS) ... ..... 55
TABLE 2-8 POL YTUBE EXPERIMENT. RESULTS FROM THE ANOV A OF SHEAR TESTS AT 0 .44 M (BOTTOM SECTIONS) . 55
TABLE 2-9 POL YTUBE EXPERIMENT. ADJUSTED LEAST SQUARE MEAN RESISTANCE (KPA) FOR EACH PLANT TYPE IN
ALL SOIL TEXTURES AT 0 .22 M (TOP SECTIONS). SHEAR RESISTANCE FOLLOWED BY THE SAME LETTERS WERE
NOT STATISTICALLY DIFFERENT..... .... ..... ............................................... ..... .......................................... .......... 55
TABLE 2-10 POL YTUBE EXPERIMENT. ADJUSTED LEAST SQUARE MEAN RESISTANCE (KPA) FOR EACH PLANT TYPE IN
ALL SOIL TEXTURES AT 0 .44 M (BOTTOM SECTIONS). SHEAR RESISTANCE FOLLOWED BY THE SAME LETTERS
WERE NOT STATISTICALLY DIFFERENT ....... ...... ...... ....... ..... .. ... .............................. ... ................. ............. .... .. .. .. 55
TABLE 2-11 POL YTUBE EXPERIMENT. ADJUSTED LEAST SQUARE MEAN RESISTANCE (KP A) FOR EACH SOIL TEXTURE
AND ALL PLANT TYPES AT 0 .22 M (TOP SECTIONS). SHEAR RESISTANCE FOLLOWED BY THE SAME LETTERS WERE
NOT STATISTICALLY DIFFERENT .. ....... ....................... ................. ...................... .. .................................... .. ....... 56
TABLE 2-12 POL YTUBE EXPERIMENT. ADJUSTED LEAST SQUARE MEAN RESISTANCE (KP A) FOR EACH SOIL TEXTURE
AND ALL PLANT TYPES AT 0.44 M (BOTTOM SECTIONS). SHEAR RESISTANCE FOLLOWED BY THE SAME LETTERS
WERE NOT STATISTICALLY DIFFERENT ............................................................................................................. 56
TABLE 2-13 POL YTUBE EXPERIMENT. ADJUSTED LEAST SQUARE MEAN RESISTANCE (KPA) FOR EACH PLANT TYPE
AND SOIL TEXTURE AT 0 .22 M (TOP SECTIONS) ... ... .... .. ............................................................. .. ... ................... 56
TABLE 2-14 POL YTUBE EXPERIMENT. ADJUSTED LEAST SQUARE MEAN RESISTANCE (KPA) FOR EACH PLANT
TEXTURE AND SOIL TYPE AT 0.44 M (BOTTOM SECTIONS) ......... ....... . .. ............ ..... .. ... ... .......... ....... .... .... .. ...... .... 57
TABLE 2-15 SUMMARY OF INCREASED RESISTANCE FROM THE LITERATURE AND FROM THIS CHAPTER. .... .. .... .... .. .... .. 59
TABLE 3-1 RESULTS OF VERTICAL UPROOTING TESTS BY NILA WEERA ( 1994) IN THAILAND ..... ... ....... ..... ... .. ..... ...... .. 76
TABLE 3-2 SITE INFORMATION .......... ....... ................... .......... .... ....... ....... ..... .... .. .... .... ..... .......... ..... ...... .... ... ........ .. ... 78
TABLE 3-3 RESULTS FROM THE ANCOVA ................... ....... .... ..... .. ... .......... ....................................................... ...... 81
TABLE 3-4 ADJUSTED LEAST SQUARE MEAN RESISTANCE (LOG KN) FOR EACH PLANT TYPE, AT ALL LOCATIONS .. ... ... 82
TABLE 3-5 ADJUSTED LEAST SQUARE MEAN RESISTANCE (LOG KN) AT EACH LOCATION, FOR BOTH SPECIES.
UPROOTING RESISTANCES FOLLOWED BY THE SAME LETTERS WERE NOT STATISTICALLY DIFFERENT . .... ... ........ 82
TABLE 3-6 ADJUSTED LEAST SQUARE MEAN RESISTANCE (LOG KN) FOR EACH PLANT TYPE AND NUMBER OF MAIN
STEMS . . ......... ... .... ... .................................. .................. ....... ..... ... .... .. .... .............................................. ........... . 82
TABLE 3-7 MEAN ROOT BIOMASS (LOG lRANSFORMED) AND MEAN RESISTANCE PER UNIT AREA ROOT BIOMASS OF
PAPER BIRCH AND LODGEPOLE PINE TREES AT ALL SITES . ... ... ............................ .......... ..... .. ... ...... .. .. .... .. ........... 83
TABLE 3-8 MEAN ROOT BIOMASS (LOG lRANSFORMED) AND MEAN RESISTANCE PER UNIT ROOT BIOMASS OF PAPER
BIRCH AND LODGEPOLE PINE AT THE THREE LOCATIONS ............... .. .... .. ..... .. ...... .... .. ............. ... .... .... .. ..... ...... ... 84
TABLE 3-9 MEAN ROOT BIOMASS, LOG lRANSFORMED, AND MEAN RESISTANCE PER UNIT ROOT BIOMASS OF PAPER
BIRCH AND LODGEPOLE PINE AT EACH FIELD LOCATION ...................................... ... ........ .. ..... ... ... ..................... 85
TABLE 4-1 SUMMARY DATA FOR THE LOCATION OF THE PAPER BIRCH SEED SOURCES (ADAPTED FROM WANG ET AL.
1998A) ..... ................................... ....... .. ........................................ ........ ... .... ... .......... ... ... ..... ........................... 99
TABLE 4-2 RESULTS FROM THE ANCOV A. ....... ........ .. .... ... .... ...... ............................................................. .... ... ...... I 00
TABLE 4-3 RESISTANCE, ROOT BIOMASS, AND RESISTANCE PER UNIT ROOT BIOMASS BY SEED SOURCE. UPROOTING
RESISTANCES FOLLOWED BY THE SAME LETTERS WERE NOT STATISTICALLY DIFFERENT .................. .. ............ . 100
TABLE4-4 RESISTANCE, ANDROOTBIOMASSBYNURSERY .. .......... ... .. .. ................... ........ ......... ... .. ......................... 100
TABLE 4-5 RESISTANCE, AND ROOT BIOMASS BY NURSERY AND STOCK TYPE. UPROOTING RESISTANCES FOLLOWED BY
THE SAME LETTERS WERE NOT STATISTICALLY DIFFERENT .... .. ..... .. ..... .. ..... ... ....... .... ............ .......................... 101
TABLE 4-6 COMPARISON OF HEIGHT AND DIAMETER OF THE 4 SEED SOURCES: IN THE NURSERY (RED RocK AND
KALAMALKA) IN 1996, AT RED RocK IN 2000, AND AT SKIMIKIN IN 2000 ....................... ....... ..................... 102
TABLE A - 1 LOADCELL PROGRAM FOR THE CR 1 OX ...... ........... ... ..... ... .. ..... .. ..... .............. ......... ... .. .. ......... ...... .. .. .... 118
Vlll

TABLE A - 2 WIRING DIAGRAM FOR TilE CR 1OX OAT ALOGGER ....... ......... ... ..... ....... .. ..... .. .... ... ............... ................ . 119
TABLE B-1 SONOTUBE EXPERIMENT. ANCOVA RESULTS FOR TOP TUBE SECTIONS .................. ....... .. .... .. .. .. .. ......... 129
TABLE B-2 SONOTUBE EXPERIMENT ANCOV A RESULTS FOR TilE BOTTOM TUBE SECTIONS .. .. .. .. .. .. ...... .. .. ............ 129
TABLE B-3 SONOTUBE EXPERIMENT. TEST FOR HOMOGENEITY OF SLOPES ......... .. ... .... .... ........ ......... .... ... ..... .... ...... 130
TABLE B-4 SONOTUBE EXPERIMENT. TEST FOR EQUAL COY ARlATE MEANS ........... ... .. .... ............................. .. ......... 131
TABLE B-5 POL YTUBE EXPERIMENT. PROPOSED ANCOV A MODEL FOR TilE TOP TUBE SECTIONS ....... ...... .. ... .. .... .. . 131
TABLE B-6 POL YTUBE EXPERIMENT. PROPOSED ANCOV A MODEL FOR TilE BOTTOM TUBE SECTIONS ... .. .. .... ...... .. . 131
TABLE B-7 FIELD STUDY. PROPOSED ANCOV A MODEL . ...................... .. .... ...................... .. ................................ .. 132
TABLE B-8 FIELD STUDY. TEST FOR HOMOGENEITY OF SLOPES .. .. ................................................ .. ........ ... .... .... .. .. . 133
TABLE B-9 FIELD STUDY. TEST FOR EQUAL COY ARlATE MEANS ................ .. ............. .. ........ ... ................. .. ......... .. ... 133
TABLE B-10 GENECOLOGY STIJDY. RESULTS FROM TilE PROPOSED ANCOV A. .. ... .. .......................... ....... .. ............ 134
TABLE B-11 GENECOLOGY STUDY. RESULTS FROM THE TESTS FOR HOMOGENEITY OF SLOPES . .. ..... .. .............. .... .... 13 5
TABLE B-12 GENECOLOGY STUDY. RESULTS FROM TilE TEST FOR EQUAL COYARlATE MEANS ... .. .. .. ......... .. .. ......... . 135

IX

Acknowledgments
I would like to gratefully thank my supervisor, Dr. Chris Hawkins, for his guidance, support and
assistance in the preparation of this thesis and throughout my graduate study. Thank-you also to
my knowledgeable and patient committee members, Michael Carlson, Han-Sup Han, and Paul
Sanborn.
My appreciation is sincerely extended to Patience Byman for her continual assistance and sense
of humour. In addition, thank-you to the technical and field assistance of Anne Cole, Jennifer
Lange, Sue Nykoluk, and Marcin Partyka.
And, most importantly, thanks to Moshi Chamell for his assistance, understanding, humour,
support, and hard work throughout the preparation of this thesis. Thank-you also to my parents,
Hugh and Catherine Campbell, who volunteered their vacation time to help with my work.
The experiments in this thesis could not have been carried out without the donation of time and
effort from: Susan Thorpe (J.D. Little Nursery), John Orlowsky & Steve Storch (UNBC), and
Alan Fenwick (Intertechnology Inc.). Many others have lent their expertise and their help
towards the completion of this thesis, and I thank-you.
Funding for this thesis research was provided by the National Science and Engineering Research
Council, the Slocan-FRBC Endowed Chair ofMixedwood Ecology and Management at the
University of Northern British Columbia, and Forest Renewal British Columbia.

X

Chapter 1
Introduction and Literature Review

1.1 Introduction
A general literature review on the effect of vegetation on terrain stability is provided in this
chapter; specific information about articles relevant to this research can be found in the following
chapters. The focus of this thesis is on paper birch (Betula papyrifera Marsh.) root
reinforcement. The objective of this thesis is to determine if paper birch can be used in British
Columbia (BC) to increase or enhance the stability of slopes where the primary mechanisms of
failure are shallow(< 1 min depth) mass movements.

The two broad processes of slope failure in forested or terrestrial (non-riparian) ecosystems
recognized in the literature are surface erosion, and mass movement. Surface erosion is "the
loosening or dissolving and removal of materials" by processes such as rainfall, surface runoff,
or wind (Trenhaile 1998). Mass movement (also called mass failure), is "the slow or rapid
gravitational movement of large masses of earth material" (Trenhaile 1998). When the shear
stresses acting on the slope material are greater than the shear strength (or shear resistance),
movement downslope along a shallow(< 1m) or deep(> I m) failure plane is initiated (Gray
and Sotir 1996). Different types ofvegetation can be more or less successful in mitigating
surface erosion and mass movement, depending on both the morphology and physiology of the
species, as well as the magnitude of the slope failure processes.

1.1.1 Objectives
The objectives of this literature review are:
•!• To briefly discuss how vegetation mitigates surface erosional processes;

•!• To provide a comprehensive review of the contribution of vegetation, and more specifically,
the contribution of root systems, to the stability of slopes prone to shallow mass failure
events; and

•!• To introduce information on paper birch genecology to determine if this species can be used
for terrain stabilization in BC.

1.2 Surface Erosion
Surface erosion often occurs when vegetation is removed and mineral soil is exposed to the
erosive action of precipitation, runoff, and wind (Gray and Sotir 1996). In general, vegetated
slopes will have less surface erosion than unvegetated slopes of otherwise comparable physical
characteristics (Cerda 1998, Weltz et al. 1998, Cerda 1999, Reid et al. 1999, Grace 2000 ).
Vegetation clearing activities, such as timber harvesting and road building increase surface
erosion (Megahan 1987, Hartman and Scrivener 1990, Chamberlin et al. 1991, Hartman et al.
1996, Grace 2000). The amount of surface erosion depends on, in part, the spatial distribution,
density and type of vegetation growing on the soil (Weltz et al. 1998).

1.2.1 Density and Spatial Distribution of Vegetation
Comparison studies of vegetated and unvegetated soils have shown how the presence and
distribution of vegetation affects the rate and amount of surface erosion. Dense vegetation
growing on slopes, ditches, or road cutslopes decreases surface erosion, reduces sediment
production, and enhances infiltration thereby diminishing surface runoff (Cerda 1998, Cerda
2

1999, Luce and Black 1999). Where vegetative cover is sparse or discontinuous, bare,
unvegetated soil continues to have high surface erosion (Abrahams et al. 1995, Parsons et al.
1996, Cerda 1999, Reid et al. 1999). Therefore, regardless of vegetation type, cover must be
dense and continuous to sufficiently protect against surface erosion.

1.2.2 Type of Vegetation
The morphological and physiological characteristics of vegetation influence the magnitude of
protection against surface erosion (Prosser et al. 1995, Parsons et al. 1996, Ghidey and Alberts
1997, Weltz et al. 1998, Grace 2000). In particular, the dense shallow root systems (Schiechtl
1980, Anonymous 1995, Gray and Sotir 1996, Ghidey and Alberts 1997) and the flexible, aboveground stems and leaves (Prosser et al. 1995) of perennial grass and herb species significantly
reduce surface erosion.

Perennial grass and herb species with shallow, dense root systems resist the processes of surface
erosion more effectively than deeper rooting species (Berglund 1976, Shields and Gray 1992,
Prosser et al. 1995, Coulter and Halladay 1997, Ghidey and Alberts 1997, Weltz et al. 1997,
Grace 2000). At shallow depths, species such as alfalfa (Medicago sativa L. var. Sonora) provide
more root reinforcement or cohesion to the soil than tree species such as Pinus ponderosa
(Douglas ex P. Laws. & C. Laws.) (Waldron 1977, Waldron et al. 1983). In addition, the dense
root systems of grass and herb species bind the soil, thereby reducing soil erosion (Prosser et al.
1995, Ghidey and Alberts 1997). In a study of a grassland valley in coastal California, Prosser et
al. ( 1995) found that 90% of the surface water flow resistance of dense grass cover was exerted
on the stems of plants. Even when the grass was cut short, roots provided soil cohesion and
limited wash erosion and channel initiation.

3

The effectiveness of grass species at controlling surface erosion was demonstrated in studies by
Abrahams et al. (1995 ) and Parsons et al. (1996), who looked at the impact of converting
grasslands to shrublands in Arizona. Surface erosion was substantially higher on shrubland
slopes than grassland slopes. Shrub spacing contributed to higher surface erosion as the exposed
soil between the shrubs was eroded away by rainsplash and surface runoff.

Rapid establishment of species is essential when mitigating surface erosion. Grace (2000), found
that a mixture of exotic grass species seeded on a fill slope established faster than a mixture of
native grass species. In the first year, erosion from the slope seeded with exotic species had less
erosion than the slope seeded with native species.

These studies illustrate the importance of vegetation with shallow, dense root networks, such as
grass species at providing erosion control. Although a continuous cover of any species may
control surface erosion (Gray and Sotir 1996), quick establishment on site is integral to slowing
erosional processes. Therefore, fast growing perennial grass and herbs species would be superior
to other vegetation types at providing effective control of surface erosion.

1.3 Mass Failure
Removal of vegetation reduces slope shear resistance (shear strength), and contributes to an
increase in the frequency of mass movements. Vegetation enhances slope stability by: 1) limiting
the amount of water on a slope and the rate at which water reaches the soil (hydrological effects),
and 2) contributing to soil shear strength with root reinforcement (mechanical effects) (Gray and
Sotir 1996 ). Both the alteration of hydrologic patterns and/or the loss of root reinforcement will
4

decrease slope shear strength and may lead to mass failure (O'Loughlin 1974, Burroughs and
Thomas 1977, Ziemer and Swanston 1977, Wu et al. 1979, Wu and Swanston 1980, Schroeder et
al. 1984, Sidle 1991 , Ekanayake et al. 1997, Zhou et al. 1998).

Many studies have shown that mass failures increase in both rate and magnitude as a
consequence of land clearing activities such as road building and, to a lesser extent, timber
harvesting (Swanston and Swanson 1978, Wu and Swanston 1980, Swanston et al. 1987,
Megahan 1987, Hartman and Scrivener 1990, Sidle 1991 , Hartman et al. 1996). As much as 80%
of mass movement and surface erosion (discussed above) in a harvested block can be attributed
to road building (Anderson 1971 , Brown 1972, Anderson et al. 1976, Beschta 1978, Fredriksen
1988). Therefore, although land clearing activities are mentioned generally, road building should
be mentioned specifically as the instigator of increased mass movement in harvested areas,
especially on a small scale.

1.3.1 Hydrological Effects of Vegetation

Both the leaves and the roots of vegetation limit the amount of precipitation reaching the soil,
through the processes of interception and evapotranspiration (Waldron 1977, Wu and Swanston
1980, Calder 1993, Gray and Sotir 1996). When vegetation is cleared, more water reaches the
soil and pressures build in the soil pores. As soil is saturated, pressures greater than atmospheric
pressure build, and positive pore water pressures are generated (Trenhaile 1998). Positive pore
water pressures decrease soil shear strength, and make the slope highly susceptible to failure
(Burroughs et al. 1976, Waldron 1977, Swanston and Swanson 1978, Wu et al. 1979, Wu and
Swanston 1980, Burroughs 1984, Ekanayake et al. 1997).

5

Several studies have documented the effect of positive pore water pressures on mass stability.
Wu et al. ( 1979) and Wu and Swanston ( 1980) measured pore water pressures in the Maybeso
valley (southeastern Alaska) and found significant increases between 1965 (pre-logging) and
1974 (post-logging). The increase was attributed to, in part, the loss of evapotranspiration, and
interception afforded by vegetation. The authors concluded that timber harvesting caused an
increased landslide risk due to the loss of the hydrologic benefits of vegetation. In Oregon,
Schroeder et al. ( 1984) observed 221 new landslides after a storm event with a 5-7 year return
interval, which generated sufficient precipitation to cause failure in both forest and clearcut
areas. In the slides considered, the loss of root reinforcement did not contribute to mass failure.
Calder ( 1993) studied the effects of afforestation on the hydrology and stability of slopes and
found that pore water pressures were reduced and slope stability was enhanced with the addition
of vegetation. Afforestation increased interception, and transpiration, thereby limiting the
amount of water on the slope.

It is the interaction of increased porewater pressures and decreased root reinforcement on a slope

resulting from vegetation removal that often causes mass failure (Waldron 1977, Wu et al. 1979,
Ekanayake 1997, Wu and Watson 1998). Large precipitation events on forested terrain do not
always result in failure, even if positive pore water pressures are generated; the mechanical effect
of vegetation (root reinforcement) may be more important than the hydrologic effect (Waldron
1977, Ekanayake 1997). Studies of root reinforcement, as discussed in the proceeding sections,
are abundant, while studies of the hydrologic effect appear to be limited. Root reinforcement is
easily quantifiable, and inter-species comparisons are possible, while the hydrologic effect is
more abstract and it is more difficult to determine inter-species differences. Nevertheless, the

6

importance of vegetation on slope hydrology was demonstrated by a few studies, and should be a
consideration when mitigating slope stability problems.

1.3.2 Mechanical Effects- the Contribution of Roots to Soil Shear Strength
Root systems enhance slope shear resistance (Waldron 1977, Wu et al. 1979, Waldron et al.
1983, Abe and Iwamoto 1986, Abe and Ziemer 1991 , Ekanayake et al. 1997, Wu and Watson
1998, Zhou et al. 1998). Root reinforcement is lost over time when vegetation is removed and
roots quickly begin to decay (O ' Loughlin 1974, Burroughs and Thomas 1977, Ziemer and
Swanston 1977, Watson and O'Loughlin 1985, Sidle 1991, Johnson et al. 1998). If sufficient
root reinforcement from new vegetation is not re-established soon after clearing, shear resistance
may decline to the point where shear stresses are great enough to cause mass failure (Watson and
O' Loughlin 1985, Sidle 1991 , Ekanayake et al. 1997, Wu and Watson 1998).

The contribution of root reinforcement to a slope depends on the morphology and the physical
properties of the root system, both of which can vary between species. Studies have shown that
root density (Shields and Gray 1992), rooting depth and width (Papesch et al. 1997), root
strength and decay (Burroughs and Thomas 1977), root elasticity (Watson et al. 1997), and the
orientation of the root system (Watson and O'Loughlin 1985) are important characteristics to
consider when studying vegetative species for terrain stability; such characteristics can affect the
ability of vegetation to prevent shallow mass slope failure.

1.3.2.1 Root Density
Shear resistance is affected by root density in the soil; the greater the density, the greater the
resistance and therefore, the greater the slope stability (Wu et al. 1979, Waldron et al. 1983, Abe
7

and Iwamoto 1986, Abe and Ziemer 1991, Ekanayake et al. 1997, Wu and Watson 1998, Zhou et
al. 1998). Studies of root density show a variation in root density, depending on the vegetation
cover (Watson and O' Loughlin 1985, Shields and Gray 1992), as well as a significant
relationship between density along a failure plane and shear resistance (Ekanayake et al. 1997,
Wu and Watson 1998, Zhou et al. 1998).

Shields and Gray ( 1992) studied the root densities of vegetation on a sandy levee along the
Sacramento Valley, California. The mean root density declined exponentially with depth, more
so for the sites with herbaceous or shrub cover. In addition, root density exponentially decreased
with increasing root size at all sites; at woody sites, the mean density of roots less than 0.1 em in
diameter was 90 % higher than herb sites.

Studies in New Zealand of the native species manuka (Leptospermum scoparium J.R. et G.
Forst.) and kanuka (Kunzea ericoides var. ericoides (A. Rich.) J. Thompson) have demonstrated
how root density affects slope stability. Watson and O'Loughlin (1985) excavated the root
systems ofmanuka. Primarily lateral roots were found in the upper 20-25 em ofthe soil while
vertical roots did not extend much beyond 50 em, which the authors attribute to the rockiness of
the soil. In general, the excavated root systems had a "dense network of fine roots." The high
root density of manuka indicated that it would provide more root reinforcement to slopes than
the plantation species Pinus radiata (D. Don). Watson et al. ( 1995) found that in the first eight
years of growth, kanuka produced more roots annually than P. radiata. Finally, Ekanayake et al.
( 1997) reported a significant positive correlation between kanuka root density per unit of soil
volume and shear resistance.

8

1.3.2.2 Root Plate Depth and Width

Shear resistance is affected by rooting depth (Waldron et al. 1983, Anderson et al. 1989, Ray and
Nicoll 1998, Peltola et al. 2000) and width (Sidle 1991, Papesch et al. 1997, Zhou et al. 1998).
Shear resistance is increased vertically by roots anchoring across failure boundaries and laterally
by roots intertwining with roots of adjacent vegetation to form a "membrane of strength" (Sidle
1991).

Reinforcement by lateral roots can substantially contribute to the shear resistance of a slope.
Ekanayake et al. ( 1997) compared the contribution of P. radiata and kanuka roots to soil shear
strength. At 8 years of age, kanuka growing at higher stocking densities than P. radiata (15, 000
stems per hectare for kanuka and 300 stems per hectare for P. radiata), had more overall lateral
root biomass, and therefore provided more root reinforcement. In looking at older P. radiata (I 039 years) stands, Papesch et al. ( 1997) found a significant relationship between root plate width
and the resistance of the tree to

pr

tin ~ tree uprooting is used as a surrogate for tree stability

in wind events (Anderson et al. 1989, Papesch et al. 1997, Ray and Nicoll 1998, Peltola et al.
2000), but is also a measure of root strength (Nilaweera 1994, Nilaweera and Nutalaya 1999).
Zhou et al. ( 1998) studied the role of lateral roots of Pinus yunnanensis (French) on shallow
slope stability and concluded that the shallow traction of lateral roots increased the overall shear
resistance of soil.

Vertical rooting depth is a factor in root reinforcement. Tree uprooting studies have shown a
relationship between rooting depth and the resistance of the tree to uprooting: the deeper the
roots, the greater the resistance (Anderson et al.l989, Ray and Nicoll 1998, Peltola et al. 2000).
In the same study previously discussed, Ekanayake et al. ( 1997) reported that by 16 years of age,
9

kanuka stands started to self-thin, and root biomass declined. At the same time, P. radiata
established taproots and vertical sinker roots, making the reinforcement provided by this species
superior to the reinforcement ofkanuka. Waldron (1977) and Waldron et al. (1983) showed that
at 30 em depth, alfalfa provided more shear resistance to the soil than Pinus ponderosa, but that
at 60 em depth, P. ponderosa provided more reinforcement than alfalfa. This was attributed to:
1) the dense roots of alfalfa at 30 em, and 2) the deeper roots of P. ponderosa at 60 centimetres.

1.3.2.3 Root Tensile Strength

O' Loughlin (1974), and Burroughs and Thomas (1977) found that a large percentage of roots fail
in tension during mass failure events. This has been verified by researchers who used slope
stability models to predict the amount of root reinforcement provided by vegetation, and
compared model results with field tests. Results showed that tensile strength was a critical
component ofthe overall root reinforcing capabilities of vegetation (Abe and Ziemer 1991, Wu
and Watson 1998). In examining the traction effect of Pinus yunnanensis lateral roots, Zhou et
al. (1998, pp. 117-118) explained the importance of tensile strength:

In regard to the traction effect. this study further suggests that the lateral roots enhance the in-plane tensile
strength of the rooted soil zone particularly via three mechanical actions: (1) when a slide occurs ... the sliding
force stresses the rooted soil mass at a particular area .. . , and causes a tensile stress in the roots, through the
root- soil bond; (2) with the mechanical property of the root, the roots transfer this tensile stress to another area
of the rooted mass of lower stress ... and mobilize the resistance to sliding in the lower-stress area ... ; and (3) at
the same time the roots deliver this mobilized resistance to the area where the load was first applied ... in a
form of a tensile resistance in the roots, to resist the load.

Root tensile strength increases with increasing diameter, but per unit area, tensile strength
decreases with increasing diameter (Hathaway and Penny 1975, Burroughs and Thomas 1977,
Ziemer and Swanston 1977, Watson and O'Loughlin 1985, Watson et al. 1997, Wu and Watson
1998). Small roots, therefore have more tensile strength per unit area than large roots. The
10

inference is that a high density of small roots would have equal, if not more, total strength than a
few large roots. This may explain why tensile strength varies between species (Table 1-1 ).
Species that produce high fine root biomass may have more overall strength than species that
produce a few large tap roots. In general, broadleaf tree and shrub species have equal, if not
greater tensile strength than do coniferous species, with the exception of coastal Douglas-fir,
which had the highest tensile strength of all species listed (Table 1-1 ). Several researchers have
referred to this difference between broadleaf and conifer species (Ziemer and Swanston 1978,
Schiechtl 1980, Watson and O'Loughlin 1985, Gray and Sotir 1996, Watson et al. 1997, Wu and
Watson 1998). However, there have been few direct comparison studies (with the exception of
comparisons in New Zealand between manuka and kanuka (broadleaftrees) and Pinus radiata,
which has been well studied) of the variation in root reinforcement between broad leaf
trees/shrubs, and conifer trees.

1.3.2.4 Root Decay Rate
After vegetation is cut, roots decay, and shear resistance declines, leaving the slope vulnerable to
failure if vegetation is not re-established quickly (O'Loughlin 1974, Burroughs and Thomas
1977, Ziemer and Swanston 1977, Watson and O' Loughlin 1985, Sidle 1991 , Johnson et al.
1998). Root reinforcement therefore can depend on the rate of root decay, as well as the rate of
new vegetation growth (Sidle 1991 ).

Root decay will occur at different rates, depending on the species. Initially finer, nonresinous
roots decay, leading to rapid root strength loss; over time, larger resinous roots will also decay
(O' Loughlin 1974, Burroughs and Thomas 1977, Ziemer and Swanston 1977). It has been
speculated that the initial loss of nonresinous roots is caused by fungal decomposition
II

(O'Loughlin 1974, Watson and O'Loughlin 1985, Watson et al. 1997) and that fungal
decomposition will occur sooner in softwood species than in hardwood or broadleaf species
(Watson et al. 1997).

Studies of root tensile strength decay have demonstrated that decay rates can vary between
vegetative species. These inter-species differences are, in all likelihood, a result of root
morphology; species with predominately fine nonresinous roots would lose strength faster than
species with predominantly large resinous roots. O'Loughlin (1974) reported a 50% decline in
the root strength of Douglas-fir and western red cedar (Thuja plica/a Donn ex D. Don) in 3-5
years. Three years after cutting, coastal Douglas-fir had lost 82 %of its strength per unit area,
while Rocky Mountain Douglas-fir had only lost 64 % (Burroughs and Thomas 1977). Ziemer
and Swanston ( 1977) found that two years after cutting, most roots 1 mm or more in diameter of
western hemlock, Sitka spruce, and Douglas-fir were present, while after 10 years most roots,
including resinous roots, had decayed. A study by Johnson et al. (1998) showed that yellowcedar roots (Chamaecyparis nootkatensis (D. Don) Spach) 25 mm or less in diameter had nearly
deteriorated 14 years after cutting.

Sidle ( 1991) simulated the effect of vegetation removal on root reinforcement by looking at root
decay rates (exponential relationship) and vegetation root re-growth rates (sigmoidal
relationship) for different vegetation and silvicultural cutting systems. The importance of
understorey vegetation for root cohesion was shown with a two-step shelterwood model where
85% ofthe trees were harvested in the initial cut and 15% were harvested in the final cut. From
the model, Sidle ( 1991) found that leaving a longer time between the initial cut and the final cut
and cutting fewer trees initially allowed higher root cohesion on site.
12

1.3.2.5 Root Elasticity
Root elasticity (the ability of roots to stretch without breaking), is also an important component
of shear resistance (0 ' Loughlin 1974, Watson et al. 1997, Peltola et al. 2000), although it has not
been studied extensively. Several researchers have observed rooted soils resisting failure over
larger displacements (movement) than unrooted soil, a characteristic attributed to the elasticity of
roots (Abe and Iwamoto 1986, Abe and Ziemer 1991 , Ekanayake et al. 1997, Zhou et al. 1998).
The implication for slope stability is that soil with vegetation would be able to withstand small
downslope movements without failure.

O ' Loughlin (1974) found that dead roots had less ability to stretch than live roots and concluded
that root elasticity allows movement of the soil mantle without rupturing the root system. In New
Zealand, Watson et al. ( 1997) measured the elasticity of kanuka roots and compared the effect of
kanuka roots to P. radiata roots. The authors demonstrated with slope stability models that
slopes planted with kanuka, which had more root elasticity, would have increased resiliency to
mass failure than slopes planted with P. radiata. Peltola et al. (2000) found a negative correlation
between root elasticity and wood density; elasticity was also highly correlated with tree

resistance to uprooting.

1.3.2.6 Root Orientation
Field observations of roots indicate that orientation may have an important role in providing
slope shear resistance. When growing on a slope, tree roots appear to have more roots oriented in
the upslope direction; in addition, these roots may have greater tensile strength than roots
13

oriented downslope (Schiechtl 1980, Watson and O' Loughlin 1985, Wass and Smith 1994). This
orientation against the pull of gravity (upslope) possibly provides a tremendous increase to slope
shear resistance.

Schiechtl (1980), measured the differences in tensile strength between roots oriented uphill and
roots oriented downhill of mountain alder (Alnus incana (L.) Moench). Japanese alder (Alnus
japonica). and Japanese red pine (Pinus densiflora Siebold & Zaccarini). Results indicated that
uphill, or anchor roots, had higher tensile strength than downhill roots. In a study in New
Zealand, the majority ofmanuka roots were oriented in the upslope direction (Watson and
O' Loughlin 1985). Wass and Smith ( 1994) found inter-specific differences in root orientation.
Douglas-fir did not have a larger percent of the first lateral roots oriented in the uphill direction,
however, lodgepole pine (Pinus contorta Douglas & Loud. var. latifolia Engelm. ex S. Wats) did.

1.3.3 Summary of Mass Stability
Vegetation stabilizes against mass failure by limiting the water reaching the soil, and by
increasing slope shear strength with root reinforcement. The hydrological and mechanical
influence of vegetation depends on the morphology and physiology of the plant species. In
particular, the contribution of roots to slope shear strength is essential for maintaining or
enhancing stability; the amount of root reinforcement is determined by the density, distribution,
depth/width, strength, elasticity, orientation, and decay rate of a species' root system.

Although the studies reviewed in this chapter did not show inter-species differences for the effect
of vegetation on the hydrological aspects, variation may exist. Tall, long-lived trees would have
higher rates of transpiration than small, short-lived shrubs. In addition, a forest cover of
14

evergreen species would provide year round interception, whereas a forest of deciduous trees
would not. The magnitude of these differences has not been documented, possibly because, as
mentioned previously, vegetation root reinforcement may have a greater effect on slope shear
resistance than the hydrologic effect of vegetation.

There is considerable variation between species in the contribution of root reinforcement to slope
shear strength. Although little research has been done in this area, broadleaf tree species may
have greater root reinforcement than conifer species, especially at a young age. Studies of tensile
strength (Table 1) indicate that broadleaf trees may have equal if not greater tensile strength than
coniferous trees. In addition, broadleaf trees and shrubs may have a high density of fine roots
within the top 1 m of soil (as found by Watson and O' Loughlin 1985). The dense root systems of
broadleaf trees may afford greater root reinforcement than the less dense root systems of
coniferous trees (Ekanayake et al. 1997). Finally, the root decay of softwood species (coniferous
trees) may occur sooner than for hardwood species (broadleaf trees).

1.4 Paper Birch
This thesis will suggest that retention and regeneration ofbroadleaf species, such as paper birch,
in BC' s forests may increase or enhance slope stability. Some of the benefits ofbroadleaf-conifer
mixtures summarized by Comeau (1996) are:
•!• Increased biodiversity (genetic,

species, ecosystem)

•!• Overstorey shade protection to young

conifers

•!• Improved forest health

•!• Higher yield and economic return

•!• Enhanced soil nutrients

•!• Forest sustainability

15

1.4.1 Importance of Birch-Conifer Mixedwoods

Management ofbirch in mixtures with conifer species such as lodgepole pine and interior spruce
(Picea glauca (Moench) Voss x emgelmanii Parry ex Engelm.) can improve the sustainability of
BC' s forests . Many attributes of paper birch make it an appropriate species for use in mixedwood
management.

Biodiversity Birch enhances biodiversity by: increasing tree species diversity in the forest;
providing a food source for ungulates such as moose; and supplying preferred cavity nesting sites
and food for many bird species (Safford et al. 1990, Simard 1996, Peterson et al. 1997). In
addition, birch trees are a source of coarse woody debris, an important factor for nutrient cycling,
and habitat (Peterson et al. 1997).

Forest health and [unction Paper birch trees provide overstorey shade to young conifer seedlings
and facilitate conifer growth (Simard 1996, Peterson et al. 1997). Research in Finland showed
higher growth in mixed conifer-birch forests (Pinus sylvestris, Picea abies, and Betula pendula)
compared with single species stands (Mielikainen 1996). In addition, birch reduces both spruce
leader weevil (Pissodes strobi) and the spread of Armillaria root rot (Simard 1996, Carlson et al.
2000).

Soil nutrients Safford et al. ( 1990) reported that paper birch leaf litter contributed more nutrients
to the forest floor than red pine. Few studies have further documented this possible role of paper
birch in forests . However, a retrospective study in the Prince George region ofBC suggested that
paper birch leaf litter increased pH and nutrients such as N and P in the forest floor (Sanborn
2001).
16

Yield and economic return If paper birch trees are grown as a commercial species, then mixed
birch conifer stands would have increased yield over stands managed only for conifers (Comeau
1996, Mielkainen 1996, Peterson et al. 1997). Since the mid-90's there has been growing interest
3

in BC in paper birch as a commercial species. In 1995, 29000 m of birch was used
commercially in BC, a 70% increase from 1990 (Peterson et al. 1997). In other locales, the
commercial use of paper birch includes pulp and paper, lumber, and plywood (D. Lousier pers.

comm. 200 11) .

Forest sustainability Both the ecological and economic sustainability of the forest can be
maintained by the retention of birch in mixed or pure stands in BC. Biodiversity, soil nutrients,
forest health and function, yield and economic return all can be enhanced by managing to retain
mixed birch-conifer stands; as a result of such management practices forest sustainability can be
perpetuated.

1.4.2 Genecology of Paper Birch
Paper birch is a highly variable species with a wide geographic distribution in North America
that grows in areas with a variety of topographic and climatic conditions (Safford et al. 1990,
Farrar 1995, Peterson et al. 1997). As a pioneer species, paper birch has a relatively fast growth
rate and can regenerate easily in exposed mineral soil in cleared areas and in mature forest
openings as small as 2-3 tree lengths (Safford et al. 1990, Peterson et al. 1997). Paper birch
reaches maturity and peak seed production between 40 and 50 years of age, and often dies out of

1

J.Daniel Lousier. pers comm. 2001 . Whiskey Jack Forest Sciences, Prince George, BC. Email :

whi skeyj ackscience@telus.net .

17

the stand between 70 to 140 years (Safford et al. 1990, Peterson et al. 1997). Top height of
mature trees varies between 15-30 m (Peterson et al. 1997). Paper birch has a shallow root
system, with the majority of roots in the top 60 em of soil, and it does not develop tap roots
(Safford et al. 1990).

The genetic variation of paper birch in BC has not been well studied (Carlson et al. 2000). Tree
species with an extensive range that grow in diverse environments, such as birch, often have
local adaptations expressed phenotypically (and perhaps genotypically) (Stetler and Bradshaw
1994, Carlson et al. 2000). Studying the genetic variation of paper birch, or any other tree species
allows the: 1) determination of the environmental range, or limit, of different populations, and 2)
identification of populations which are not growing in the most productive environments, most
often because of physical limitations of reaching the most productive site conditions (Rehfeldt
2000). When determining the environmental range of populations, it becomes clear that different
species, or even perhaps different populations (M. Carlson pers. comm. 200 12) have different
evolutionary strategies (Rehfeldt 1994). Rehfeldt (1994, p. 93) defined these strategies as
follows :

In the specialist strategy ... genetic variability has been organized into numerous local populations each of which
is physiologically specialized for a particular range of environments ... .In species displaying a generalist
strategy ... individuals and, therefore, populations are physiologically attuned to a broad range of environments.

Identification of the evolutionary (generalist or specialist) strategy used by paper birch would aid
in developing operational reforestation guidelines for this species in BC (Carlson et al. 2000).

2

M. Carlson. pers. comm. 2001 . Research Scientist, Interior Tree Breeding. Forest Genetics Section. BC Ministry of

Forests. Vernon, BC. Email: Mike.Carlson@gems3 .gov.bc.ca.

18

Furthermore, paper birch populations may have substantial differences in root reinforcement,
which has implications for management of unstable terrain.

Preliminary work on the genecology of paper birch is underway in BC (Wang et al. 1998a,
1998b, Carlson et al. 2000). In a greenhouse study, four populations of paper birch from BC had
differences in growth rates (height and root biomass), growth period, drought tolerance, and
nutrient requirements (Wang et al. 1998a, 1998b ). Carlson et al. (2000) reported initial results
from an 18 seed source trial that was replicated in 5 BC forest regions. Results showed negligible
height differences after 2 years between the seed sources, except on the more northern sites
(where there were more restrictive environments). On these sites, growing conditions were
severe and the local seed sources were taller than the other seed sources. Overall, height
variation occurred at the stand, rather than the regional level, while frost damage differences
occurred at the regional, rather than the stand level. Regional differences in frost damage may
indicate that paper birch has a generalist evolutionary strategy with respect to frost hardiness
(Carlson et al. 2000).

1.5 Purpose of This Research
Management of paper birch in mixedwood stands is a sustainable forest management practice. In
addition to the ecological and economical benefits of mixed woods (stated above), paper birch
can be managed to maintain or enhance slope mass stability. This literature reviews suggests that
paper birch has many attributes that warrant further research of this species for terrain
stabilization in BC. These attributes are summarized below:

19

•!• Paper birch trees have a relatively fast growth rate, and root reinforcement may be

established earlier in mixed birch-conifer forests than in pure conifer forests. As young
conifer trees become established paper birch will maintain slope shear resistance with root
reinforcement, provide overstorey shade for young seedlings, and enhance local biodiversity.

•!• The shallow, dense root system of paper birch may provide superior root reinforcement to the

root systems of conifer species in the first decade of growth.

•!• After a birch tree is cut or after stem breakage occurs, birch sprouts grow from the stump. A

degree of root reinforcement would therefore be maintained by paper birch sprouts on site,
even after the tree has been harvested.

This research will attempt to quantifY the contribution of paper birch root reinforcement in BC to
slope shear resistance. The emphasis ofthis research is on the ability of young(< 15 years) paper
birch root systems to prevent shallow mass failure. There are two reasons for limiting the scope
of this research. First, young conifer trees cannot provide sufficient root reinforcement on a slope
after harvesting untill5 years, although it could be longer (Chamberlin et al. 1991, Sidle 1991).
Fast growing paper birch may be able to provide sufficient root reinforcement to prevent failure
while conifer root reinforcement is established. Second, the shallow root system of paper birch
would not be able to reinforce against deep-seated mass failure. In areas where mass failure
occurs at depths greater than 1 m, use of paper birch to prevent failure would not be appropriate.

Lodgepole pine was used in two of the thesis experiments to provide a point of reference for the
magnitude of paper birch root reinforcement. In addition, it was hoped that such comparisons
20

would demonstrate that a broadleaf tree species such as paper birch, has superior root
reinforcement to a conifer species such as lodgepole pine, at 15 years of age or Jess. Lodgepole
pine was chosen because it is a fast growing early seral species that has a wide range of
environmental tolerance (Lotan and Critchfield 1990). Lodgepole pine has a shallow root system,
but often develops taproots and vertical sinkers, which results in a heart shaped root system
(Lotan and Critchfield 1990, Koch 1996). Lateral roots do not grow deeper than 60 em into the
soil (Koch 1996).

The objectives of this thesis are:

•!•

To determine the genetic variation in paper birch root reinforcement.

•:•

To determine the environmental variation in paper birch and lodgepole pine root
reinforcement.

•!•

To determine the differences in root reinforcement between paper birch and lodgepole
pme.

21

1.6 Tables and Figures
Table 1-1 Mean individual root tensile strength (MPa) of conifer trees and broad leaf trees and
shrubs.
i

Species

II

I

I

Common Name

I
I

I

'

I

Mean Root
Tensile
Strength
(MPa)

I
!

Source

I

Coniferous trees
1Sitka spruce
Picea sitchensis
1
Pinus radiata
Radiata pine
Pinus yunnanesis
Yunnan pine
Pseudotsuga menziesii var.
menziesii
~ t Douglas fir
Pseudotsuga menziesii var. glauca Rocky Mountain

Douglas fir

Tsuga heterophylla

I

'

16
18
19
55
19

!Western hemlock

20

Mountain alder

31
41
38
33
34
36
46

Ziemer and Swanston ( 1977)
!watson and O'Loughlin (1985)
Zhou et al. (1998)

!

IBurroughs and Thomas (1977)

IBurroughs and Thomas ( 1977)
Ziemer and Swanston (1977)

Broadleaftrees and shrubs

Alnus incana
Alnus japonica
Betula pendula
Kunzea ericoides var. ericoides
Leptospermum scoparium
Populus deltoides
Populus euramericana '1-78'
Populus euramericana 1-488'
Salix matsundana
Salix purpurea 'Booth'
Vaccinium parvifolium

1
1

Japanese alder
White birch
Kanuka
Manuka
Cottonwood
Amercian poplar
Amercian poplar

Willow

IPurple willow
Huckleberry

32

36
36
16

Schiechtl ( 1980)
Schiechtl (1980)
Schiechtl (1980)
!Watson et al. (1997)
Iwatson and O'Loughlin (1985)
Hathaway and Penny (1975)
,Hathaway and Penny(l975)
Hathaway and Penny(l975)
Hathaway and Penny ( 1975)
Hathaway and Pamy (1975)
!Ziemer and Swanston (1977)

22

Chapter 2
Shear strength of soil permeated with the roots of paper birch and
lodgepole pine
2.1 Introduction
Vegetation enhances slope stability, especially when the failure plane is shallow (less than one
metredeep)(Waldron 1977, Wuetal. 1979, WuandSwanston 1980, Waldronetal. 1983,Abe
and Iwamoto 1986, Abe and Ziemer 1991, Ekanayake et al. 1997, Zhou et al. 1998). Roots of
vegetation reinforce soil laterally and vertically, increasing soil cohesion and shear resistance.
Studies have shown that the cohesion or reinforcement provided by roots may vary between
plant species, depending on the morphological and physiological characteristics of the root
system (Waldron 1977, Waldron et al. 1983, Watson and O'Loughlin 1985, Watson et al. 1995,
Ekanayake et al. 1997, Peltola et al. 2000). In situ field and laboratory shear tests of soil blocks
with and without roots have demonstrated the contribution of roots to shear resistance, and the
possible variation of this contribution among plant species (Waldron 1977, Wu et al. 1979,
Waldron et al. 1983, Abe and Iwamoto 1986, Abe and Ziemer 1991, Ekanayake et al. 1997,
Zhou et a. 1998).

2.1.1/n Situ Tests
Researchers have employed similar methods to determine the amount of root reinforcement
provided by vegetation using in situ shear tests (Wu et al. 1979, Abe and Iwamoto 1986,
Ekanayake et al. 1997, Zhou et al. 1998). Soil blocks containing the roots of vegetation and soil
blocks without roots were partially excavated and then sheared in the field. The shearing force
was recorded, and then divided by the area of the shear plane to calculate shear stress. The
maximum shear stress represented the maximum shear resistance of the soil block under a given
23

set of conditions. Comparisons in shear resistance were then made between rooted soil blocks
and unrooted soil blocks to estimate the contribution of the root reinforcement to soil shear
resistance.

Wu et al. ( 1979) tested the shear resistance of soil permeated with the roots of Sitka spruce
(Picea sitchensis (Bong.) Carr.) in both the laboratory and in situ. Stability analyses using the
resulting data indicated that slopes (of similar soil properties) without roots would be unstable,
while slopes with vegetation would be stable. Abe and Iwamoto ( 1986) tested a direct-shear
device at 0.5 m depth using soil blocks containing the roots of 6 year old Cryptomeria japonica
(D. Don) and soil blocks without roots. The rooted samples yielded an 11-34% greater shear
resistance than the unrooted samples. Ekanayake et al. ( 1997) compared the contribution of 2
year old Pinus radiata (D. Don) and 8-16 year old kanuka (Kunzea ericoides var. ericoides (A
Rich.) J. Thompson) roots to soil shear resistance using in situ shear tests of soil blocks at 0.5 m
depth. For both species, soil blocks with roots had about 85% more shear resistance than soil
blocks without roots. Furthermore, soil blocks with roots underwent 90% more displacement
before reaching maximum resistance than soil blocks without roots. There was, however, no
difference in root reinforcement between kanuka and P. radiata. Using in situ tests of soil blocks
permeated with the roots of mature Pinus yunnanensis (French), Zhou et al. (1998) reported that
at 0.20 m depth, rooted soil blocks had 38% greater resistance and withstood 70% more
displacement before reaching maximum resistance than did soil blocks without roots.

2.1.2 Laboratory Tests
The contribution of roots to shear resistance has also been ascertained using laboratory shear
tests (Waldron 1977, Waldron et al. 1983, Abe and Ziemer 1991 ). In addition, the root
24

reinforcement provided by tree and herbaceous species has been compared (Waldron 1977,
Waldron eta!. 1983).

Abe and Ziemer ( 1991) conducted laboratory shear tests on sand with no roots and sand
containing the roots of shore pine (Pinus contorta Doug!. & Loud. var. contorta). Rooted
samples had 18% greater resistance and over 80% more displacement before reaching maximum
resistance than sand samples without roots.

Waldron (1977) compared the shear resistance of soil permeated with alfalfa (Medicago sativa L.
var. Sonora), barley (Hordeum vulgare L.), and ponderosa pine (Pinus ponderosa Douglas ex P.
Laws. & C. Laws.) roots and the shear resistance of soil without roots (fallow) in the nursery.
Cardboard tubes, 0.25 min diameter, and 0.61 min length were filled with soil. Three shear
depths (0.15, 0.30, and 0.45 m) were simulated. Barley tubes (24 plants per container) were
sheared 3 months after planting, while alfalfa tubes (24 plants per container) were sheared 12
months after planting. Ponderosa pine tubes were planted with 1-year-old seedlings and sheared
52 months later. In general, alfalfa had greater shear resistance than barley or ponderosa pine
(Table 2-1). At 0.30 m depth, the increase in shear resistance (compared to fallow tubes) due to
root reinforcement was 10.0 kPa for alfalfa, 2.3 kPa for barley, and 1.0 kPa for ponderosa pine.
The author concluded that the large number of tap roots and vertical roots allowed alfalfa to have
significantly higher shear resistance than ponderosa pine or barley at 0.30 m depth. In addition,
the roots of the ponderosa pine spiraled around the tube container and may not have provided
maximum reinforcement.

25

A similar experiment was carried out by Waldron et al. (1983), using alfalfa and ponderosa pine
in larger containers (1.22 min diameter, and 1.12 min length). Tubes were sheared at a depth of
0.60 m. One hundred and twenty alfalfa plants per container and four 2-year-old pine per
container were planted, while some containers were left unplanted (fallow). Alfalfa and some
fallow tubes were sheared after 12 months and ponderosa pine and the remaining fallow were
sheared after 48 months. Results showed that the rooted soil withstood greater displacements and
had higher resistance than fallow soil (Table 2-1 ). Furthermore, ponderosa pine containers
continued to increase in resistance over all displacements while the resistance of alfalfa
containers leveled off after 25 mm. In all cases, ponderosa pine provided more root
reinforcement to the soil than alfalfa

2.1.3 Effect of Soil Physical Properties on Root Reinforcement
Root growth, and architecture, and therefore root reinforcement, is affected by the physical
properties of soil, including bulk density and soil shear strength (Foil and Ralston 1967, Waldron
1977, Gent et al. 1983, Rab 1994, Ray and Nicoll 1998, Day et al. 1999). Increasing bulk density
decreases root length as growth is inhibited by the loss of voids and macropores in the soil
(Greacen and Sands 1980); bulk density, therefore, is indicative of soil porosity (Brady and Weil
1996, Bulmer 1998). Increasing shear strength also limits root growth when roots are unable to
penetrate the soil (Bulmer 1998). Porosity and strength are a function of soil texture. For
example, coarse textured sand has few pore spaces, and high bulk density, while fine textured
clay has a large number of pores and low bulk density (Brady and Wei] 1996 ). In addition,
coarse textured sand is cohesionless and has low shear strength, while fine textured clay has high
cohesion and high shear strength (Gray and Sotir 1996). Porosity and strength of a soil will not

26

only directly affect root growth, but also can also indirectly affect root growth and architecture
by limiting water and nutrient movement through the soil (Bulmer 1998).

Several studies have demonstrated the effect of soil physical properties on the growth of
broadleaf and coniferous tree root systems. Thomas (2000) mapped out the vertical root
distribution of oak (Quercus spp.) trees growing in Germany and found that the vertical
distribution of roots was different between clay and silt soil. At similar bulk densities, the clay
soil had most roots at depths of 34-37 em, while the silt soil had the majority of roots at 17-22
em. Ray and Nicoll ( 1998) found that roots growing in soil of high shear strength provided
greater reinforcement than roots growing in soil of lower shear strength. Sitka spruce trees
growing on poorly drained soils had shallower root systems, and therefore less root
reinforcement than trees growing on well drained soils (Anderson et al. 1989, Ray and Nicoll
1998).

Downward root growth of flowering dogwood (Comus florida L.) and silver maple (Acer

saccharinum L.) decreased when bulk density increased from 1.2 g/cm 3 to 1.7 g/cm 3 (Day et al.
1999). Eucalyptus (Eucalyptus regnans) height and diameter were affected by bulk densities
greater than 1.0 g/cm 3 (Rab 1994). Several studies have shown that bulk density affected the root
growth, and morphology ofloblolly pine (Pinus taeda L.). At high bulk densities, loblolly pine
had more lateral roots than at lower bulk densities (Foil and Ralston 1967). Loblolly pine root
growth began to be limited at bulk densities of 1.2-1.4 g/cm 3 (Foil and Ralston 1967, Gent et al.
1983) and was completely inhibited at 1.8 g/cm 3 (Foil and Ralston 1967).

27

Results from Waldron (1977) and Waldron et al. ( 1983) indicate that root reinforcement was
affected by soil type and structure (Table 2-1 ). In an experiment by Waldron ( 1977), alfalfa and
barley had more root reinforcement in profile I, while ponderosa pine had more root
reinforcement in profile III. All species had considerably less root reinforcement in profile II,
3

which had loamy sand with a high bulk density of 1.66 g/cm . In Waldron et al. (1983), both
alfalfa and ponderosa pine had more root reinforcement in profile II, which had a gravel mixture
at 0.76 em, and possibly better drainage than profile I.

2.1.4 Shear Tests Using Paper Birch and Lodgepole Pine
This study compared the contribution of paper birch (Betula papyrifera Marsh.) and lodgepole
pine (Pinus contorta Douglas & Loud. var. latifolia Engelm. ex S. Wats) roots to soil shear
resistance using two controlled environment greenhouse experiments. The purpose of this study
was to determine iftree root reinforcement varied between species, populations (seed sources),
and soil textures (bulk density). Several preconceptions, or ideas, were tested in these
experiments. They were as follows :

•!• Paper birch will have greater root reinforcement than lodgepole pine;
•!• Root reinforcement will be differentiated, at the very least, between the highest (1200 m) and
lowest (700 m) elevation seed sources.

•!• Root reinforcement will be greatest in the coarse textured soil, and least in fine textured soil.

Two experiments were carried out between May 1999 and May 2001. The objectives ofthe first
experiment, the Sonotube Experiment, were to compare the root reinforcement of: 1) paper birch
and lodgepole pine growing in one soil type, and 2) six paper birch seed sources from an
elevational transect, to determine if root reinforcement varied genotypically. The objective ofthe
28

second experiment, the Polytube Experiment, was to compare the root reinforcement of paper
birch and lodgepole pine growing in coarse, medium, and fine textured soils.

2.2 Methods

The experiments discussed in this chapter are modeled after Waldron ( 1977) and Waldron et al.
(1983). Refinements to the measurement instruments were made based on the in situ field tests of
Ekanayake et al. ( 1997), and Zhou et al. ( 1998).

2.2.1 Experimental Designs and Procedures
2.2.1.1 Sonotube Experiment
In May 1999, six paper birch populations and one lodgepole pine population were sown at
Canfor' s J. D. Little Nursery in Prince George, BC (Table 2-2). The birch populations,
representing an elevational gradient of seed sources on Tabor Mountain, east ofPrince George
(53°55 ' N, 122° 28'W), ranged from 700-1200 metres (100m intervals) and were grown in 515D
styroblocks (Beaver Plastics, Edmonton, AB). The birch were pruned if their height was greater
than 50 em in the summer of 1999. The lodgepole pine population was collected at an elevation
of735 metres in the McGregor Region, also east ofPrince George (54° 12'N, 121° 48 ' W), and
was grown in 410 styroblocks.

The experimental design is a randomized single-tube plot. Cardboard sono tubes (used as
concrete molds in construction) were 0.70 m in length, and three diameter sizes (0.27, 0.26, and
0.25 m). Three tube sizes were used unintentionally, as it was unknown until time of delivery
that ten inch sonotube could vary in diameter (three tubes fit inside each other for shipping). The
29

three diameter sizes were incorporated into the experimental design as large (0.27 m), medium
(0.26 m), and small tubes (0.25 m). To simulate failure planes at two different depths, the tubes
were cut 0.20 and 0.50 m from the top ofthe tube (Figure 2-1). Spacers were placed between
these cuts and the tubes were reassembled with duct tape. Garbage bags covered the tubes inside
and outside for waterproofing, with perforations in the bottom of the bags to allow water
drainage.

The tubes were filled with a medium textured Gray Luvisol silt to silt loam (Keser et al.1973,
Valentine and Dawson 1978) from a road cutslope, northwest ofPrince George. The soil was
sieved through a 1.5-cm sieve to achieve uniformity and was allowed to settle after repeated
watering until it was approximately 5 em from the top of the tube. The bulk density of the soil in
the tubes was 1.24 g/cm 3.

The experiment included the six birch populations (from 700, 800, 900, 1000, 1100, and 1200
m), the lodgepole pine population, and a control (no trees planted). In August 1999, one tree per
tube was planted for the birch and lodgepole pine treatments. Tubes were arranged on eight
palettes with 16 tubes per palette. Treatments tube size (large, medium, small), planting type
(birch, pine, no-plant), and population ( 1-8, where no-plant and pine tubes were assigned
population numbers 1 and 2 for the statistical analysis) were distributed across the palettes
(Figure 2-2). The palettes were placed outside in October to allow winterization and birch leaf
drop to occur. In November, the palettes were placed in cold storage (-5 to -2°C).

In mid-February the palettes were removed from cold storage and placed in the Enhanced
Forestry Lab at the University of Northern British Columbia (UNBC). Three additional birch and
30

lodgepole pine were planted in each tube to maximize rooting depth and density. The birch trees
were exposed only to natural daylight cycles. The mean daily temperature was 23 .1 °C, and
ranged between 16.1 and 29.3 oc.

The tubes were watered 2-3 times a week. Twenty-five grams of slow release (pelletized) 13N16P-10K fertilizer (Coast Agri, manufacturer) was applied in April, and again in June.
Fertilization was intended to minimize mycorrhizal inoculation and to maximize root growth. On
Aprill4 Safer's soap was sprayed on the birch at a rate of 120 ml in 6 l of water to control
aphids. The application was unsuccessful and on June 1 Cygon dimethoate 240 EC at a rate of
2.5 ml in 5 l water was applied. This was repeated in July when the aphids continued to be a
problem, and this final spray controlled the aphids.

2.2.1.2 Polytube Experiment
In May 2000, paper birch seed from the 900 m Tabor Lake seed source were sown in 515D
styroblocks at UNBC (Table 2-3). Lodgepole pine seedlings, from a different seed source than
the Sonotube Experiment in the McGregor Region at 835 m elevation (registered seedlot
#31389), were grown at Canfor' s J.D. Little Nursery.

The experimental design is a randomized block design. Polyethylene tubes, 0.26 min diameter,
and 0.66 min length were cut 0.22 and 0.44 m from the top to simulate failure planes at these
depths. The tubes were reassembled using three lathe (60 em x 3.5 em x I em) braces per tube
(Figure 2-3). The braces were drilled with screws for spacers at 0.22 and 0.44 m, and then held in
place with plastic strapping. Garbage bags, perforated at the bottom for drainage, were placed in
the tubes.
31

The tubes were filled with coarse, medium, and fine textured soils. Only the fine texture soil was
passed through a 1.5 em sieve to achieve greater uniformity. The coarse textured soil was a
Regosol sand (Keser et al.1973 , Valentine and Dawson 1978) from a cultivated agricultural field
at Red Rock Research Station (south ofPrince George). The medium textured soil was a Gray
Luvisol silt to silt loam (Keser et al.1973, Valentine and Dawson 1978) from a road cutslope,
northeast ofPrince George. The fine texture soil was a Gray Luvisol silty clay to clay (Keser et
al.1973 , Valentine and Dawson 1978), from a road cutslope northwest ofPrince George. All soil
collection sites had some degree of disturbance, and neither the forest floor nor the A horizon
were present.

Over several days, the tubes were filled, watered and then refilled, until the soil was
approximately 3 em from the top. The fine textured clay soil continued to settle after planting
and, in some cases was more than 3 em from the top of the tube. At the time of shearing, the dry
bulk density of the coarse, medium, and fine textured soil was 1.56, 1.39, and 1.50 g/cm 3,
respectively. The bulk density of the clay soil was higher than expected, likely due to the loss of
structure caused by sieving the soil.

Five trees per tube were planted in July 2000 for the birch and lodgepole pine treatments. Tubes
were arranged on four palettes with nine tubes per palette. Each palette represented one block
and contained one lodgepole pine, one birch, and one control (no plant) treatment in each of the
soil types (Figure 2-4). Palettes were arranged north- south in the greenhouse to account for the
effects of the microclimate differences. Until November, the tubes had no supplemental lighting
and the mean daily temperature was 23 .1oc with a range of 16.1 - 29. 3°C. The tubes were
32

watered 2-3 times per week as needed. In the last week of October, the temperatures were
dropped to an average of I 0.3°C with a range of 5.3 - I9.8°C for winterization and birch leaf
drop to occur. Supplemental light was turned on for 8 hours daily. By the third week in
December, birch leaf drop was complete.

In the second week of February, light was increased to a 16 hour period. Temperatures were
turned up for a mean daily temperature of 12.4°C and a range of I 0.3- 26.I °C. On February 8,
50 ppm of potassium fertilizer was applied to encourage root growth. In the beginning of March,
100 ppm of20 N-20 P-20 K (Tune Up, manufacturer) was applied with each watering
application (2-3 times per week).

2.2.2 Shear Device
A shear device, to be used in both experiments, was designed, built and tested in October 2000
(Figure 2-5). The shear device was equipped with a Sensortronics Model60001-2K 'S' -beam
tension loadcell with a 2000 lb (908 kg) capacity (Intertechnology Inc., Don Mills ONT), and a
Campbell Scientific CRlOX datalogger (Campbell Scientific Inc., Edmonton AB) to measure
and record the maximum force exerted on the tube every 0.01 second. Programming information
for the datalogger and loadcell can be found in Appendix A.

The tube to be sheared was secured to the shear device trolleys with compression straps. Trolleys
I and 3 were on wheels, while trolley 2 was immobile (Figure 2-6). The winch and loadcell were
attached to the bottom section of the tube first. The winch was ratcheted for three repetitions
(forwards and backwards) thereby pulling the bottom section of tube toward the winch. The
winch and loadcell were transferred to the top section and the winch was ratcheted for five

repetitions. The number of repetitions for each section was chosen because it ensured that the
maximum force was recorded based on the test run data; this maximum force represented the
shearing force exerted on the tube. The number was larger for the top section as it was observed
that the roots did not break after only three repetitions, most likely due to the presence of more
roots in this section.

2.2.2.1 Sonotube Experiment
Eight trial tubes were used from the initial experiment to determine if the device could
satisfactorily shear the rooted tubes. These tubes were eliminated from the final data set, as the
shearing methods were inconsistent. Height and ground line diameter were measured prior to
shearing all tubes. On October 12-23, 2000 the tubes were sheared. Each day, the tubes to be
sheared were watered in the morning, with the exception of the first day when the tubes were
watered for about 15 minutes at a slow continuous rate. The plastic bag covering the outside of
the tube was removed and the tube was moved to the shear device. The tube was then placed
horizontally on the three trolleys (shear device) so that the shear planes were lined up between
the trolleys.

A soil sample was taken from the bottom and top section of each tube and combined to
determine average soil moisture of the tube. The soil was weighed, dried in paper bags at 105°C
for 24 hours, and then re-weighed to obtain percent moisture content.

It was found with the trial tubes that the roots of the trees had permeated the internal plastic liner
and grown into the sonotube because the tube was wetter than the dense soil inside the tube.
Consequently, the internal liner had to remain uncut along the shear plane. Appendix D contains
34

a sample of the loadcell output data for eleven of the tubes (10% of the data): 6 birch, 3 pine, and
2 fallow tubes. It was assumed that the effect of the plastic bags was constant, especially since
the bags were the same size and brand. Although the bags affected the magnitude of the
resistance, it did not likely affect the differences between birch, pine, no-plant tubes or among
populations.

2.2.2.2 Polytube Experiment
The plastic tubes were sheared May 7 and 8, 2001 . On May 6 all the tubes were watered for a
five count interval. The water was allowed to drain and the process was repeated 2 more times.
The height and diameter of the trees was measured prior to shearing. On the morning of May 7,
three trial tubes were sheared. The equipment functioned satisfactorily, and these tubes were
included in the total data set.

The shearing methods used on the plastic tubes were similar to the methods used in the Sonotube
Experiment. In particular, the plastic bag lining the tube sections was not cut, as it was observed
with the trial tubes that the majority of roots in the fine-textured clay soil were on the surface
between the soil and the liner. The effect of the plastic bag was assumed to be constant
(Appendix D). Soil moisture content was measured for the top and bottom section of tube
separately using a Campbell Scientific Hydrosense soil moisture probe (Campbell Scientific,
Australia).

All birch and pine tubes were retained after shearing for root biomass collection. The roots were
obtained by sifting the soil through a 1.5 em sieve. They were then washed, placed in a labeled
paper bag and dried for 48 hours at 67 °C before being weighed.

35

2.2.3 Statistical Methods
The maximum force (N) recorded by the data logger for the top and bottom tube sections was
selected from the total data set (Figure 2-7). This force was divided by the surface area of the
shear plane to obtain a measure of shear stress (kPa). The surface area ofthe large, medium, and
2

small tubes in the Sonotube Experiment was 0.057, 0.053, 0.049 m tubes respectively, while the
2

surface area of the tubes in the Polytube Experiment was 0.053 m . The effect of tube size in the
Sonotube Experiment was likely minimized by this calculation, but tube size was retained in the
analysis to verify this assumption.

All data were analyzed using a general linear model (GLM) method of analysis of covariance
(ANCOVA) or analysis ofvariance (ANOVA). Data were analyzed using SYSTAT (v.8.0, SPSS
Ltd., 1998). To determine if a covariate was necessary, the proposed ANCOV A model was run,
and the assumptions of ANCOV A were tested. In all cases, the proposed covariate for the
ANCOV A was percent soil moisture because shear resistance decreases with increasing moisture
content (Waldron 1977). If the covariate was not significant in the model (Assumption ofNonzero Slopes) then ANOVA was used. The methods and results of the ANCOVA assumptions
tests can be found in Appendix B. Pairwise differences for significant treatment effects were
determined using orthogonal contrasts.

2.2.3.1 Sonotube Experiment
The proposed incomplete nested ANCOVA model for this experiment was:

RESISI'ANCE =PIANfT\'PE + 1lJBE SI'ZE + PIANfT\'PE * 1lJBE SI7E + PlANT T\'PE (POPUlATION)+
MOISIURE roNilNf

... eqn 2-1
36

where:
RESISTANCE= shear resistance (kPa)
PLANT TYPE= birch, pine, or no-plant
TUBE SIZE= large, medium, or small
MOISTURE CONTENT = percent moisture content
POPULATION
1 =no-plant

5 =birch, 900 m

2 =pine

6 = birch, 1000 m

3 = birch, 700 m

7 =birch, 1100 m

4 = birch, 800 m

8 = birch, 1200 m

Ifthe assumptions of ANCOVA were not met, the following incomplete nested ANOVA model
would be used:

ImiiSTANCE = PIANf'IYft: +lUBE Sl'lE + PIANf'IYft: * 1UBE Sl'lE + PlANf 1Ym (POPUlATION)

... eqn 2-2

All treatments of interest were included in the experiment and therefore the independent
variables were treated as fixed factors. Top (0-0.20 m) and bottom (0.50-0.70 m) sections were
analyzed separately.

2.2.3.2 Polytube Experiment
A complete factorial ANCOV A (3x3) was proposed as follows :

msiSTANCE =PIANf'IYft: +SOIL 1Ym + PIANf'IYft: *SOIL1Ym + MOISilJRECONIENf

... eqn 2-3

where :
RESISTANCE= shear resistance (kPa)
PLANT TYPE= birch, pine, or no-plant

37

SOIL TYPE= coarse, medium, or fine-texture
MOISTURE CONTENT = percent moisture content

The following complete factorial ANOVA model would be used if the assumptions of ANCOVA
were not met:

RFSISfANCE = PlANflYPE +SOIL 1YPE + PlANflYPE *SOIL1YPE

... eqn 2-4

Again, all treatments of interest were sampled in the experiment, and therefore all of the factors
were fixed.

2.2.3.3 Residual Analyses (Assumptions of Linear Statistical Analysis)
Several tests were run to check the assumptions of ANCOVA and ANOV A using the residuals
resulting from the statistical analyses. In particular, the residuals were examined to determine if
they followed a normal distribution, had homogeneity of variance across treatment levels, and
were independent (Wilkinson et al. 1996). The methods used to test the assumptions and the
results of these tests can be found in Appendix C.

2.3 Results
2.3.1 Sonotube Experiment
2.3.1.1 Final Model Selection
The tests ofthe ANCOVA assumptions (Appendix B) indicated that the covariate (moisture
content) was only significant for the top sections of tube, and therefore an ANCOVA would not
38

be appropriate for the bottom sections. Final model selection for the top sections of tube was an
ANCOV A (eqn. 2-1) while the final model selection for the bottom sections was an ANOV A
(eqn. 2-2).

2.3.1.2 Results From Statistical Analyses
Results from the ANCOV A and ANOV A are summarized in Table 2-4 and 2-5 . Significant main
effects were found for planting type at a depth of0.20 m (top sections) (p = 0.019), but not at
0.50 m (bottom sections). At the 0.20 m depth, paper birch trees had 4.061 kPa (22%) more
resistance than no-plant tubes while lodgepole pine had 2.441 kPa (13%) more resistance than
no-plant tubes (Table 2-6). At neither depth were there significant differences in shear resistance
among birch populations, although some variation did occur (Figure 2-8).

2.3.2 Polytube Experiment
2.3.2.1 Final Model Selection
The regression coefficient for the proposed covariate, percent soil moisture content, was not
significantly different from zero in the ANCOV A run for the top or bottom tube sections
(Appendix B). Therefore, the final model chosen for the analyses was the ANOVA model
(equation 2-4 ).

2.3.2.2 Results From Statistical Analyses
For both the top and bottom sections, significant main effects were found for plant type (p <
0.001, and p = 0.004) and soil texture (p = 0.030 and p < 0.001) (Table 2-7 and Table 2-8). There
was no significant interaction between plant type and soil texture.
39

At the 0.22 m and the 0.44 m depth, birch and pine planted tubes had greater resistance than noplant tubes (Table 2-9 and Table 2-1 0). At 0.22 m paper birch contributed to an increase of
12.892 kPa (88%) and lodgepole pine contributed to an increase of8.907 kPa (61%) in
resistance, while at 0.44 m paper birch contributed to an increase of 5.286 kPa (29%) and
lodgepole pine contributed to an increase of 3.713 kPa (21%) in soil resistance. The order of
decreasing shear resistance of the three soil textures at 0.22 and 0.44 m was: fine, medium, and
coarse (Table 2-11 and Table 2-12).

The contribution of roots to soil shear strength varied with soil texture (Table 2-13 and Table
2-14). Both paper birch and lodgepole pine had the highest root reinforcement (112 and 114%
increase from no-plant in the top tube sections) in the coarse textured soil, and the lowest root
reinforcement (56 and 35% increase from no-plant from the top tube sections) in the medium
textured soil. In the fine textured soil, paper birch contributed twice as much root reinforcement
than lodgepole pine ( 102 and 49% increase from no-plant in the top tube sections).

Paper birch had greater root biomass in all soil types, than lodgepole pine (Figure 2-9 to Figure
2-11 ). Paper birch had the most root biomass in silt soil, while lodgepole pine had the most root
biomass in sand soil (Figure 2-12), although these differences would not likely stand up to
statistical testing. Both species had the most root biomass in the top (0-0.22 em) tube sections
(Figure 2-9). Paper birch had the least root biomass in the bottom (0.44-0.66 em) sections
(Figure 2-11) while lodgepole pine had the least root biomass in the middle (0.22-0.44 em)
sections (Figure 2-1 0).

40

Moisture content varied between top and bottom tube sections, and between soil types (Figure
2-13).

2.3.3 Residual Analyses
The residuals from both the Sonotube and Polytube Experiments met the assumptions of
normality, homogeneity of variance, and independence (Appendix C). The models chosen were
therefore appropriate for the analyses undertaken.

2.4 Discussion
The roots of paper birch and lodgepole pine trees contributed to a significant increase in soil
shear resistance, regardless of soil type. At a shear depth of0.20, 0.22 and 0.44 m, paper birch
contributed greater reinforcement than lodgepole pine. There are indications that soil texture
influenced the root reinforcement of paper birch and lodgepole pine trees; both species provided
the most reinforcement in coarse texture soil, and provided the least reinforcement in medium
textured silt soiL

The root reinforcement of paper birch and lodgepole pine at 0.20 min the Sonotube Experiment
was comparable to the root reinforcement at 0.44 m of these species in the Polytube Experiment
The results, although low, were comparable to results reported in the literature for Cryptomeria
japonica, and shore pine (Table 2-15). The root reinforcement of paper birch and lodgepole pine
at 0.22 m in the Polytube Experiment was higher and comparable to the root reinforcement of
kanuka, Pinus radiata and P. ponderosa (Table 2-15), all of which were considerably older than
either the paper birch or lodgepole pine used in this study. At less than one year of age, paper

41

birch trees planted in high densities have greater root reinforcement, up to a depth of half a
metre, than does lodgepole pine (planted at the same density).

Soil texture affected the root reinforcement of paper birch and lodgepole pine. Soil texture
appeared to have little overall effect on root biomass, however, which suggests that the
differences in root reinforcement were not caused by an increase or decrease in root biomass
alone. The effect of root biomass on root reinforcement was still imp rt nt~ paper birch had
greater root biomass and greater root reinforcement than lodgepole pine. Nevertheless, root
biomass within soil types for each species cannot account for the low root reinforcement of paper
birch and lodgepole pine in silt soil. Root density and root depth (both measured by root biomass
in each tube section) were not negatively affected by soil bulk density or shear strength in any of
the experiments.

The silt soil had low bulk density, but had similar shear strength as the clay soil. High porosity,
when combined with high shear strength, appeared to impact root reinforcement. Bulk density
tests in this experiment were not replicated, as suggested by Bulmer ( 1998), but rather were
taken from each section of one t

e ~ the bulk densities provided in this study may not be

representative of the population bulk density. When trying to determine growth limiting soil
physical properties, Bulmer ( 1998) recommends pairing bulk density and shear strength
measurements with measurements of organic matter and moisture content. Analysis of organic
matter content was not done in this experiment, but moisture content was measured with each
tube (Figure 2-13). Percent moisture was higher for the sand soil, in the bottom sections than in
the top, while for the silt soil, moisture was higher in the top sections than in the bottom. The

42

limiting factor ofthe medium textured silt soil may have been, in part, a lack of water and
nutrients.

Observations from the Sonotube Experiment, in which a similar medium textured silt soil was
used, found that the roots of both paper birch and lodgepole pine had spiraled around the outside
of the soil column, in between the plastic liner bag and the soil. Waldron (1977) observed a
similar phenomenon with ponderosa pine, and believed that the spiraling decreased root
reinforcement. The tree roots may have spiraled in the medium textured silt soil because they
were not receiving sufficient water and nutrients within the soil column. This would not
necessarily result in decreased root biomass, but only in decreased root reinforcement.

These preliminary results suggest that root reinforcement can be maximized in well-drained,
coarse textured sandy soils. Root reinforcement may be affected by water and nutrient
availability. To this end, future studies of root reinforcement in different soil types should
incorporate measures of organic matter, in addition to bulk density, shear strength, and moisture
content.

The results from the Polytube Experiment indicated that paper birch and lodgepole pine root
reinforcement was underestimated by the Sonotube Experiment. Overall, paper birch can
contribute as much as 27% more root reinforcement to soil shear strength than lodgepole pine
(Table 2-13 ). The management implications of this experiment are that paper birch of less than
one year of age can substantially increase slope shear strength, and hence slope stability. Even
when trees are planted in plugs, as they were in this experiment, rooting depth, if the species is

43

planted in high densities, can almost reach 0.5 m. Fertilization of the trees will encourage root
and shoot growth, allowing the paper birch to quickly become established on site.

For both experiments, the percent increase in shear resistance attributed to roots was
underestimated by including the effect or resistance of the uncut plastic bags lining the tubes. By
not subtracting out the effect of the plastic bag, the shear resistance ofthe no-plant tubes was
overestimated, which thereby underestimated the increase in shear resistance attributed to birch
or pine roots. This problem could have been eliminated by the systematic testing of the shear
resistance of the plastic bags, but it was not felt that the shear device could accurately measure
this force.

Many problems existed with the design of the Sonotube Experiment. Most of these problems
were corrected in the Polytube Experiment, which resulted in more accurate and higher quality
data. Nevertheless, a few of these problems should be mentioned. The experimental design of the
Sonotube Experiment was very poor. This resulted in a number of issues:

•!• tube size was a confounding factor that should have been eliminated; the result was
incomplete repetitions of each treatment on each palette, which lead to possible
unaccountable microclimate variations;

•!• there were insufficient repetitions of no-plant and lodgepole pine repetitions, and hence a
small sample size for these treatments;

•!• initial planting density per tube was too low, and the fill plant may not have occurred soon
enough to adequately increase root biomass per tube, and;

•!• tube density per palette, the use of cardboard tubes, and the soil density made regular
watering difficult.

44

There was also a disease or fungus (unidentifiable by the greenhouse technicians) that killed
many of the paper birch trees and would again have caused root reinforcement to be less than
expected.

Many of the above problems may have impacted the performance of the 6 seed sources in the
Sonotube Experiment. Preliminary research has shown differences in height, diameter, and root
biomass between paper birch seed sources in BC (Wang et al. 1998a and b, Carlson et al. 2000),
but field trials on the same seed sources used in this study is in the beginning stages. In addition,
Zobel (1995, p. 1189) cautions:
[G]reenhouse and growth chamber growth conditions are not representative of field conditions during
seedling development, and, therefore, results developed under these conditions should be used with caution
when applied to hypotheses about seedling growth under field conditions

Therefore it may be that under field conditions, the Tabor Lake seed sources will show different
genetic traits, including differences in root strength.

Another possibility is that the root reinforcement of the Tabor Lake seed sources is not
differentiated genetically across a 500 m elevational gradient. Rehfeldt ( 1994) gives the example
of western red cedar (Thuja plicata) as a species with a generalist adaptive strategy to
heterogeneous environments. Populations of western red cedar must be separated by 600 m in
elevation before genetic differences are evident. The expectation of this experiment was that the
low elevation (700 m) and high elevation (1200 m) seed sources would have significantly
different root reinforcement when grown in a common environment, where the effect of the
environment on the tree performance was the same for all populations. However, root
reinforcement had little variation between the seed sources, which suggests that the Tabor Lake
birch trees are from one population exhibiting a generalist adaptive strategy with regards to root
45

reinforcement rather than six populations exhibiting a specialist adaptive strategy. Further trials
of these populations should be carried out to confirm the findings of this experiment before
operational management recommendations can be made for the Tabor Lake birch trees. In
particular, other physiological characteristics, such as bud flush and height growth should be
studied to determine if Tabor Lake exhibit a generalist adaptive strategy overall, or just with
respect to root reinforcement.

46

2.5 Tables and Figures
Table 2-1 Results from Waldron (1977) and Waldron et al. (1983) which show the effect of soil type
on root reinforcement.

Experiment
Source

I
Profile I

Soil Type

Bulk Density
3
g!cm

Increase in Resistance of
Planted Soil from Unplanted
Soil(%)

1.20

289

Ponderosa
Pine
66
29

1.66; 1.50

171

40

19

1.20; 1.90

235

35

50

1.00

36

1.00; unknown

45

Alfalfa
I

II

Waldron
(1977)
Ill

I

Waldron et
al. (1983)

II

silt clay loam
loamy sand;
compacted layer
of silty clay loam
(at 30 em)
silty clay loam (030 em); gravel
(30-61 em)
clay loam
clay loam (0-76
em);
gravel/sand/soil
mixture (76-112
em)

Barley

71

-

84

47

Table 2-2 Sonotube Experiment. Height and diameter of the paper birch and lodgepole pine trees at
the time of planting, and at the time of shearing.

Plant
Type
No-Plant
(control)
Pine
Birch
Birch
Birch
Birch
Birch
Birch

Elevation
(m)

-

735
700
800
900
1000
1100
1200

Population

Average
Height at
Planting
(em)

Average
Height at
Shearing
(em)

-

-

1
2
3
4
5
6
7
8

10.679
34.322
32 .969
34.305
29.932
30.025
27.570

27.735
74.828
69.255
66.179
71.055
77.136
71.929

Average
Average
Diameter at Diameter at
Planting
Shearing
(em)
(em)

-

0.329
0.435
0.415
0.405
0.419
0.432
0.382

0.555
0.634
0.623
0.570
0.647
0.694
0.622

Birch Trees -

Sonotube

em

Spacers

Plastic Liner

~

Figure 2-1 Sonotube Experiment. Tube assembly design.

48

Figure 2-2 Sonotube Experiment. Distribution of treatment effects on the palettes.

49

Table 2-3 Polytube Experiment. Height and diameter of the paper birch and lodgepole pine trees at
the time of planting, and at the time of shearing.

Plant
Type

Soil Type

No-Plant Coarse
(control) Medium

Pine

Birch

Fine
Coarse
Medium
Fine
Coarse
Medium
Fine

Average
Height at
Planting
(em)

Average
Height at
Shearing
(em)

-

-

-

10.780
10.356
10.412
22 .384
19.684
17.658

~~

-

.

-

-

-

-

Average
Average
Diameter at Diameter at
Planting
Shearing
(em)
(em)

24.200
17.400
16.640
55 .240
49.520
52.960

0.274
0.263
0.262
0.297
0.288
0.286

-

0.617
0.481
0.489
0.748
0.683
0.746

~

~ ~ f£:1

Birc h trees - -

Polyethelene
tube -

~~
-

I

\

I

Garbage
bag

Lathe_+-IH

braces

'•,

1•-

0.22 m

1:,,
I

Figure 2-3 Polytube Experiment. Tube assembly design.

50

'"b
p

Soil Texture

Figure 2-4 Polytube Experiment. Distribution of treatment effects across the palettes.

51

Compression Straps

Plywood Base

"

I
Winch Mount

•
Datalogger ~

-

Figure 2-5 Top view of the device used in both the Sonotube and Polytube Experiments to shear the
tubes.

Bottom Tube
Trolley
Cable

Winch Cradle

Anchor

Figure 2-6 Side view of the device used in both the Sonotube and Polytube Experiments to shear the
tubes.

52

Bottom and Top Tube Sections, Sonotube Experiment
Large Birch , 1200 m elevation

~

Maximum resistance of top tube

1200

z

Ratchet (forward, backward) of winch

(])

Ji

u

c

.s
(J)

"Ui

(])

800

Maximum resistance of bottom tube

0:::
(6
(])
..c
(f)

Time

Figure 2-7 Data from the Sonotube Experiment, showing the maximum resistance (N) selected out
for the statistical analysis.

Table 2-4 Sonotube Experiment. Results from ANCOVA of shear tests at 0.20 m (top sections).
N: 115
2

R : 0.381

F-ratio
Sum-of-Squares df
p
0.344 0.710
2
16.403
Tube size
4.132
0.019
2 .. -- ··-- -- - --Plant Typ': _ _ -·- -····~ ~~
- - - -- - ----20.792 o:ooo
1
Moisture content
495 .246
1.460 0.220
4
139.067
Plant Type* Tube size
0.979 0.434
5
Population(Piant Type)
116.628
I
I
Error
2381.948 1100
Factor

53

Table 2-5 Sono tube Experiment. Results from ANOVA of shear tests at 0.50 m (bottom sections).
N:llS
R 2 : 0.139

Factor

Tube size
Plant Type
Plant Type* Tube size
Population(Piant Type)
Error

Sum-of-Squares df F-ratio
0.665
26.287
2
1.426
56.372
2
125 .088
4
1.583
82.247
5
0.832
1995.658 101

p
0.516
0.245
0.185
0.530

Table 2-6 Sonotube Experiment. Comparison of adjusted least square mean shear resistance (kPa)
and root reinforcement by planting type of shear tests at 0.20 m (top sections). Shear resistances
foUowed by the same letters were not statistically different.

Plant
Type
Birch
Pine
No-Plant

Adjusted Least
Square Mean
Resistance (kPa)
22.807 a
21.187 a,b
18.746 b

Standard
E"or

Sample
Number

0.551
1.194
1.301

82
17
16

Root
Reinforcement
(kPa)

-

4.061
2.441

Increase
from NoPlant(%)

-

21.6
13.0

700 800 900 1 000 11 00 1200 1300
Birch Seed Source Bevation (m)

Figure 2-8 Sonotube Experiment. Adjusted least square mean shear resistance (kPa) and standard
error for 6 birch populations of shear tests at 0.20 m (top sections).

54

Table 2-7 Polytube Experiment. Results from the AN OVA of shear tests at 0.22 m (top sections).
N: 45
R2 : 0.656

Factor
Plant Type
Soil Type
Plant Type* Soil Type
Error

Sum-of-Squares df F-ratio
p
1307.128
2 27.016 <0.001
186.994
3.865
0.030
2
164.007
4
1.695
0.173
870.910 36

Table 2-8 Polytube Experiment. Results from the ANOVA of shear tests at 0.44 m (bottom
sections).
N: 45
R2 : 0.586
Factor
Plant Type
Soil Type
Plant Type*Soil Type
Error

Sum-of-Squares df F-ratio
p
221 .040 2
6.539
0.004
589.557 2 17.442 <0.001
52.244 4
0.773
0.550
608.421 36

Table 2-9 Polytube Experiment. Adjusted least square mean resistance (kPa) for each plant type in
aU soil textures at 0.22 m (top sections). Shear resistances followed by the same letters were not
statistically different.

Plant
Type
Birch
Pine
No-Plant

Adjusted Least
Square Mean
Resistance (kPa)
27.578 a
23.593 b
14.686 c

Standard
E"or

Sample
Number

1.270
1.270
1.270

15
15
15

Root
Reinforcement
(kPa)

-

12.892
8.907

Increase
from NoPlant(%)

-

88
61

Table 2-10 Polytube Experiment. Adjusted least square mean resistance (kPa) for each plant type

in aU soil textures at 0.44 m (bottom sections). Shear resistances foUowed by the same letters were

not statisticaUy different.

Plant
Type
Birch
I
Pine
No-Plant !

Adjusted Least
Root
Increase
Standard Sample
Square Mean
Reinforcement from NoNumber
E"or
(kPa)
Resistance (kPa)
Plant(%)
15
5.286
29
1.061
23.345 a
3.713
15
21
1.061
21.772 a
1.061
18.059 b l
t5 l
I

55

Table 2-11 Polytube Experiment. Adjusted least square mean resistance (kPa) for each soil texture
and aU plant types at 0.22 m (top sections). Shear resistances foUowed by the same letters were not
statistically different.
!

I

Adjusted Least Square
Standard
Soil
Mean Resistance
Texture
E"or
(kPa)

Sample
Number

1.270
1.270
1.270

15
15
15

19.947 a
21.162 a,b
24.749 b

Coarse
Medium
Fine

Table 2-12 Polytube Experiment. Adjusted Least Square Mean Resistance (kPa) for each soil
texture and all plant types at 0.44 m (bottom sections). Shear resistance followed by the same letters
were not statistically different.

Soil
Texture

Adjusted Least
Square Mean
Resistance (kPa)

Standard
E"or

Sample
Number

1.061
1.061
1.061

15
15
15

16.876 a
20.594 b
25 .705 b

Coarse
Medium
Fine

Table 2-13 Polytube Experiment. Adjusted least square mean resistance (kPa) for each plant type
and soil texture at 0.22 m (top sections).

Soil
Texture

Plant
Type

Birch
Coarse Pine
Fallow
Birch
Medium Pine
Fallow
Birch
Fine
Pine
Fallow

Adjusted Least
Square Mean
Resistance (kPa)
24.134
24.349
11.358
25 .334
21.904
16.248
33.267
24.526
16.452

Standard
Error

Sample
Number

2.200
2.200
2.200
2.200
2.200
2.200
2.200
2.200
2.200

5
5
5
5
5
5
5
5
5

Root
Increase
Reinforcement from No(kPa)
Plant(%)

-

12.776
12.991
9.086
5.656
16.815
8.074

-

112
114
56
35
102
49

56

Table 2-14 Polytube Experiment. Adjusted least square mean resistance (kPa) for each plant
texture and soil type at 0.44 m (bottom sections).
I

I

Soil
Texture i

Ii

Plant
Type

Adjusted Least
Square Mean
Resistance (kPa)

Standard
E"or

~

~

5
5
5
5
5
5
5
5
5

1.839
1.839
1.839
1.8391
1.839
1.839
1.839
1.839
1.839

18.774
18.489
13.364
21.386
21.582
18.815
29.875
25 .245
21.997

Birch
Coarse Pine
Fallow
Birch
Medium Pine
Fallow
Birch
Fine
Pine
Fallow

I

Root
Sample i
Reinforcement
Number I
(kPa)

~

-

5.41
5.125
2.571
2.767
7.878
3.248

~

28

§

::·:

::: 21

"'

E
.2

co 14
()

:;,:

rn §
§
~

0

~

··l':

7

I=

~

:T
'''·
~
~

~
~

::y

:
.~

~

~

~
~

~
~

~

~

~

=

Soil Texture

~
E

o Coarse
1!1 Fine
o Medium

Birch
Pine
Plant Type

Figure 2-9 Polytube Experiment. Mean Root biomass (g) and standard error in the top sections (00.22 m) of tube.

57

§

::: 21

~
0

iii 14

;s
0

0::

Soil Texture

Birch
Pine
Plant Type

o Coarse
Rlfine
1:1 Medium

Figure 2-10 Polytube Experiment. Mean Root biomass (g) and standard error in the middle sections
(0.22- 0.44 m) of tube.

28

§

::: 21

~

iii 14

;s
0

0::

Soil Texture

7

Birch
Pine
Plant Type

o Coarse
~ fine
1:1 Medium

Figure 2-11 Polytube Experiment. Mean Root biomass (g) and standard error in the bottom
sections (0.44- 0.66 m) of tube.

58

40

=

§ 30

.."'"'

:•:
:..:-

E

;;.:·

0

iii 20

>:·
~

00

~

::::::

~
=

§
E

tr

ii

0 10

.;

1-

y

..=·:-

~

0

§

§I=

~

I'

~~

!,I

i,

;:
Soil Texture

~

o

~

~e

Fine
o Medium
~

Birch
Pine
Plant Type

Figure 2-12 Polytube Experiment. Combined root biomass (g) of the top, middle, and bottom tube
sections.

Table 2-15 Summary of increased resistance from the literature and from this chapter.

Shear
Depth (m)

Experiment Source

Plant Species

Increase in
Resistance (%)

alfalfa
barley
ponderosa pine
alfalfa
ponderosa pine

171-289
35-66
19-50
36-45
71-84

Waldron (1977)

0.30

Waldron et al. (1983)

0.60

Abe & Iwamoto (1986)

0.50

Cryptomeria japonica

11-34

Abe & Ziemer (1991)

nfa

shore pine

18

Ekanayake et al. (1997)

0.50

Pinus radiata
kanuka

85
85

Zhou et al. (1998)

0.20

Pinus yunnanensis

38

Sonotube Experiment

0.20

paper birch
lodgepole pine
paper birch
lodgepole pine
paper birch
lodgepole pine

22
13
88
61
29
21

Polytube Experiment

I
I

0.22
0.44

59

Bottom Tube Sections

Top Tube Sect1ons
70

70

60

60

'li50

1150

<'
0

.,

';:40
~

120
a. 10

0

t--

$
c

Sol Texture

~
"'

~

';:40
::;

i ~

:;

i20

l10

0

~ Q~
c

F
Soil Texltre

"'

Figure 2-13 Percent soil moisture oftop and bottom tube sections, by soil texture.

60

Chapter 3
Vertical tree uprooting of paper birch and lodgepole pine: a case
study of three field locations
3.1 Introduction
Tree stability analyses have been used to study root strength in situ (Anderson et al. 1989,
Krasowski et al. 1996, Papesch et al. 1997, Ray and Nicoll 1998, Peltola et al. 2000). This type
of analysis has traditionally been employed to compare windfirmness between stands of trees, or
to compare windfirmness between species. By applying a horizontal or lateral force on a tree, the
force required to break the roots and uproot the tree can be measured (Anderson et al. 1989,
Krasowski et al. 1996, Papesch et al. 1997, Ray and Nicoll 1998, Peltola et al. 2000).

Vertical tree uprooting has also been used to evaluate the root anchorage and buttressing effects
of trees on a slope (Nilaweera 1994, Nilaweera and Nutalaya 1999). Vertical uprooting
resistance is a function of both root tensile strength and root morphology (Nilaweera 1994, Gray
and Sotir 1996, Nilaweera and Nutalaya 1999). Both root shear and tensile strength are important
components of root reinforcement, especially on slopes prone to shallow mass failure events
(O'Loughlin 1974, Burroughs and Thomas 1977, Waldron 1977, Abe and Iwamoto 1986,
Ekanayake et al. 1997, Wu and Watson 1998, Zhou et al. 1998).

Using tree stability analyses, comparisons in root reinforcement caused by root strength and
morphology can be made in situ between different tree species (Nilaweera 1994, Nilaweera and
Nutalaya 1999, Peltola et al. 2000), and between the same species growing under different
environmental conditions (Anderson et al. 1989, Krasowski et al. 1996, Ray and Nicoll 1998).

61

The effectiveness of the root reinforcement at maintaining or enhancing slope stability under
certain environmental conditions can then be discerned.

3. 1.1 Tree Stability Analyses
Anderson et al. ( 1989) investigated the shear strength of Sitka spruce (Picea sitchensis (Bong.)
Carr.) tree roots !,lfOwing on peaty gley, brown earth, and basin peat and found that trees growing
on the brown earth where root growth was unimpeded by the water table had the greatest
strength. Results from a study by Ray and Nicoll ( 1998), also of Sitka spruce, concur with
Anderson et al. ( 1989). Sitka spruce trees growing in waterlogged conditions had less resistance
to horizontal uprooting than trees growing in drier conditions.

Krasowski et al. ( 1996) demonstrated the effect of site conditions on root strength and root
reinforcement by horizontally uprooting lodgepole pine (Pinus contorta Dougl. ex Loud. var.

latifo/ia Engelm.) at six field sites in the central interior of British Columbia. In addition, the
stability of naturally regenerated trees and the stability of trees grown under various nursery
cultures was compared. Results indicated that the method of regeneration was not as important to
tree stability as differences in site soil physical properties.

Researchers have compared the resistance to uprooting of different tree species using tree
uprooting tests. Nilaweera and Nutalaya (1999) vertically uprooted seven one-year-old hardwood
tree species and found variation in the pull-out resistance (Table 3-1 ). Peltola et al. (2000)
horizontally uprooted Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) Karst.),
and birch (Betula spp.), ranging in age between 40-100 years; the order in decreasing resistance
to uprooting was Scots pine, birch, Norway spruce.
62

3.1.2 Root Reinforcement of Paper Birch and Lodgepole Pine
This chapter compares the vertical uprooting resistance of young (< 15 years) paper birch (Betula

papyrifera Marsh.) and lodgepole pine (Pinus contorta Douglas & Loud. var latifolia Engelm. ex
S. Wats) growing at three field study sites. In a study using similar methods, vertical uprooting
of hardwood trees produced values several magnitudes smaller than horizontal uprooting, but
measured inter-species' differences as accurately (Nilaweera 1994, Nilaweera and Nutalaya
1999). In the same study, vertical uprooting resistance was significantly related to root tensile
strength multiplied by the root volume (Nilaweera 1994 ).

The objectives of this study were to determine the differences in root reinforcement provided by
paper birch and lodgepole pine, and to determine the effect of site conditions, and more
specifically soil type, on root reinforcement.

3.2 Methods
3.2.1 Experimental Design and Procedures
Three field sites, of contrasting soil types, were chosen based on the presence of young (< 15
years old) paper birch and lodgepole pine (Figure 3-1 ). Sites at Red Rock Research Station,
Gregg Creek, and Aleza Lake Research Forest represented a range in the soil types found in the
Prince George Forest Region 3. A summary of the site information can be found in
Table 3-2.

3

P. Sanborn. pers. comm. 2000. Forest Soil Specialist. Forest Resources. BC Ministry of Forests. Email:

Paul. Sanbom@gems9 .gov .be.ca.

63

3.2.1.1 Red Rock
The paper birch and lodgepole pine trees sampled at Red Rock were from research trials
established by the British Columbia Ministry of Forests (see Chapter 4). In 1996, a 4 seed source
paper birch trial was planted with 1+0 415A and 515D stocktypes in 10-tree rows with an in-row
spacing of0.5 m and a between row spacing of 1.0 m. Every summer, 50 g of l3N-16P-10K
fertilizer was applied to each tree. The lodgepole pine trial was established circa. 1988. The trees
were planted in 4-tree rows with an in-row and between-row spacing ofless than 0.5 m. This
lodgepole pine trial was used as it was the only young pine trial at Red Rock Research Station.

For the purpose of this study all paper birch seed sources and other trial treatments (nursery
where the stock was grown, stocktype, and pruning treatment) were pooled. The results from
these trees, therefore, may not best represent the actual growing conditions of paper birch on this
soil type. Within the paper birch trial, the macroenvironment was the same for all seed sources.
The variation within the site, therefore, was caused by the genetic variation among the seed
sources. This variation may have confounded the effect of the soil texture on paper birch root
reinforcement.

The soil at Red Rock was a Regosol sand to sandy loam (Keser et al. 1973, Valentine and
Dawson 1978). Dry bulk density ranged from 1.36-1.41 g/cm 3 under the birch, and from 1.051.20 g/cm 3 under the pine. The birch site had higher bulk density because of repeated cultivation,

64

which has caused a hardpan to develop at 25-30 em

ept ~ this hardpan may also affect the

rooting depth of the birch4 .

3.2.1.2 Gregg Creek
The Gregg Creek site had naturally regenerated paper birch, and naturally and artificially
regenerated lodgepole pine. The block was logged by the licensee, Canfor, in the summer of
1990 and planted in the spring with 1+0 313 Douglas-fir (Pseudotsuga menziesii Mirb. Franco)
and 1+0 211 lodgepole pine at 1350 stems per hectare. The soil was a Gray Luvisol sandy loam
(Keser et al. 1973, Valentine and Dawson 1978). Dry bulk density ranged across the site from
0.99 to 1.43 glcm 3.

3.2. 1.3 Aleza Lake
Two sites were chosen at Aleza Lake. The first site, located in the Aleza Lake Research Forest,
had naturally regenerated paper birch. Heavy moose browse of the birch had occurred at this site.
The block was logged prior to 1988, and spring planted (in 1988) with 1+0 313A Douglas-fir,
2+0 313A interior spruce (Picea glauca (Moench) Voss x engelmannii Parry ex Engelm.), for a
total of 1628 stems per hectare. The soil was a Gray Luvisol clay (Keser et al. 1973, Valentine
and Dawson 1978). Dry bulk density ranged between 0.96-1.25 glcm 3 .

The second block was located near the southern boundary of the Aleza Lake Research Forest.
The licensee, Canfor, had salvage logged the site in 1993 after a fire, and replanted in the spring

4

C.D.B. Hawkins. pers. comm. 2001 . FRBC - Slocan Endowed Chair ofMixedwood Ecology and Management.

UNBC . Email : hawkinsc@unbc.ca.

65

of 1994 with 1+0 313 interior spruce and 1+0 313 lodgepole pine, for a total of 1400 stems per
hectare. The soil at this site was a Gray Luvisol silty clay loam (Keser et al. 1973, Valentine and
Dawson 1978), and bulk density ranged between 0.86-0.91 g/cm 3 .

3.2.1.4 Sampling Methods
Trial horizontal tree uprooting of paper birch was not successful as the flexible stems prevented
the tree from uprooting. Nilaweera and Nutalaya (1999) encountered similar problems with
horizontal uprooting tests of young hardwood species, and discontinued use of this method. In
the study discussed in this chapter, only vertical uprooting tests were carried out.

An initial visit was made to each field site (Gregg Creek and Aleza Lake) to determine soil

uniformity. Transects were laid out and a soil pit dug every 50 m. Any obvious soil changes
(such as swampy areas) were noted and these areas were avoided during the sampling.

At each site the paper birch trees were sampled once a week over a 12 week period (JulySeptember) while the lodgepole pine trees were sampled over a 6 week period (AugustSeptember). At the field sites a directional bearing was chosen and trees were sampled along this
transect, within a 30 m width. Between 30-80 trees were sampled each day depending on the
weather and ease of pulling. Throughout the day at each site, three soil samples were obtained
for soil moisture content.

Prior to uprooting, trees were cut approximately 15-20 em from the base and the ground line
diameter was measured. In addition, number of birch stems was noted. At the field sites, trees

66

were coded with a 0 (no vegetation), 1 (moderate vegetation), or 2 (heavy vegetation) to indicate
the density of surrounding vegetation and possible level of inter-specific competition.

Trees were uprooted using a winch and tripod device (Figure 3-2). A 2000 lb (908 kg) capacity
Sensortronics Model60001K ' S' -beam tension loadcell (lntertechnology Inc., Don Mills Ont.)
and a CRIOX Campbell Scientific datalogger (Campbell Scientific Inc., Edmonton AB) recorded
the force being exerted on the tree every 0.01 seconds (Appendix A). A manual winch was
attached to a wooden tripod and placed over the stump of each tree. The loadcell was fixed to the
stump of the tree using a pipe wrench, and the winch was attached to the loadcell. The winch was
then ratcheted upwards until all roots broke or the stump reached the end of the winch cable. If it
was felt that the maximum force required to uproot the tree was not obtained, often indicated by
no release in pulling pressure by the person operating the winch, then this was noted and the data
were later excluded from the data set.

A sample of the uprooted stumps was collected from all sites. Roots were cleaned, placed in
paper bags, and dried for 48 hours at 67°C to obtain a measure of root biomass.

3.2.2 Statistical Methods
Data were analyzed using SYSTAT (v. 8.0, SPSS Ltd., 1998).

The maximum force (N) required to vertically uproot each tree was selected out of the original
data set (Figure 3-5). This force represented the maximwn resistance of the tree to uprooting in a
vertical direction.

67

The data were analyzed using a general linear model (GLM) method of analysis of covariance
(ANCOVA). The proposed covariate for the analysis was tree ground line diameter. The
assumptions of ANCOVA (Appendix B) and the assumptions oflinear analysis (Appendix C)
were tested, and, if necessary, the proposed ANCOVA model was revised.

A simple scatterplot of the data (Figure 3-3) indicated that the relationship between resistance
force and tree diameter was exponential, rather than linear. To correct for this, both variables
were logarithmically transformed (Wilkinson et al. 1996).

Soil moisture data were graphed (Figure 3-4) and it was determined that, although some
variation occurred over the sampling days at each site, the variation in soil moisture was similar
at all sites. For example, at all sites soil moisture was lowest around Julian Day 215-216. Soil
moisture was considerably different at each site; Aleza Lake was the wettest and Red Rock was
the driest. This was accounted for, in part, by soil type, and therefore the variation was
eliminated in the statistical analysis.

The proposed incomplete nested ANCOVA model was:

RFSISTAN<E = PlANf'IYPE +I.OC'ATION+Nl.JMHER OFSIE!\fi(PIANI''IYPE)+ VEGETATION (lOCATION)+

••• eqn. 3-1

IIAMEIER

where:
RESISTANCE= pulling force, with a logarithmic transformation
PLANT TYPE= paper birch or lodgepole pine
LOCATION= Aleza Lake, Gregg Creek, Red Rock
NUMBER OF STEMS = number of birch main stems

68

VEGETATION = density of vegetation surrounding the tree at the field sites
DIAMETER = diameter, with a logarithmic transformation

Although the variable location, as represented primarily by soil properties, could be considered a
random factor, rather than a fixed factor, it was decided that only fixed factors would be used in
the analysis. The limitations of such as decision in interpretation were appropriate as only one
site of each soil type was sampled, and inferences beyond each site were not valid. Pairwise
differences for significant treatment effects were determined using orthogonal contrasts.

Mean root biomass and standard error were calculated for each field location, species, and for
each species at each field site, to compare the biomass with the results from the uprooting tests.

3.3 Results
3.3.1 Final Model Selection
The final model that arose from the tests of ANCOV A was as follows :

RINSTANCE =PlANflYPE +I.DCATION +NUMBER OF SIEl\fi (PlANf"'YPE)+ VF..GEI'ATION (I.DCATION)

, • , eqn. 3-2

+I.DCATION * DIAMEIER+DIAMEIER

where:
RESISTANCE= pulling force, with a logarithmic transformation
PLANT TYPE= paper birch or lodgepole pine
LOCATION= Aleza Lake, Gregg Creek, Red Rock
NUMBER OF STEMS= number of birch main stems
VEGETATION = density of vegetation surrounding the tree at the field sites
DIAMETER = diameter, with a logarithmic transformation

69

3.3.2 Results From Statistical Analyses
The results from the ANCOVA are summarized in (Table 3-3). Significant differences in the
resistance to vertical uprooting were found for the factors location (p < 0.001) and plant type (p

< 0.001 ). Significant interactions were found for the nested variables number of stems, and
location (p < 0.001), and for the interaction oflocation and diameter (p = 0.018).

Paper birch trees had significantly greater resistance to vertical uprooting than did lodgepole pine
trees at all field locations (Table 3-4 ). Both paper birch and lodgepole pine trees growing at
Aleza Lake had significantly more resistance to uprooting than at the other field sites (Table
3-5). However, this only was true for trees with smaller diameters, as larger diameter trees at
Gregg Creek and Red Rock had greater resistance than similar diameter trees at Aleza Lake
(Figure 3-6). Paper birch trees at all field sites that had three main stems had greater resistance
than trees with 1, 2, or 4 main stems, although sample size is small (Table 3-6). Density of
vegetation around the tree being pulled did not affect the resistance to uprooting.

Pine had, on average, greater root biomass than paper birch, and less resistance per unit root
biomass (Table 3-7). Trees growing at Aleza Lake had the most root biomass and the most
resistance per unit root biomass (Table 3-8). Trees growing at Aleza Lake had greater root
biomass at the smaller diameters, but again was surpassed by the root biomass of trees growing
at Gregg Creek and Red Rock at larger diameters (Figure 3-7).

70

3.4 Discussion
Vertical tree uprooting is an uncommon measure of root strength. More often, researchers have
measured root anchorage strength using horizontal tree uprooting (Anderson et al. 1989,
Krasowski et al. 1996, Ray and Nicoll 1998, Peltola et al. 2000), root tensile strength using
individual root breakage tests (Burroughs and Thomas 1977, Ziemer and Swanston 1977,
Watson and O' Loughlin 1985, Watson et al. 1997, Watson 2000), and root shear strength using
shear tests of soil blocks (Waldron 1977, Waldron et al. 1983, Abe and Iwamoto 1986,
Ekanayake et al. 1997, Zhou et al. 1998). Results from the vertical uprooting tests of paper birch
and lodgepole pine are similar to those presented by Nilaweera (1994) and Nilaweera and
Nutalaya ( 1999) from vertical uprooting tests of 7 hardwood (broadleaf) tree species in Thailand
(Table 3-1). Vertical uprooting tests are useful to compare the contribution of roots to soil
strength of young trees, especially hardwood species with flexible stems.

The previous chapter (2) determined that paper birch provided more root reinforcement to soil
shear strength than lodgepole pine, when grown under controlled nursery conditions. This field
study concurred with the results of the nursery shear tests. Young paper birch trees had greater
resistance to uprooting than did young lodgepole pine trees at all three field locations. Interspecific differences in tree uprooting have been noted by other researchers. Eighty year old birch
species uprooted by Peltola et al. (2000) had greater horizontal uprooting resistance than 80 year
old Norway spruce, but less resistance than Scots pine (40-100 years old). Nilaweera (1994) and
Nilaweera and Nutalaya (1999) reported vertical uprooting resistance differences between
hardwood species such as Ficus benjamina and Hevea braziliensis (Table 3-1 ), both of which
had the most and least resistance, respectively, to vertical and horizontal uprooting. In this study,
paper birch (at all sites) had twice as much resistance to uprooting as did lodgepole pine (Table
71

3-4 ). When considered with the results from Chapter 2, the data suggest that young paper birch
trees in the Prince George Forest Region have greater root strength and root reinforcement than
young lodgepole pine trees, regardless of the growing environment.

Tree resistance to uprooting varied between field locations, and therefore possibly with soil type.
Other tree stability analyses have demonstrated the impact of soil characteristics on resistance to
uprooting (Anderson et al. 1989, Krasowski et al. 1996, Ray and Nicolll998). In particular, soil
shear strength (Krasowski et al. 1996, Ray and Nicolll998), and moisture content (Anderson et
al. 1989, Ray and Nicoll 1998), affected root anchorage, and rooting depth, and consequently
affected resistance to uprooting. Both shear strength and moisture content are related to soil
texture (Bulmer 1998).

Soil shear strength and moisture content may account for the root reinforcement differences per
unit diameter at Aleza Lake for paper birch and lodgepole pine (Figure 3-6). Ray and Nicoll
( 1998) reported that Sitka spruce trees growing in soil with high shear strength had greater
resistance to uprooting than trees growing in soil with low shear strength. Krasowski et al.
(1996) found that trees growing in loamy sand and gravelly loam underlain by compacted loamy
glacial till (which may have greater strength though this was not tested) had greater resistance to
uprooting than trees growing on gravelly loamy sand. Furthermore, Anderson et al. ( 1989) found
that trees growing on soil with a stony layer within rooting depth also had greater stability.

The clay soil at Aleza Lake probably had higher shear strength than the sand and sandy loam
soils at Red Rock and Gregg Creek. In Chapter 2, fine textured clay soils had higher shear
strength than coarse textured sand (Table 2-13). At small diameters, the resistance to uprooting
72

of paper birch and lodgepole pine at Aleza Lake would be notably higher than the resistance of
trees at Red Rock and Gregg Creek. Most of the resistance to uprooting at these small diameters,
where roots have only begun to develop, could be attributed to soil shear strength. As
demonstrated by the shear tests in Chapter 2, the contribution of root reinforcement, although
possibly significant for slope stability, can be as small as 20% (Table 2-10); soil essentially has
greater strength than the roots alone.

As the trees at all sites aged and grew more roots, rooting depth may have been important.
Researchers have found a significant relationship between rooting depth and tree resistance to
uprooting (Anderson et al. 1989, Ekanayak:e et al. 1997, Ray and Nicoll 1998, Peltola et al.
2000). High moisture content, combined with high soil shear strength (which can prevent root
penetration into the soil (Bulmer 1998)), may have restricted rooting depth at Aleza Lake. Once
tree roots at Red Rock and Gregg Creek had reached a certain depth, tree resistance would
surpass the resistance of trees at Aleza Lake. The implication of these results is that paper birch
and lodgepole pine at Aleza Lake may have less root reinforcement than determined by the
uprooting tests and therefore, these results did not conflict with the results of the nursery tests in
Chapter 2 where root reinforcement for both species was greatest in coarse textured sand (Table
2-13).

The effect of soil shear strength, rather than soil texture or soil bulk density, on root
reinforcement may be a more appropriate avenue for further research. Without measures of soil
strength, site to site comparisons of root reinforcement are not possible using vertical tree
uprooting methods. Shear strength can be measured by various methods, the easiest of which is
to use a penetrometer to sample extensively across a site (Bulmer 1998). Optimally, a
73

penetrometer could measure the shear strength of the soil near each tree prior to uprooting,
although its use is limited in rocky soils. Vertical uprooting tests alone cannot determine the
effect of soil type on root reinforcement in the field, especially when substantial variation in soil
texture and tree age can occur at a site.

Both Krasowski et al. (1996) and Ray and Nicoll (1998), reported uprooting variation within a
site, even when trees were of a known age. In this study, paper birch and lodgepole pine trees at
Gregg Creek, and paper birch trees at Aleza Lake varied in age. At Red Rock, paper birch trees
were younger and lodgepole pine trees were older, than the trees at the field sites. It should be
noted, however, at Red Rock, that five-year-old paper birch had the same resistance to uprooting
as did 15-year-old lodgepole. In addition, regeneration method (natural vs. artificial) varied for
both species. This influence was not determined in this study, although Krasowski et al. (1996)
reported that there was no difference in tree stability between regeneration types of lodgepole
pine after 11-21 years.

It is also possible that soil nutrients, amount of local precipitation, moose browse, and seasonal

temperature fluctuations could affect the growth rate, and therefore the resistance to uprooting,
of paper birch and lodgepole pine trees. As will be demonstrated in the following chapter, seed
source (local population adaptations) can affect the root reinforcement of paper birch. Therefore,
although this study found differences in tree resistance to uprooting at three different field sites
(and possibly different soil types), further study is needed to confidently determine the cause of
these differences.

74

This chapter demonstrated that young paper birch has greater root reinforcement in the field than
young lodgepole pine, regardless of soil type. Planting young paper birch trees on unstable
slopes could substantially increase slope shear strength and thereby decrease the probability of
failure. Within the first 12-15 years of growth, paper birch provides as much as twice the root
reinforcement to slope shear strength as lodgepole pine (Table 3-4 ). These results are for paper
birch trees planted in birch-conifer mixtures. Pure plantations of paper birch, especially when
planted at high densities, could provide much higher root reinforcement than the results
presented in this study. Depending on the management goals for the site, paper birch planted in
pure or mixed stands could substantially increase slope stability. This species should be
considered for use in any terrain stabilization project in BC in the future.

75

3.5 Figures and Tables
Table 3-1 Results of vertical uprooting tests by Nilaweera (1994) in Thailand.
Species

Dipterocarpus alatus
Hopea oderata
Astonia macrophylla
Hibiscus macrophyllus
Ficus benjamina
Hevea braziliensis

Uprooting
Resistance (kN)
1.81
I
1.94
I
2.46
;
4.00
4.67
1.36

76

Gregg Creek •
Red Rock•

0

Kilometres

300

Figure 3-1 Location of field sites.

77

Table 3-2 Site information
l

!

Fidd Site
Lociltio11
Rod Rock

I extt~re
Soil ~ Soil T
I &oteoc/Uwatic
I . ~ LIHrtihl«
(tJerrees
ype i
Zo11e
'

mm~~

.,;,.,nes)

SBSmkl

53 45

122 41

SBSdw3

53 40

123 IS

SBSwk1

54 03

12202

1

~

sand
saudy

CrMk

loam

Alfta
Lako

I

clay
(birch);
sihy clay
loam

(pine)

Rcgosol [
Gray
Luvisol

I

Gray
Luvisol

I

1

I Soil BII/Jc I
Mped

Dmsity

I r/CIII '

Southwest
(birch)·
East (pU:C)

I A.....at
~t

(defrees
Cdsuu)

fHIPD

/JUdo

Ate of
/JN/repok
pilte

(ye.n)

et~n

A"""al

T011perlllllTe

I Ate of

(•111)

(CIII)

1.06-1.41

727.4

306.3

u

0.99-1.43

494.4

204.2

2.6

3 to 10

3 to 10

930.9

333.7

2.6

3 to 12

6

I

none
East and
southwest

A .....al
Pret:ipittllimt

s

IS

0.96- 1.25

I (birch);
~ ~
pme

I

Loadcell
Loadcell Wire
Data logger

Figure 3-2 Tripod and winch setup for the vertical uprooting of paper birch and lodgepole pine.

78

7

~

z.::.:.

+

Cll

oo
0

oo

'0

0

0
0

ooo

°0 0
'¢00

0
0

0

~

i

~

0

~

oO

-;-4
u

c

s, 3

"iii

G.l

0:::

2

0

0

0

2

5
3
4
Diameter (em)

6

0

7

Figure 3-3 Scatterplot of the field data: tree resistance to vertical uprooting (kN) versus tree
ground line diameter (em).

79

Gregg Creek

Aleza Lake
45

~

"£

.
i

~ 27

u

f

<(

~i

~ ~

~ ~

~

16

9

.n

0
190 200 210 221l ZID 240 250 260
JWnO..,.

~

Red Rock

t36
~

~ 27

u

j

"~

18

~

mm

~

1Sil 200 210 220 230 240 250 2Gl
~

Figure 3-4 Average soil moisture(%), by Julian Day, at Aleza Lake, Gregg Creek, and Red Rock.

80

Aleza Lake, Birch Tree

2400
2200

Maximum force

~

2000
1800

6

Q)

u
.....
0
l..L

0)

c:

"15
0
.....

0..

::)

1600
1400
1200
1000
800
600

Ratchet (up and down) of winch

400
200
0

Time

Figure 3-5 Sample of data recorded by the load cell and datalogger.

Table 3-3 Results from the ANCOVA
N: 578
R 2 : 0.546

Factor
Location
Plant Type
Diameter
Location • Plant Type
Location • Diameter
Number of Stems (Plant Type)
Vegetation Density (Location)
Error

Sum-of-Squares df F-ratio
2.602
2 10.800
9.835
1 81.645
47.325
1 392.866
0.615
2
2.552
0.970
2
4.025
4.517
3 12.499
0.142
4
0.296
67.700
5

p
<0.001
<0.001
<0.001
0.079
0.018
<0.001
0.881

81

Table 3-4 Adjusted least square mean resistance (log kN) for each plant type, at all locations.
I

Plant
Type

I Adjusted Least

Square Mean
Resistance (log
kN)
0.951
0.432

Birch
Pine

Standard
Error

Sample
Number

0.046
0.032

436
145

Table 3-5 Adjusted least square mean resistance (log kN) at each location, for both species.
Uprooting resistances followed by the same letters were not statistically different.

Location

Adjusted Least
Square Mean
Resistance (Log kN)

Aleza Lake
Red Rock
Gregg Creek

0.907 a
0.625 b
0.543 b

Standard
E"or
0.037
0.036
0.038

Table 3-6 Adjusted least square mean resistance (log kN) for each plant type and number of main
stems.

Plant
Type

Birch
Pine

Number
of Stems
1
2
3
4
1

Adjusted Least Square
Standard Sample
Mean Resistance (log
Number
E"or
kN)
0.717
0.020
347
73
0.887
0.043
0.117
1.335
9
7
0.866
0.133
145
0.032
0.432

82

Gregg Creek

AJeza Lake

~

-----.,
0"':-0 -----,..,_
0 ~

t

i

----,J'0

,"':,

~

------=o':, ------,-,:-. ------,-,..,.._
, ------='
,o0..« . bg b lflSfCI'med

r e

Red Rock

Figure 3-6 Scatterplot of resistance to vertical uprooting (log transformed) as related to tree ground
line diameter (log transformed) at each field location.

Table 3-7 Mean root biomass (log transformed) and mean resistance per unit area root biomass of
paper birch and lodgepole pine trees at aU sites.

Plant
Type
Birch

Pine

Mean Root
Biomass (log g)
4.717
5.003

Standard
E"or

Sample
Number

0.045
0.088

171
101

Mean Resistance,
logkN
0.714
0.576

Mean
Resistance per
unit Root
Biomass (log
kN/logg)
0.151
0.115

83

Table 3-8 Mean root biomass (log transformed) and mean resistance per unit root biomass of paper
birch and lodgepole pine at the three locations.

'

I

j

II

I

lncation

Mean Root
Biomass (log g)

Aleza Lake

RedRock
Gregg Creek

Standard
E"or

I

Mean
R
.
.
esistance per
Sample Mean Resistance,
. R
l
kN
unit
oot
Number
og
Biomass (log
kN/logg)
I

4.862 1
4.852

0.061
0.060

63 1
149

0.915
0.554

0. 188
0.114

4.709

0.114

60 1

0.559

0. 119

Gregg Creek

Aleza Lake

~ ':--::-':25---='
,.:---:,:-'.=-----'
· ·:---'
···
Dillnder, logtriWIStar..ed

Red Rock

~

I

I

I

~

':-

~
i

et r

----',.:---'••.
~

..,

___,...
,.:---:,-':. ~
••----'
••
i net

tr~

Figure 3-7 Root biomass obtained from vertical uprooting (log transformed) as a function of tree
ground line diameter (log transformed) at each location.

84

Table 3-9 Mean root biomass, log transformed, and mean resistance per unit root biomass of paper
birch and lodgepole pine at each field location.

I

Location

Aleza Lake
Red Rock
Gregg Creek

Plant
Type
Birch
Pine
Birch
Pine
Birch
Pine

I

Mean Root
Biomass (log g)
4.783
4.939
4.621
5.576
5.041
4.438

Standard
E"or
0.089
0.083
0.056
0.110
0.099
0.179

Mean
!Mean Resistance per
Sample
Resistance, log . unit Root Biomass
Number
I
(log kN/Iog g)
kN
31
32
113
36
27
33

0.946
0.812
0.514
0.687
0.692
0.241

0.198
0.164
0.111
0.123
0.137
0.054

85

Chapter 4
Vertical uprooting resistance of paper birch seed sources grown
under different nursery cultures, five years after planting
4.1 Introduction
Paper birch is a highly variable species with a wide geographic distribution in North America
(Farrar 1995). In BC, paper birch is commonly found in mixed stands, at low to mid elevation in
the wetbelts of the ICH, IDF, and SBS biogeoclimatic zones (Peterson et al. 1997). Since the
mid-90's interest has been growing in paper birch as a commercial species. In 1995, 29000 m3 of
birch was used commercially in BC, a 70% increase from 1990 (Peterson et al.1997). Birch also
plays a vital role in the health and function of mixedwood forests, such as providing overstorey
shade to young conifer seedlings, and reducing both spruce leader weevil (Pissodes strobi) and
the spread of Armillaria root rot (Peterson et al. 1997, Carlson et al. 2000).

Little is known about paper birch regeneration biology (Carlson et al. 2000) and the effects of
seed source and nursery culture on the growth and performance (root strength) of artificially
regenerated paper birch planted in the field. Stocktype affected the root strength and tree stability
of juvenile lodgepole pine (Krasowski et al. 1996). Nursery practices had an effect on the
growth of interior spruce even after 5 years (Hawkins and Carlson 2000i. Birch genecology
studies have shown differences in growth rate, biomass allocation, photosynthesis, water-use

5

Hawkins, C.D.B. and M. Carlson. 2000. Nursery origin affects fifth year height of seed orchard and
natural stand interior spruce seedlots. Canadian Tree Improvement Association Conference. Sault Ste.
Marie, Ont.

86

efficiency, and nitrogen-use efficiency in four birch populations (Wang et al. 1998a, Wang et al.
1998b).

4.1.1 Birch Genecology Studies
Carlson et al. (2000) tested 18 paper birch seed sources from 5 BC forest regions (Nelson,
Karnloops, Cariboo, Prince George, and Prince Rupert). All seed sources were planted on 6 trial
sites (4 forested and 2 agricultural fields). Results showed negligible height differences among
seed sources except on the northern sites, Aleza Lake and Tisdall Lake, where growing
conditions were severe. At these sites, both the Prince George and Cariboo seed sources were
taller than the southern and coastal seed sources. All seed source growing on the agricultural
field sites (Skimikin and Creston) were taller(> 120 em average height) than the forest field
trials(< 60 em average height) after 2 years of growth. Frost damage was less for northern seed
sources than southern/coastal seed sources. Overall, variation in height occurred at the stand
(population), rather than the regional level, while frost damage differences occurred at the
regional, not the stand level.

To study the growth rate and biomass allocation of paper birch in BC, Wang et al. (1998a) grew

4 paper birch populations, representing extremes of temperature, moisture, and photoperiod
gradients in BC, in a nursery greenhouse. Four treatments of varying water and nitrogen levels
were applied. All treatments and populations were significantly different in final heights. Trees
in the high water- high nitrogen treatment were the tallest (87.3 em) compared to trees in the
low water -low nitrogen treatment, which were the shortest (55 .2 em ). Trees from the Prince
George seed source, Eaglet Lake, were the tallest (75 .1 em), while trees from the Kamloops seed
source, Lee Creek, were the shortest (62.4 em); this difference was possibly due to the difference
87

in height growth period. In all treatments, Lee Creek had the least root biomass. Overall, water
and nitrogen availability affected root biomass. In high nitrogen treatments the Nelson seed
source, Porcupine, and the Eaglet Lake seed source had the most root biomass, while in low
nitrogen the Skeena seed source had the most root biomass. In low nitrogen conditions, root
weight ratios (root biomass per unit total biomass) were higher than in high nitrogen conditions,
indicating that the trees were allocating more resources to root growth. However, root biomass
was the greatest for all populations in high water- high nitrogen conditions.

In a companion study, Wang et al. (1998b) examined the net photosynthetic rate, stomatal
conductance, and water and nitrogen use efficiency of the same 4 seed sources to determine the
response of the trees to varying nutrient and water regimes. Results showed that the Eaglet Lake
and Porcupine seed sources were most likely drought tolerant while the Skeena and Lee Creek
seed sources were most likely drought avoiders. Under high water Skeena sources should have
the fastest growth rate, while under low water conditions Eaglet sources should have the fastest
growth rate. The Skeena source, however, showed unexpected behavior as it maximized growth
under both high and low water conditions; the authors believed that this was due to the
population rarely experiencing drought for long periods of time.

4.1.2 This Study

Previous studies in this thesis have demonstrated that paper birch is an ideal candidate for
maintaining or enhancing slope stability in the central interior of BC. When compared to young
lodgepole pine trees, paper birch had greater root reinforcement (Chapter 2 and 3).

88

The objectives of this study were to determine if the root reinforcement (as measured by vertical
tree uprooting tests) of 5-year-old paper birch varied at Red Rock Research Station in Prince
George, BC, depending on the seed source and the nursery culture in which the trees were
initially grown.

4.2 Methods
4.2.1 Experimental Methods
Four paper birch seed sources, as studied by Wang et al. (1998 a, b), representing extremes of
BC' s latitudinal, longitudinal and elevational gradients (Table 4-1) were sown at Red Rock
Research Station (Red Rock) (53° 45 ' N, 122° 41 ' W) in Prince George and the Kalamalka
Research Station (Kalamalka) (50° 18' N, 115° 15 ' W) in Vernon in February 1996. Seed was
sown in 4150, and 515A styroblocks (Beaver Plastics, Edmonton AB). Two pruning treatments
were carried out: no pruning, and one pruning when seedlings were greater than 25 em in height.
In June 1996, seedlings were randomly selected from both nurseries and planted at Red Rock in
rows (10 trees per row) with an in-row spacing of0.5 m, and a between-row spacing of 1.0 m.
Each treatment (seed source, stocktype, nursery, and pruning treatment) was replicated twice
across the trial. with 10 trees in each treatment cell.

In June-August 2000, trees were uprooted vertically at Red Rock using a tripod and manual
winch device (Figure 3-2). A Sensortronics S-beam loadcell with a 2000 lb (908 kg) capacity
(Intertechnology Inc., Don Mills Ont.) and a Campbell Scientific CR10X datalogger (Campbell
Scientific Inc, Edmonton AB) were used to measure the maximum force required to pull the tree
from the ground (see Appendix A). The maximum force, when multiplied by the force of gravity

89

resulted in a measure of the maximum resistance of the tree to uprooting, measured in Newtons,
N.

Each day all four seed sources grown at both nurseries (Kalamalka and Red Rock) were sampled.
Trees from one stocktype (415D or 515A) and pruning treatment (no prune or one prune) were
uprooted each day. As a result, a total of 30-40 trees were sampled per day. The tree to be
uprooted was cut about 15 em above the ground and the ground line diameter was measured
prior to uprooting. In addition, the number of main tree stems was noted. Three soil samples
were taken throughout each sampling day to measure the variation in soil moisture content.

A sample of roots from the uprooting tests was collected. Each sample was the root system
pulled out of the ground during the test rather than the total root system. Root systems were
washed and then cut and placed in paper bags. They were dried for 48 hours at 67°C. Total
weight of the dry roots was then determined (root biomass).

Height and diameter data were obtained from the Ministry of Forests, Prince George and Vernon,
for the trees in the nursery (1996), for the trees grown in a companion study at Skimikin Nursery
6

in Salmon Arm, BC, and for the trees in field trials around the province . Then, this data was
used to compare the pattern of results from the tree uprooting portion of this study.

6

C.D.B. Hawkins. FRBC- Slocan Endowed Chair ofMixedwood Ecology and Management. UNBC. Email:

hawkinsc@unbc.ca._M. Carlson. Research Scientist, Interior Tree Breeding. Forest Genetics Section. BC Ministry of
Forests. Vernon, BC. Email: Mike.Carlson@gems3 .gov.bc.ca.

90

4.2.2 Statistical Methods
Data were analyzed in SYSTAT (v.8.0, SPSS Ltd., 1998).

The maximum vertical uprooting force (N) was determined from the original data set. This force
represented the maximum resistance in the vertical direction of the tree to uprooting. The data
were analyzed using a general linear model (GLM) method of analysis of covariance
(ANCOVA). The proposed covariate for the analysis was tree ground line diameter. The
assumptions of ANCOVA (Appendix B) and the assumptions of linear analysis (Appendix C)
were tested, and, if necessary, the proposed ANCOVA model was revised.

The relationship between resistance force and tree diameter was exponential, rather than linear
(Figure 4-1 ). Both the variables resistance force and tree ground line diameter were
logarithmically transformed to account for this relationship (Wilkinson et al. 1996).

An incomplete factorial ANCOVA (4*2*2*2) was proposed as follows:

RESISTANCE=

SEE> SOURCE+SfOCKf\'JIE+NUIN:RY+ PRUNING1RFA1MENf +DIAMEim+SEE>

SOURCE *SfOCKf\'JIE+SDDSOURCE *NUIN:RY+SEE>SOURCE *PRUNING
1RFA1MENf+

E ~

••• eqtL 4-1

+SfOCKf\'JIE* PRUNING1RFA1MENf +

Nl119RY*PRI.JNING 1m:A1MENf

where:
RESISTANCE= tree resistance to vertical uprooting, log transformed
SEED SOURCE= Skeena, Lee Creek, Eaglet, or Porcupine seed sources
STOCKTYPE = 415D or 515 A stocktypes
NURSERY= Kalamalka or Red Rock
PRUNING TREATMENT= no pruning treatment, or one pruning treatment
DIAMETER= tree ground line diameter, log transformed

91

All factors were considered to be fixed, as all levels of interest were sampled. Pairwise
differences for significant treatment effects were determined using orthogonal contrasts.

The uprooting resistance was divided by the root biomass to determine the amount of resistance
per unit root biomass. This would be compared across seed sources only (if significant
differences existed), as it aided in discovering genetic and environmental instigators of
resistance. Mean height, and diameter data for trees at Red Rock in 1996 and 2000, and for trees
at Skimikin in 2000 would also be compared by seed source, if significant, in the ANCOVA.
However, mean root biomass was compared across all significant treatment levels, as root
biomass could be related to tree resistance.

4.3 Results
4.3.1 Final Model Selection
The final model chosen, based on the tests of ANCOV A assumptions was:

RESISTANCE=

SEED SOUR<E+Sf()(](IYft:+NIJRSERY+ PRUNII'<GTRFATMENf +lliAMEIER+SEE>
SOUR<E *SIOCKIYPE+SI1EDSOURCE *NURSERY+SEE>SOUR<E *PRUNING

... eqn. 4-2

TRFA1MENf + Sf()(]([YPE *NURSERY +SIOCKIYPE * PRUNII'<GTRFATMENf+

NURSERY *PRUNING TRFATMENf +NURSERY*DIAMEIER

where:
RESISTANCE= tree resistance to vertical uprooting, Jog transformed
SEED SOURCE= Skeena, Lee Creek, Eaglet, or Porcupine seed sources
STOCKTYPE = 415D or 515 A stocktypes
NURSERY= Kalamalka or Red Rock
PRUNING TREATMENT= no pruning treatment, or one pruning treatment

92

DIAMETER= tree ground line diameter, log transformed

4.3.2 Results from the Statistical Analyses
The results from the ANCOVA can be found in Table 4-2. Significant main effects in resistance
to uprooting were found for seed source (p = 0.011) and nursery (p = 0.003). Significant
interactions were found between stocktype *nursery (p = 0.009), and nursery* diameter (p =
0.001).

The order, in decreasing resistance to uprooting, of the seed sources was: Skeena, Porcupine,
Eaglet, Lee Creek (Table 4-3). Mean resistance per unit root biomass, in decreasing order was
Porcupine, Eaglet, Lee Creek, Skeena. Trees grown at Red Rock nursery had significantly more
resistance to uprooting and greater root biomass than trees grown at Kalamalka (Table 4-4 ).
Trees grown at Red Rock in 515A stocktypes had greater resistance, but less root biomass than
trees in 415D styroblocks while trees grown at Kalamalka in 515A stocktypes had less
resistance, and less root biomass than trees in 415D styroblocks (Table 4-5). At smaller
diameters, trees from Kalamalka had greater resistance to uprooting than trees from Red Rock,
but at larger diameters, trees from Red Rock had greater resistance (Figure 4-2).

The order of the seed sources in decreasing height was the same at both Red Rock and Skimikin
(Skeena, Lee Creek, Porcupine, Eaglet) although the trees at Skimikin were over 2 metres taller
than the trees at Red Rock (Table 4-6).

93

4.4 Discussion
4.4.1 Seed Sources

The ability of a population (seed source) to move across elevational, latitudinal/longitudinal, and
environmental gradients is dependent on the amount of phenotypic and genotypic plasticity; this
plasticity depends on the adaptive strategy of the population (Rehfeldt 1994 ). The physiological
"performance," as measured by physical characteristics such as height, diameter or root
reinforcement, has often been used to distinguish between populations, and to identify the
plasticity and adaptive strategy of the population (Carlson et al. 2000, Rehfeldt 2000). The four
seed sources vertically uprooted at Red Rock showed differences in resistance to uprooting.
These differences, when combined with height, ground line diameter, and root biomass data from
Red Rock, and with height and diameter data from field trials of the same seed sources
throughout the province, may help distinguish seed source differences and the effects of these
differences on slope stability in BC.

Trees from the Skeena seed source had the greatest resistance to uprooting, and the greatest
height, diameter and root biomass compared to the other seed sources. Wang et al. (1998a)
reported that in greenhouse trials Skeena trees were the tallest and had more root biomass than
the other three seed sources, and that these differences could be attributed to the longer growing
season (meaning the trees flush sooner, and drop their leaves later) of this seed source under the
test conditions. In Prince George, at the same latitude (54 °) as the Skeena Region, the light
requirements for flushing would be met as day lengths would be similar. However, heat sums to
flush would be met earlier in the spring for the Skeena source as it is from a milder climate. This
would result in Skeena flushing earlier in the spring and growing later into the fall than the local

94

Eaglet seed source at Red Rock. Each year, more root growth would be put on, providing the tree
was not killed by spring or fall frosts.

Height data from Skimikin and other companion trials of this seed source showed that trees from
the Skeena seed source maximized growth in a variety of environmental conditions, and across
both elevational and latitudinal/longitudinal gradients (Figure 4-3 and Table 4-6). These results
were confirmed by Wang et al. (1998b), who reported that trees from the Skeena source
performed well under both high and low water conditions. These results suggest that Skeena
trees exhibit a generalist adaptive strategy, and that this strategy would allow maximum root
reinforcement to become established in wide range of environments in BC. Therefore, the
Skeena seed source should be considered an ideal population for use in terrain stabilization
projects as it can be grown in a variety of environmental conditions (in a variety of soil types,
and under a variety of temperature and moisture regimes) and still provide superior root
reinforcement to local populations. For example, at Red Rock, the Skeena seed source had
greater root reinforcement than the local Eaglet seed source {Table 4-3), even though Prince
George winter temperatures are considerably cooler, on average, than the winters in the Skeena
area.

The other seed sources uprooted in this study were not as clearly defined in their adaptive
strategy. For example, trees from the Lee Creek seed source had the least amount of resistance to
uprooting, yet had the second highest height, diameter, and root biomass. Overall, resistance was
low due to low resistance per unit root biomass (root strength). Wang et al. ( 1998b) reported that
trees from Lee Creek had poor overall performance, which is inconsistent with the results from
this study, and the other field trials (Figure 4-3 ). It is important to keep in mind that performance
95

of seedlings under controlled environment conditions may not represent the growth of seedlings
in field conditions (Zobel 1995).

Root strength, as described in this study as the amount of resistance to uprooting per unit root
biomass, is a genetic trait. On a per unit root biomass basis, trees from the Skeena seed source
had the least resistance and trees from Porcupine had the most (Table 4-3). Although these
differences were not statistically tested, the standard error of the mean suggested that trees from
Skeena and trees from Porcupine had different resistance per unit root biomass. Hathaway and
Penny (1977) tested the root tensile strength of Populus and Salix clones, and found that there
was interclonal variation. Although trees from the Porcupine seed source had greater resistance
per unit root biomass, trees from Skeena had higher root biomass, and therefore greater overall
root reinforcement. It should be noted that the root biomass measured in this experiment was
only the amount of roots pulled up during the uprooting tests. Therefore, it may not be
representative of true root biomass, although the argument could be made that trees with less root
strength (such as Skeena trees) would have more roots pulled up than trees with stronger roots
(such as Porcupine trees).

Root reinforcement is not a function of root strength alone, but is, in part, a combination of root
strength and root biomass. Root biomass, although likely a genetic trait in part, can be affected
by the environment (Chapter 2 and 3). This study also has shown that tree height and diameter,
although excellent indicators of performance in general, are not adequate indicators of overall
root reinforcement. When choosing material for slope stabilisation, seed sources such as Skeena,
which have a large root biomass and can maximize growth across wide environmental gradients,
should be considered.

96

4.4.2 Nursery and Stocktype
The nursery where the trees were grown impacted tree resistance to uprooting, even after five
years growing in the field. In 2000, trees that had been grown at Red Rock had greater uprooting
resistance and greater root biomass than trees from Kalamalka. Initially, in 1996, when the trees
were removed from the nursery, Kalamalka trees had greater root biomass (Table 4-6). Although
Kalamalka stock was hardy stock leaving the nursery, its growth was soon overtaken by trees
from Red Rock. To date this phenomenon has not been satisfactorily explained (Hawkins and
Carlson, pers. comm., 2001\ Nursery origin also affected the relationship between resistance
and tree ground line diameter. At similar diameters, trees at Red Rock had significantly greater
resistance than did trees from Kalamalka.

Nursery impacted stocktype performance. Trees grown at both nurseries in 415D styroblocks had
similar resistance to uprooting, but those grown in 515A styroblocks had very different
resistance. An unknown effect on the 515A styroblock trees occurred at Kalamalka, causing
decreased growth. Overall, these results reconfirm the significant length of time nursery can
affect tree performance in the field, although the cause of the problem is unknown.

Apparently nursery practices and conditions are dissimilar enough to affect the root strength of
paper birch trees even after being planted in a field trial for 5 years. It is uncertain what specific
practices or conditions would cause such differences. Type of styroblock is not the only variable

7

C.D.B. Hawkins. FRBC- Slocan Endowed Chair ofMixedwood Ecology and Management. UNBC. Email :

hawkinsc@unbc.ca. M. Carlson. Research Scientist, Interior Tree Breeding. Forest Genetics Section. BC Ministry of
Forests. Vernon, BC. Email: Mike.Carlson@gems3 .gov.bc.ca.

97

that affects root growth and root strength of seedlings. Fertilizing and watering regimes may
have an effect, but until nursery practices are further documented, it will be unknown which
specific practice impacts tree performance after field planting.

Seed source, and nursery where seedlings were grown had the most impact on root strength of
young paper birch in the field. Root strength is an important consideration for terrain stability in
BC, but this study has other implications for forest management. Quick establishment of
artificially regenerated seedlings after planting requires the growth of new roots beyond the plug.
Populations such as Skeena will be able to maximize root growth each year, whereas
conservative populations, such as Porcupine, would take longer to become established. Root
strength is also a consideration in plantations where windthrow is a problem. Trees with a larger,
stronger root system will be more stable during wind events (Papesh et al. 1998, Smith 1986).
Regardless of application, seedling material should be grown to optimize root growth and root
strength.

98

4.5 Tables and Figures

Table 4-1 Summary data for the location of the paper birch seed sources (adapted from Wang et al.
1998a).

Seed Source

Skeen a

Lee Creek

Eaglet

Porcupine

Forest District

Kalum

Salmon
Arm

Prince
George

Arrow

Latitude

54° 30' N

50° 46' N

54° 06' N

49° 15' N

6.3

7.6

3.0

8.2

Longitude
Elevation (m)
Rain (mm)
Snow(mm)
Total precipitation (mm)

128° 34' w 118° 50' w 122° 21' w 117° 10' w
70
685
840
600
557.9
945.5
276.9
452.5
339.3
209.0
125.6
216.4
897.2
1154.5
402.5
668.9

Mean annual temperature (C)

6000 ,------,,------.----r-----,------.----,
5000 r-

z 4000 r-

.s 3ooo-

0
0 0

0

0

0

eD

u

"'

0

"iii

~ 2000
1000

Diameter (em)

Figure 4-1 Scatterplot of tree resistance to uprooting and tree ground line diameter.

99

Table 4-2 Results from the ANCOV A.
N: 131
R 2 : 0.594

df F-ratio
p
0.042
0.766
3
2.831
0.080
0.890
0.348
1
0.245
1
2.718
0.102
0.045
1
0.501
0.481
8.823
I
97.781 <0.001
0.497
3
1.836
0.145
0.013
3
0.047
0.986
0.346
3
1.279
0.285
0.780
1
8.648
0.004
0.038
0.420
0.518
1
0.048
0.536
1
0.466
10.015 Ill

II Sum-of-Squares

Factors

Seed Source
Stocktype
Nursery
Pruning Treatment
Diameter
Seed Source* Stocktype
Seed Source* Nursery
Seed Source * Pruning Treatment
Stocktype * Nursery
Stocktype * Pruning Treatment
Nursery * Pruning Treatment
Error

Table 4-3 Resistance, root biomass, and resistance per unit root biomass by seed source. Uprooting
resistances followed by the same letters were not statistically different.
Mean
Adjusted Least Square
Mean
Mean Root
Resistance
Standard Sample
Seed Source Mean Resistance, log
Resistance, log Biomass, log per unit Root
Number
E"or
kN
kN
g
Biomass, log
kN/Iogg
7.525 b
7.302 c
7.483 a,b
7.367 a,c

Skeen a
Lee Creek
Porcupine
Eaglet

0.052
0.051
0.055
0.058

34
33
34
30

7.613
7.358
7.309
7.374

4.934
4.682
4.309
4.534

1.553
1.597
1.748
1.643

Table 4-4 Resistance, and root biomass by nursery.

Nursery

Kalamalka
Red Rock

Adjusted Least
Square Mean
Resistance, log
kN
7.369
7.470

Standard
E"or

Sample
Number

Mean Root
Biomass, log g

0.037
0.037

65
66

4.579
4.637

100

Table 4-5 Resistance, and root biomass by nursery and stocktype. Uprooting resistances followed
by the same letters were not statistically different.

I

II

Stock type

4150
515A

Nursery

Adjusted Least Square
Mean Resistance, log
kN

Standard
E"or

Kalamalka
Red Rock
Kalamalka
Red Rock

7.455 b
7.411 a,b,c
7.283 c
7.528 fa

0.051
0.054
0.055
0.051

!

J

Kalamalka Nursery

.

I

Sample
Number

Mean Root
Biomass, log g

34
31
31
35

4.606
4.693
4.517
4.590

Red Rock Nursery

9

0

...,

.,

"0

E
0

D

"ti
8
c:

E
0

~ 8
~

£:
""
..5!

0

..2

.;

.;
:ii 7
.lii

..

~ 7

(.)

.

.11i

a::

a::

I!

O.D

0.5

1.0

1.5

Diameter, log transformed

2.0

6

0.0

Diameter, log transformed

2.0

Figure 4-2 Comparison of resistance and diameter by nursery where the trees where initially
grown. Bars represent average height, with standard error bars.

101

Table 4-6 Comparison of height and diameter of the 4 seed sources: in the nursery (Red Rock and
Kalamalka) in 1996, at Red Rock in 2000, and at Skimikin in 2000.

Location

I Year

Seed Source

Skeena
Lee Creek
Red Rock
1996
Porcupine
Eaglet
Skeen a
I
Lee Creek
Kalamalka
1996
Porcupine
Eaglet
Skeen a
Lee Creek
Red Rock
2000
Porcupine
Eaglet
Skeena
Lee Creek
Skimikin
2000
Porcupine
Eaglet

Root Collar
Height (em)
Diameter (em)
0.419
44.600
0.385
39.000
0.403
37.500
0.403
36.900
0.445
38.300
0.412
36.800
0.438
35.200
0.426
33 .800
3.821
228.529
3.565
202.303
3.097
183.588
3.360
174.200
5.213
451 .250
5.748
432 .143
5.004
396.600
4.609
341.957

102

400

- 350
E

I

~~

t-

T

I

I

I

-

u

---- 300 f-

0)
0)
0)

...-c

......

..c

0)

'05

..c

Q)

Q)
.._

......

Q)
0)

ro
.._
Q)

>

<(

250 f200 f150 f-

B
v

-

.!:

-

~
~
v~

·::

-

":!

:::

100 f-

:::

~

50 f0

::!

~ ~

~

~

~

~
v~

#-0

~

~~

~~

~~~

.,

~

~~ ~
~

$0

-

Seed Source
Eaglet Lake
Lee Creek
8 Porcupine Creek
rn. Skeena River
~

D

~~

Location of field trials in BC

Figure 4-3 Comparison of average height in 1999 (5 growing seasons) of the seed sources at 5 field
trial sites in BC.

103

Chapter 5
Discussion, recommendations, and conclusions
5.1 Discussion
5.1.1 The Effects of Environment and Genetics on Root Reinforcement
In the first 15 years of growth, paper birch trees will provide more root reinforcement to unstable
slopes than lodgepole pine trees where shallow mass movement is the primary mechanism of
failure. The fast growth rate of a strong, dense, fine root system maximizes paper birch root
reinforcement early in the development of the tree compared to lodgepole pine.

As discussed in Chapter 1, researchers have documented the effect of morphological
characteristics such as root density (Wu et al. 1979, Waldron et al.1983, Abe and Iwamoto 1986,
Abe and Ziemer 1991, Ekanayake et al. 1997, Zhou et al. 1998), root system width and depth
(Sidle 1991, Anderson et al. 1989, Papesch et al. 1997, Ray and Nicoll 1998, Peltola et al. 2000),
and root tensile strength (O'Loughlin 1974, Burroughs and Thomas 1977, Ziemer and Swanston,
Watson and O' Loughlin 1985, Nilaweera 1994, Watson et al. 1997, Wu and Watson 1998) on
the contribution of root reinforcement to the soil. This thesis explicitly measured root density
(root biomass in Chapters 2-4) and root depth (in Chapter 2), and implicitly measured root
strength (resistance per unit root biomass, in Chapters 3 and 4).

Root density, or root biomass, alone did not account for the inter-specific root reinforcement
differences found in Chapters 2 and 3. At one year of age, paper birch had more root biomass
and greater root reinforcement than lodgepole pine (Table 2-6, Table 2-9, and Figure 2-12). Once
the trees were older (between 6-15 years of age) paper birch had less root biomass than
104

lodgepole pine, but still had greater root reinforcement (Table 3-4, and Table 3-7). There was no
difference in rooting depth after one year of growth in the nursery between paper birch and
lodgepole pine; observations in the field indicated that paper birch and lodgepole pine also had
similar rooting depth. Root strength (resistance to uprooting per unit root biomass) appeared to
be the morphological characteristic that caused the variation in root strength between the two tree
species. Paper birch trees generally had higher root strength (Table 3-9), and hence higher root
reinforcement, in all soil types than did lodgepole pine.

In addition to root strength, however, is the importance of root system structure, a morphological
characteristic not measured in the thesis experiments. Researchers have shown that small fine
roots have, per unit area, greater tensile strength than larger roots (Hathaway and Penny 1975,
Burroughs and Thomas 1977, Ziemer and Swanston 1977, Watson and O' Loughlin 1985,
Watson et al. 1997, Wu and Watson 1998). Species, such as lodgepole pine, which develop a tap
root and few fine roots (Koch 1996), would, at a young age, provide less root reinforcement than
species, such as paper birch, which develop a shallow root system dominated by a high density
of fine roots (Safford et al. 1990). In New Zealand, Ekanayake et al. (1997) found that at 8 years
of age the broadleaf species kanuka provided more stability to slopes than the coniferous species
Pinus radiata because of the root biomass of this species and its ability to grow in dense (in

terms of stems per hectare) stands. At 16 years of age, however, P. radiala had developed its
taproot system and now provided more stability than the kanuka stands, which had begun to selfthin.

Based on these results, inter-specific studies of root reinforcement must include measurements of
root strength. The root strength measurements (resistance per unit area root biomass) and the tree
105

uprooting techniques discussed in this thesis adequately accounted for root reinforcement
variability between paper birch and lodgepole pine, and could be used again for future research.
Future studies may also incorporate a measure of root system structure (by mapping primary and
secondary roots or by weighing roots by size class), and root surface area to determine the effect
of these characteristics on the root reinforcement of paper birch and lodgepole pine.

In contrast to the interspecific differences found in Chapters 2 and 3, root strength did not
account for the variability in root reinforcement among paper birch populations (Chapter 4).
Root reinforcement variation was better described by differences in root biomass. For example,
trees from the Skeena seed source had the least root strength (Table 4-3), but had the most root
biomass and root reinforcement compared to the other three seed sources. These results should
be treated with some caution, as the root biomass measured in this study was the biomass of the
roots uprooted, not total root biomass. However, population performance, in terms of root
reinforcement, cannot be determined by root strength alone. Vertical uprooting tests are a simple
method of determining root reinforcement differences, and, in combination with root biomass
measurements, can identify candidate populations for long-term terrain stabilization trials.

Soil physical characteristics, such as shear strength and bulk density, affect root system
morphology (Foil and Ralston 1967, Waldron 1977, Gent et al. 1983, Rab 1994, Bulmer 1998,
Day et al. 1999, Thomas 2000), and therefore increase or decrease the reinforcement provided by
a tree. At one year of age, paper birch and lodgepole pine provided the most root reinforcement
in sand soil and the least root reinforcement in silt soil. Older trees (6-15 years of age) at smaller
diameters, had more root reinforcement at Aleza Lake in clay soil than the other sites, but at
larger diameters had more reinforcement in sand- sandy loam soil at Red Rock and Gregg Creek.
106

Again, the variation in the root reinforcement in different soil types is not explained by root
biomass alone. In general, root biomass in Chapter 2 (Figure 2-12) and in Chapter 3 (Figure 3-7)
was the same for each species in each soil type. The differences at the field sites could therefore
be a result of environmental conditions (discussed below) or genetic variation in paper birch and
lodgepole pine among the field sites. This latter explanation, although possible, was ruled out
since similar variation between soil types was found in the Polytube Experiment (with known
populations).

Soil texture, porosity and shear strength may have affected the root architecture (branching) (Wu
et al. 1988, Zhou et al. 1998) of the paper birch and lodgepole pine, and thus could have affected
root reinforcement. Root branching may be affected by soil bulk density: the lower the bulk
density the greater the ability of the roots to penetrate the soil. Furthermore, straighter roots have
less pull-out resistance than roots with more branches (Zhou et al. 1998), especially when the
branches are not oriented in tension in the failure zone (Wu and Watson 1998).

Root architecture differences also account for the variation in root reinforcement with diameter
at Aleza Lake. Early on in their life cycle trees growing in clay soil at Aleza Lake may have
developed a highly branched root system, because of high soil shear strength (Table 2-13 ), and
high year round soil moisture (Figure 3-4), both of which limits root penetration into the soil
(Anderson et al. 1989, Bulmer 1998, Ray and Nicoll 1998). At this stage, root reinforcement of
the trees would be higher than trees grown in well-drained soil with low shear strength (Red
Rock and Gregg Creek). However, as the trees in the sandy or sandy loam soil grow older their
roots will penetrate deeper into the ground than the trees at Aleza Lake, and eventually will have
107

higher root reinforcement. Again, this is similar to kanuka and P. radiata in New Zealand
(Ekanayake et al. 1997) where P. radiata eventually provided more root reinforcement to a slope
than kanuka when it developed a deeper rooting taproot.

5.1.2 Summary of Key Findings
The key findings of this thesis were:

•!• Paper birch, at less than 15 years of age and regardless of soil type or sampling method
(nursery vs. field tests), had greater root reinforcement than did lodgepole pine.

•!• Paper birch trees had greater root strength than lodgepole pine trees.
•!• Root reinforcement of paper birch and lodgepole pine was greatest in coarse textured soil and
least in medium textured soil.

•!• The effect of soil type on root reinforcement was best determined by a combination of: soil
bulk density, shear strength, and moisture content.

•!• Paper birch root reinforcement varied genotypically. Trees from the Tabor Lake and Skeena
seed sources may exhibit a generalist adaptive strategy with regard to root reinforcement.

•!• Population differences in root reinforcement may have been caused by differences in root
biomass.

5.1.3 Experimental Design- A Review of Benefits, Liabilities, and Future Directions
5.1.3.1 Overall Results- First Stage of Paper Birch Root Reinforcement Trials
The nursery and field tests (including the genecology study) are only the first stage of testing
paper birch root reinforcement. These experiments, which were completed within a two year
period, have demonstrated that paper birch may be a good candidate for slope stabilization.
However, the studies were limited in scope and the actual performance of paper birch on
108

unstable terrain is yet unknown. Long-term field studies of paper birch root reinforcement on
slopes can test the findings of this thesis. The assumption of this thesis that paper birch can and
will be a commercial species, and therefore have an advantage over species such as willow
which are traditionally used for slope stabilization, will also be tested as the market for birch
timber and other products in BC matures.

5.1.3.2 Statistical Analysis
The most important issue of the statistical analysis was determining whether a complete (all
factors of interest and all their interactions) or incomplete (where certain interactions are
removed) model should be used. In any ANOVA/ANCOVA, three and four way interactions
may be meaningless as they are the result of random error (D. Ayers,pers. comm. 2001 8) . By
including these interactions, the implication is that they are not the result of random error, but
rather are systematic (Wilkinson et al. 1996). Whenever sample size and experimental design
permitted, a complete model was used. In all other cases, only two-way interactions were
included in the model; these models were reviewed and confirmed by a statistician9 .

5.1.3.3 Nursery Study
Although the results from these experiments were comparable to the results from the literature,
several refinements could be made to the shear device and the tube design to minimize error
associated with the shearing methods. These changes are summarized below:

1. Place the trolleys on a track to stop lateral movement.

109

2. Add a displacement meter (which attaches to the datalogger and measures the movement of
the tube being sheared) or an electric winch with a constant rate of movement to measure root
elasticity. The maximum force of unrooted soil is reached at smaller displacements than
rooted soil because roots stretch elastically before breaking (Ekanayake et al. 1997, Zhou et
al. 1998).
3. Use paper bags to line the tubes. These bags would stop the soil from coming out of the cracks
between the tube sections but, over time, would decay, leaving the root structure to maintain
rigidity.

Two constant forces were assumed for these experiments. The first was the friction force of the
trolley wheels on the plywood surface of the shear device. The second was the stretching and
breaking force of the plastic liners in the tubes. Systematic testing of the trolleys may prove
valuable in the future, especially if a track system is put in place to stop sideways movement.
The most practical solution regarding the plastic bags is simply to eliminate this force from the
tube design, as the stretching of the bag would be difficult to measure.

The Polytube Experiment was more successful, in design and data collection, as it built on the
mistakes and problems encountered in the Sonotube Experiment. The design of the tubes was
sturdier, and allowed for easier watering and shearing than the sonotubes. The experimental
design (randomized block) accounted for microclimatic differences, and, because the treatments
were randomized on the palettes, accounted for differences in growing space within each palette.

8

D. Ayers.pers. comm. 2001. Statistical Consultant. UNBC, Prince George, BC. Email: dieter@unbc.ca.

110

By using such methods as those used in the Polytube Experiment, root reinforcement can be
determined in a relatively short period of time under controlled experimental conditions. This
method is less difficult than field shear tests, which require soil blocks to be carefully excavated
and then a shear device assembled around the block. This method also allows for the control of
environmental variables such as water, nutrients, and temperature, which often confound the
results of field studies.

5.1.3.4 Field Tests- Limited to Site by Site Differences
The method of tree uprooting was very successful. The manual winch imposed minor limitations
on the experiment as trees with a ground line diameter of 6 em or more could not be pulled. In
addition, the use of a datalogger to record the force of uprooting trees posed some problems
when data was lost from several sites due to human error. In general, however, vertical tree
uprooting was a suitable method to compare root reinforcement between tree species and
between field sites.

Overall, the field tests showed that paper birch has greater root reinforcement than lodgepole
pine in a variety of soil types. Extrapolation beyond the sites, which were chosen to represent
one soil type, was not possible due to the sampling design. By sampling fewer trees on a larger
number of sites, the effect of soil type on root reinforcement may be determined. The results
from each site were likely confounded by differences in soil shear strength, a parameter that, in
future, should be measured. Vertical tree uprooting does not account for differences in soil
strength and therefore, the root reinforcement may be under or overestimated. Soil strength, bulk
density, porosity, and organic matter content limits shoot and root growth of vegetation (Bulmer
1998). Future studies of paper birch root reinforcement should examine the soil physical
Ill

processes outlined above, as well as ensure selection of similarly aged trees growing in similar
climatic conditions (biogeoclimatic zones and subzones ). Although field studies often encounter
wide variation inherent in the natural environmental processes, site selection and treatment
replication can account for some of this variation.

5.1.3.5 Birch Genecology- Seed Sources Effects and Confounding Treatments
The birch genecology showed that root reinforcement on a single site is affected by seed source.
These effects may have been confounded by other treatments variables (nursery where the trees
were grown, stocktype, pruning treatment), even though a large sample of trees was pulled.

The results from this study are limited to the site in which the trees were uprooted. Differences in
root reinforcement between seed sources may not be evident, or may not be similar at other field
sites. At Red Rock, the vertical uprooting tests measured both the effect of genetics and
environment on root reinforcement; at another site, where the environment is different, results
might be different. Further tree uprooting of these same seed sources at various locations
throughout the province can test the findings of this study and then make management
recommendations based on the results. Six field trials of these populations are already in place so
there may be an opportunity for further research.

5.2 Recommendations
5.2.1 Recommendations for Operational Use and Management of Paper Birch
Based on the results of the research reported here, it is reasonable to recommend:

112

•!• Operational planting of paper birch (in pure and mixed-conifer stands) on failing slopes, and

long-term monitoring of the slopes.
•!• Operational planting of paper birch seed sources, such as Skeena, at a variety of sites in BC.
•!• Retention of paper birch in harvested stands, particularly on unstable slopes.
•!• Use of silviculture techniques (such as shelterwood) to encourage paper birch natural

regeneration on unstable or potentially unstable slopes.
•!• Re-evaluation ofbrushing and weeding practices of young paper birch established by natural

regeneration on unstable or potentially unstable slopes.
•!• Re-evaluation of free growing standards on unstable or potentially unstable slopes.

5.2.2 Recommendations for Further Research
Based on the experience and results associated with the research reported here, it is reasonable to
recommend:

•!• More vertical uprooting and nursery shear tests to determine paper birch root reinforcement
in a variety of soil types and to determine the variation in root reinforcement among paper
birch populations.
•!• Long-term field trials of paper birch established growing on failing slopes.
•!• Study of paper birch silvics to determine the best methods of regeneration and establishment

on field sites.
•!• Continued research into the effects of nursery culture on young tree seedlings.

113

5.3 Conclusions
Paper birch is an ideal candidate as a plant material to enhance terrain stabilization in BC. Root
reinforcement of young paper birch consistently was greater than young lodgepole pine, in a
variety of soil types and using a variety of experimental approaches. Paper birch root systems
can substantially increase soil shear strength and slope stability within the first 0.5 m of soil. In
addition to enhanced slope stability and its related benefits, paper birch increases other forest
values such as biodiversity, soil nutrients, forest health, and, possibly, economic return.

The fast growth rate and the fine, dense root system of paper birch allows sufficient root
reinforcement to be quickly established on site. Preliminary seed source trials suggest that root
reinforcement can be maximized if specific populations with high root reinforcement are
identified. Planting and retaining paper birch on site, on slopes or on flat terrain, can meet forest
sustainability goals. Both the ecological and economic potential of paper birch is currently being
explored by a variety of research projects; this thesis project attempts to contribute to the
knowledge base, which will help to generate future management plans in BC.

114

Appendix A
Methods for Programming Datalogger and Loadcell

A. 1 Specifications
A.l.l Loadcell
Sensortronics Modei60001-2K 'S'-beam tension loadcell with a 2000 lb (908 kg) capacity
(Intertechnology Inc., Don Mills ONT). Calibration: May 30, 2000.
Contact: Alan Fenwick, Intertechnology, Don Mills, ONT
Ph: 1-800-416-445-5500, ext. 232

A.l.2 Datalogger
Campbell Scientific CR10X datalogger (Campbell Scientific Inc., Edmonton AB). Calibration:
March 15, 1999.

A.l.J Batteries
Two six volt lantern batteries joined in series (to provide 12 V to the datalogger).

A.2 Programming
The loadcell has four wires: red, black, white and green. These wires, along with the battery
wires, are attached as shown in Figure A-2. The red wires takes 5V direct current of power from
the batteries as an excitation voltage. The black wire is an analogue ground, and the white and
green wires are negative and positive output respectively.
115

The program used in this thesis has been provided as an example (Table A-1 ). The program was
initially taken from the CR 1OX Shortcuts Program (Instruction 2 - Differential Volts) and then
modified to meet the needs of the experiment. These modifications, as denoted by the Roman
Numerals in Table A-1, will be discussed below.

I.

This number is the number of program executions. In this case, the program is executed
every 0.01563 seconds.

II.

The maximum output volts from the loadcell. At 2000 lb (maximum capacity), the output
will be 17.73 mV, and therefore this option (23) is appropriate.

III.

This multiplier translates resistance (mV) into force (kglm/sec 2 or N), using information
from the calibration certificate provided with the loadcell, and simple conversions from
the imperial to the metric system. The first calculation required is to determine the output
(mV) per pound. At full capacity (2000 lb) the output would be 3.546 mVN (Loadcell
Calibration Certificate, May 30, 2000, Intertechnology Inc.). At 5 V excitation and
maximum capacity, therefore, the output would be 17.730 mV (3.546 mVN * 5 V),
which translates into 112.803 lb/mV (2000 lb I 17.730 m V). Since there are 0.454 kg in
1 lb, the conversion to metric results in 51.213 kglmV (112 lb/mV * 0.454 kg). Finally, to
convert this into force, it was multiplied by the force of gravity (9.815 m/sec 2 ), which
equals 502.652 N/m V.

IV.

If the output is greater than 196.200 N, then the loadcell begins recording. This
eliminates constant recording by the loadcell and datalogger when not in use. It also
saves battery time.

V.

Sets the storage area. Can also be pro!:,JTammed to have final storage in storage module.

116

Vl.

Sets the level of time that is recorded every time the program is executed. This is
important in some cases when the only point of reference is time throughout one data
collection day.

A.J Error of the Load cell
At full capacity, the error of the loadcell is < 0.03 %, and the error associated with a change in
temperature is < 0.0008% per °F.

A.4 Brief Overview of How the Load cell Works
Inside the loadcell are a series of strain gauges, which stretch (in the case of a tension loadcell)
when a load is applied to the loadcell. For the loadcell to work, a current must be provided by an
outside source (in this case, the datalogger batteries provide 5 V de). As the wires stretch the
resistance increases; therefore, the more load applied, the greater the m V output.

117

A.5 Tables and Figures
Table A - 1 LoadceU program for the C RIOX
0 .01563

Tablo! I Prq;uams
Sec= . Execwzon Interval

PIO

n

r

~

Loc:( BATI_VOLT(

1'02

Jftime IS

1440
30

nanureinterval
!hondo

P19

SJP1.anre

P9S

END

n-.nute\ 11toa

Loc: (:PROG_SIGJ

P2

23

VOl CD IFF)

REP

m

r

i n~

II

IN Chon

S02 .6S2

Loc:( :MC_j
Multipber

Otrsd

P89

If X <•> F
XLocMV_

196.2

F

10
P80

Sci hiiJh Flag 0 IOurpul)

Set Active Storace Area

Ill

Fmal StCI'tge Area I
Array 10 or Locabon

P77
1121

Realtime
Year, Day, Hour-Minuk, Seconds

P73

Ma>cinue
Rep
Value oriy

III

IV

v

V1

LocMV_

10
I

P77
1220

Real arne
Year, Day, Hour-Mmut.e

II

:P74

Minmize
Rep
Value only

12

:P70
I

Loc:BATI_VOLT

13

sunpie

Reps
Loc PROG_SIG_
End Table I

10

P96
71

Table 2 PnJI!Iams
Sc:c. Exccubon lnk:rV&I.

ScriiiOulp\u
SMI921SM 7 16/CSMI
EndTabk 2

Table 3 Pr0Rfm15
End Table 3
A

c

10

I 00
500
0

"""' Lo<at>ms
lraennechak LocarKN
Final Stora@:t Area 2

12

S=rity
Lock I
Loc:k2
Loc:k3

118

Table A- 2 Wiring diagram for the CRlOx datalogger
Red Wire
Excitation From Battery
-'ve
-t-'ve

~
~

~~

From Battery
+'ve

5CJt:.:'\J T tF='1 C: , fNC

...... ·'
·

•. :·i

:....:-: 1 / • .' H·\t ..

Green Wire \Vhitc Wire
Output

+'vc

Output

-'vc

Black Wire
Excitation
-'vc

119

Appendix B
Assumptions of Analysis of Covariance
B.l Methods to Test Assumptions
The following outlines the assumptions of analysis of covariance (ANCOV A) and the methods
used throughout this thesis to test the assumptions.

8.1.1 Significant Covariate
The first assumption of ANCOVA is the regression coetlicient for the covariate is significantly
different from zero. If this assumption is not met then the ANCOVA model overfits the data and
an analysis of variance (ANOV A) is more suitable (Wilkinson et al. 1996).

8.1.2 Normally Distributed Covariate
ANCOV A assumes the covariate used in the analysis follows a normal distribution (Wilkinson et
al. 1996). To visually assess normality, a histogram fitted with a normal curve can be used. In
addition, a Kolmogorov-Smimov (K-S) one sample goodness of fit test can be used to
statistically test the distribution ofthe data against a normal distribution (Zar 1984, Silk 1985). If
the data is distributed normally it should follow a Z distribution (Zar 1984).

8.1.3 Homogeneity of Slopes
To meet this assumption, the regression slopes ofthe dependent variable and the covariate for
each treatment variable should be homogeneous. A general linear model (GLM) method of
analysis of variance (ANOVA) can be used to test the significance of the interactions of the
treatment variables with the covariate. The ANCOVA model assumes there are no significant
120

interaction terms and that the regression slopes are parallel (Wilkinson et al. 1996). Violation of
this assumption may not be critical, especially if the significant interaction is retained in the final
model (Wilkinson et al. 1996, StatSoft Inc. 2000). If this is the case, then the analysis is a more
general form of ANCOVA (StatSoft Inc. 2000), or an interaction regression model (Wilkinson et
al. 1996).

8.1.4 Equal Covariate Means
ANCOVA assumes that the subjects of interest were randomly assigned to each treatment and
the covariate means for each treatment are equal (Wilkinson et al. 1996). Again, a GLM method
of ANOVA can be used to test this assumption. The covariate should be the dependent variable,
and all treatment variables, without interactions, should be the independent variables. According
to Wilkinson et al. (1996) this assumption is hoped to be true (i.e. no significance), but it is not a
strict assumption of ANCOVA if the researcher can justify why the means were unequal.

B.2 Results: Tube Experiment (Chapter 2)- Sonotube Experiment
B.2.1 Significant Covariate
For the top section of the tubes, the covariate (moisture content) regression coefficient was
significantly different from zero (p < 0.001) (Tables B-1). For the bottom sections, however, the
regression coefficient was not significant (p = 0.137) (Table B-2). Therefore, using a covariate
was not appropriate when analyzing the bottom sections of tube and the remaining ANCOVA
assumptions were not tested for these sections.

There was a problem with the soil moisture sampling technique, which may account for an
insignificant moisture content regression coefficient for the bottom tube sections. Average
121

moisture content was sampled for each tube (a soil sample was taken from the top and the
bottom sections and then pooled), rather than for the top and bottom sections separately. The
tubes had been watered from the top, and it was observed that the top sections were wetter than
the bottom sections. Therefore, the moisture content of the soil better represents the variation in
resistance in the top sections than in the bottom sections.

B.2.2 Normally Distributed Covariate
A histogram ofthe moisture content data is shown in Figure 8-1. Visually, the data appeared to
be normally distributed. The one-sample K-S test was run using a normal distribution with a
mean of 14.370, and a standard deviation of3.801 as determined from the data. The result was a
p-value of0.308, which indicated that the distribution of the data did not significantly differ from
the normal distribution.

B.2.3 Homogeneity of Slopes
The following model was used to test the homogeneity of the slopes:

IIDiiSfAN<:E = PI..ANflYPE + llJBESIZE+PI..ANflYPE *llJBESIZE+PI..ANflYPE (POPUlATION)+

... eqn. B-1

MOISIURE<UNIENT +PI.ANI'lYPE * MOISilJRE<UNIENT+ TIJBESI'ZE *MOISllJRE

<DNrnNf + PI..ANflYPE *llJBESIZE * MOISll.JRE<DNilNf +PI..ANflYPE

~

* MOISIURE<DNrnNT

where:
RESISTANCE= shear resistance (kPa)
PLANT TYPE= birch, pine, or no-plant
TUBE SIZE= large, medium, or small
MOISTURE CONTENT= percent moisture content
POPULATION

122

.

I =NO-PLANT

2 =pine
3 = birch, 700 m
4 = birch, 800 m

5 = birch, 900 m
6 = birch, 1000 m
7 = birch, 1100 m
8 = birch, 1200 m

There were no significant interactions of the covariate with the treatment variables for the top
sections oftube (Table B-3).

B.2.4 Equal Covariate Means
The model used to test for equal covariate means was:

MOISilJREa>NIENf = PlANflYPE+1lJBESIZE+PI.ANflYPE (POPUlATION)

••• eqn. B-2

where:
RESISTANCE = shear resistance (kPa)
PLANT TYPE= birch, pine, or no-plant
TUBE SIZE= large, medium, or small
MOISTURE CONTENT = percent moisture content
POPULATION
1 =no-plant

5 = birch, 900 m

2 =pine

6 = birch, 1000 m

3 = birch, 700 m

7 =birch, 1100 m

4 = birch, 800 m

8 = birch, 1200 m

The treatment variable planting type had significantly different moisture content means (p <
0.001) for the top sections of tube (Table B-4). This difference was the result of high moisture
content in the unplanted tubes. These tubes were saturated throughout the soil column because
they were watered at the same time as the planted tubes. The planted tubes had a high root
density constantly removing water from the soil and would dry out faster than the unplanted
tubes. It would be expected, under such watering regimes, that these tubes would be wetter.
123

B.J Results: Tube Experiment (Chapter 2)- Polytube Experiment
8.3.1 Significant Covariate
The regression coefficient for the covariate, percent moisture content, was not significant for
either the top (p = 0.325) or the bottom (p = 0.108) sections oftube (Tables B-5 and B-6). The
remaining assumptions were not tested, and for both sections a GLM method of ANOVA was
used.

B.4 Results: Field Tests
8.4.1 Normally Distributed Covariate
A one sample K-S test found that the covariate diameter (Jog transformed) with a mean of 1.283,
and standard deviation of0.285 foJJowed a normal distribution (p = 0. 429). A histogram, fitted
with a normal curve, of the covariate diameter visuaJJy confirmed this (Figure B-2).

8.4.2 Significant Covariate
The regression coefficient of the covariate, diameter, was significantly different from zero (p <
0.001) (Table B-7).

8.4.3 Homogeneity of Slopes
The model used to test for homogeneity of slopes was as follows :
IIDiiSTANCE = PI.ANflYPE +LOCATION +NUMBER OFSIEMS(PlANflYPE)+ DIAMEIER+PI.ANflYPE *

... eqn. B-3

LOCATION+ PI.ANflYPE* DIAMEIER+ LOCATION* DIAMEIER+PI.ANflYPE(NUMBER
OF SIEMS)*DIAMEIER + PI.ANflYPE *LOCATION* DIAMEIER

124

where:
RESISTANCE= pulling force, with a logarithmic transformation
PLANT TYPE= paper birch or lodgepole pine
LOCATION = Aleza Lake, Gregg Creek, Red Rock
NUMBER OF STEMS= number of birch main stems
DIAMETER = diameter, with a logarithmic root transformation

A significant interaction between location and diameter was found (p = 0.038) (Table B-8). This
interaction was therefore included in the final model.

8.4.4 Equal Covariate Means
The equal covariate means assumption was tested using the following model:

DIAMEIER =PI.ANfT\'P£+lOCATION + PI.ANfT\'P£ (NUMBEROFSllMS)

••. eqn. B-4

where:
DIAMETER = diameter, with a square root transformation
PLANT TYPE= paper birch or lodgepole pine
LOCATION= Aleza Lake, Gregg Creek, Red Rock
NUMBER OF STEMS= number of birch main stems
DIAMETER = diameter, with a logarithmic root transformation

Plant type had significantly different covariate means (p < 0.001) (Table B-9). A smaller sample
of lodgepole pine trees were pulled than paper birch. When sampling lodgepole pine trees,
similar diameter trees as the paper birch samples were selected, with the exception of samples
from Red Rock. These lodgepole pine trees were 15 years old, and had larger diameters than any
other trees in the sample. The lodgepole pine growing at Red Rock were likely the cause of the
unequal covariate means.
125

8.5 Results: Birch Genecology
B.S.l Significant Covariate
The regression coefficient for the covariate, tree ground line diameter, was significantly different
from zero (Table B-10).

B.4.2 Normally Distributed Covariate
The K-S test, with a mean of 1.212 and a standard deviation of0.250, showed that the covariate
was normally distributed (p = 0.485) (Figure B-3).

B.4.3 Homogeneity of Slopes
The assumption ofhomogeneity of slopes was tested using the following model:

126

RESISTANCE =

SEED SOURCE+SfOCKIYJIE+Nl.R'IERY + PRUNINGTRFA'IMFNf + DIAMEIER+

.•. eqn. B-5

SEEDSOURCE *SfOCKIYJIE+SEEDSOURCE • Nl.R'IERY +SEEDSOURCE* PRUNING
TRFA'IMFNf + SfOCKIYilE *Nl.R'IERY +SfOCKIYJIE • PRUNINGTRFA'IMFNf+
Nl.R'IERY • PRUNING TRFA'IMFNf +SEED SOURCE • DIAMEIER+SfOCKIYJIE •
DIAMEIER+ NURSERY *DIAMEIER+ PRUNINGTRFA'IMFNf *DIAMEIER +SEED
SOURCE *Sf()(](I'YPE *DIAMEIER+SEEDSOURCE *NURSERY *DIAMEIER+SEED

SOUR<E * PRIJNINGTRFAlMENf * DIAMEIER+ SfOCKIYilE *NURSERY *
DIAMEIER+SfOCKIYJIE * PRUNINGTRFA'IMFNf *DIAMEIER +NURSERY*

where:
RESISTANCE= tree resistance to vertical uprooting, log transformed
SEED SOURCE = Skeena, Lee Creek, Eaglet, or Porcupine seed sources
STOCKTYPE = 415D or 515 A stocktypes
NURSERY= Kalamalka or Red Rock
PRUNING TREATMENT = no pruning treatment, or one pruning treatment
DIAMETER= tree ground line diameter, log transformed

Significant interactions were found between nursery and diameter (p = 0.006) (Table B-11); this
interaction was retained in the final model.

B.4.4 Equal Covariate Means

The assumption of equal covariate means was tested using the following model:

DIAMEIER =

SEED SOURCE +SfOCKIYJIE+ NURSERY+ PRUNINGTRFA'IMFNf

••• eqn. B-6

where:
127

DIAMETER= tree ground line diameter, log transformed
SEED SOURCE= Skeena, Lee Creek, Eaglet, or Porcupine seed sources
STOCKTYPE = 4150 or 515 A stocktypes
NURSERY = Kalamalka or Red Rock
PRUNING TREATMENT= no pruning treatment, or one pruning treatment

Seed source had significantly different (p < 0.001) covariate means (Table B-12). This was
interesting, and unexpected. However, such differences may be the result of seed source genetic
differences.

128

8.6 Tables and Figures
Table B-1 Sonotube Experiment. ANCOVA results for top tube sections.
N:115
R 2 : 0.381

p
Sum-of-Squares I df F-ratio
16.403
2
0.344 0.710
196.839
2
4.132 0.019
n~
~ ~
I
-- !-- - I
495.246
Moisture Content
1 20.792 0.000
Plant Type*Tube Size
139.067
1.460 0.220
4'
116.628
0.979 0.434
Population (Plant Type)
5
Error
2381.948 100
Factor
Tube Size

Table 8-2 Sonotube Experiment. ANCOVA results for the bottom tube sections.
N: 115
2

R : 0.158
Factor
Tube Size
Plant Type
Moisture Content
Plant Type*Tube Size
Population(Piant Type)
Error

df F-ratio
Sum-of-Squares
23.329
2
0.598
22.731
0.582
2
43.921
I
2.250
116.076
1.487
4
78.074
5
0.800
1951.737 100

p
0.552
0.560
0.137
0.212
0.552

129

40

I

I

- 0.3
30 I-

,----

"0
...,
0

c::J
0

{)

10-

0
0

~

1-

- 0.2 g_

/

/ ~

,----

20 I-

"0

10

()"

:::J
"0
(I)
...,

\_

- 0.1

CIJ
D.>
...,

-\
20

~

Moisture Content (%)

0.0
30

Figure B-1 Sonotube Experiment. Histogram, fitted with a normal curve, ofmoisture content
(covariate).

Table B-3 Sonotube Experiment. Test for homogeneity of slopes.

N:ll5
2

R : 0.444

Factor

Tube Size
Plant Type
Moisture Content
Plant Type* Tube Size
Tube Size"' Moisture Content
Plant Type* Moisture Content
Plant Type*Tube Size* Moisture Content
Population (Plant Type)
Population (Plant Type)*Moisture Content
Error

Sum-of-Squares df F-ratio
p
42.586 2
0.865 0.424
38.374 2
0.780 0.462
107.989 1
4.389 0.039
155.057 4
1.575 0. 188
33 .839 2
0.688 0.505
18.903 2
0.384 0.682
1 - - --115.319 4
1.172 0.329
I
I
77.161 5
0.627 0.679
60.324 5
0.490 0.783
2140.650 87
i

130

-

Table B-4 Sonotube Experiment. Test for equal covariate means.
N: 115
R 2 : 0.178

i Sum-of-Squares i df I F-ratio ;

Factor

Tube Size
Plant Type
Popul-;tlon (Plant
Error

I
I

p~
I
!

10.537 1 2 !
250 .691 ! 2 1
35 .593 1 5 1
1359.588 j 105 !

p

0.407 i 0.667
9.680 i<0.001
0.550 1 0.738

'
I

Table 8-5 Polytube Experiment. Proposed ANCOV A model for the top tube sections.
N: 45
R 2 : 0.665

Factor
Plant Type
Soil Type
Moisture Content
Plant Type* Soil Type
Error

Sum-of-Squares df F-ratio
p
515.376
2 10.651 <0.001
201.732
4.169
2
0.024
24.122
0.997
1
0.325
185.942
4
1.921
0.129
846.788 35

Table 8-6 Polytube Experiment. Proposed ANCOVA model for the bottom tube sections.
N: 45
2

R : 0.616
Factor
Plant Type
·
Soil Type
Moisture Content
Plant Type* Soil Type
Error

Sum-of-Squares
153.169
235 .362
43 .975
88.917
564.446

df

F-ratio
2
4.749
2
7.297
1
2.727
4
1.378
'
35
i

p

0.015
0.002
-0.108
0.261

131

80

I

70 r-

-0.12

60 1-

-0.10 -u

0

-o

50 1-

~0 40 ~

u

20-

0
0.0

g.

-0.06

i

-0.04

~

0

::J

30-

10

-0.08

~

m

11,:0.02

1 .0
1 .5
0 .5
Diameter (log Transformed)

0.00
2.0

Figure 8-2 Field Study. Histogram, fitted with a normal curve, of the proposed covariate diameter
(log transformed).

Table 8-7 Field Study. Proposed ANCOVA model.
N: 578
2

R : 0.539

Factor

Location
Plant Type
Diameter
Location* Plant Type
Number of Stems (Plant Type)
Vegetation Density (Location)
Error

Sum-of-Squares df F-ratio
8.377
2 34.400
10.816
1 88.832
47.770
1 392.440
1.248
2 1 5.124
4.596
3 12.584
0.148 1 4 1 0.303
68.670 1564

p

<0.001
<0.001
<0.001
0.006
<0.001
0.876

132

Table B-8 Field Study. Test for homogeneity of slopes.
N: 578
R 2 : 0.556

Factor

~
Location
Plant Type
Diameter
Location* Plant Type
Number of Stems (Plant Type)
Vegetation Density (Location)
Location * Diameter
Plant Type * Diameter
Location * Plant Type * Diameter
Number of Stems (Plant Type) * Diameter
Vegetation Density (Location)* Diameter
Error

-

l Sum-of-Squares

~

i
!
I
I

1.603

1

J

df i F-ratio
p
2 ! 6.687 1-0.001

0.543
0.462
0.065
1
9.169 \ 1 76.505 <0.001
0.333 1 2
1.389
0.250
0.731 i 3 1 2.033 \ 0.108
0.340
4
0.710
0.586
0.788
2
3.287
0.038
0.070
1
0.581
0.446
0.245 , 2
1.022
0.361
0.613
3
1.705
0.165
0.347
4
0.725
0.575
66.159 552

Table 8-9 Field Study. Test for equal covariate means.
N: 578
R 2 : 0.106

Factor

Location
Plant Type
Number of Stems (Plant Type)
Vegetation Density (Location)
Error

Sum-of-Squares df F-ratio
p
0.184
2
1.254 1 0.286
11 22.229 <0.001
1.634
0.199
3
0.901
0.441
1.772
0.133
0.521 1 4
I
41.676 567 1

133

Table B-10 Genecology Study. Results from the proposed ANCOVA.
N: 131
R2 : 0.594

Factors

I Sum-of-Squares ! df ! F-ratio i

p
0.766 ! ?t-----2.831
0.042
0.080
1·
0.890
0.348
0.245
2.7I8
0.102
1!
0.045
0.501
0.48I
1i
8.823
97.78I <0.001
II
3
1
0.145
0.497
1.836
0.013
0.047
0.986
31
31
0.346
0.285
1.279
0.780
I
8.648
0.004
0.038
1
0.420
0.518
0.048
1
0.536
0.466
10.015 Ill

'

Seed Source
§_!ocktype
Nursery
Pruning Treatment
Diameter
Seed Source * Stocktype
Seed Source* Nursery
Seed Source * Pruning Treatment
Stocktype *Nursery
Stocktype * Pruning Treatment
Nursery * Pruning Treatment
Error

I
I

40

~

1\

c

520

u

~~

0.0

0.5

1.0

0.2

"U

.g
0

d:
0

:::l
"0

!!l

0 .1 ..,
~

1.5

Diameter, log transformed

Figure B-3 Genecology Study. Histogram, fitted with a normal curve, of the covariate, diameter.

134

Table B-11 Genecology Study. Results from the tests for homogeneity of slopes.
N: 131
R 2 : 0.697

Factors

Seed Source
t~

t pe

Nursery
- -·
Pruning Treatment
Diameter
Seed Source * Stocktype
Seed Source* Nursery
Seed Source * Pruning Treatment
Stocktype *Nursery
Stocktype * Pruning Treatment
Nursery* Pruning Treatment
Seed Source * Diameter
Stocktype * Diameter
Nursery * Diameter
1--Pruning Treatment * Diameter
Seed Source * Stocktype * Diameter
Seed Source * Nursery * Diameter
1---- - -

Seed Source * Pruning Treatment * Diameter
Stocktype *Nursery* Diameter
Stocktype * Pruning Treatment * Diameter
Nursery* Pruning Treatment* Diameter
Error

i Sum-of-Squares i df I F-ratio i p
3 1 0.626 1 0.600
o. I5I I
i

0.015 [
0.532
3.464
0.121
0.540 !
0.438
O.OI5 1
0.072
0.005
0.137
0.018
0.629
0.048
0.131
0.47

0.186 0.668
I I 6.6IO O.OI2
I
0.330 0.567
43
.033 <0.001
Ii
3
0.50I 0.682
3 1 2.235 ! 0.089
3
1.812 0.150
1
0.189 0.665
I
0.892 0.347
1
0.067 0.797
3
0.566 0.639
1
0.229 0.633
1
7.819 0.006
1
0.598 0.441
-3
0.542 0.655
3
1.947 0.127

0.363 1
0.055

3
1

1.504
0.687

0.219
0.409

0.113
0.021
7.487

I
1
93

1.402
0.259

0.239
0.6I2

0.02i

I

Table B-12 Genecology Study. Results from the test for equal covariate means.
N: 131
R 2 : 0.164
Sum-of-Squares df F-ratio
p
Factors
i
1.084
3
6.601 <0.001
Seed Source
0.041 1 I I 0.757
0.386
Stocktype
I I 1.957[ 0.164
0.107
Nursery
0.205
3.750
0.055
Pruning Treatment
I
I
6.788 124 1
Error
I

135

Appendix C
Assumptions of linear analysis
C.l Methods for Testing the Assumptions
C.l.l Normal Distribution
Both graphical and statistical methods were used to assess the residuals for normality. A
histogram of the residuals, and a normal probability plot visually determined if the residuals
followed a normal distribution (Zar 1984, Stevens 1996). A one sample Kolmogorov-Smirov (KS) goodness-of-fit test statistically tested the residuals against a normal distribution (Zar 1984).

Normally distributed residuals should have a mean of zero with 95% of the residuals lying within
two standard deviations ofthe mean (Stevens 1996). Maximum leverage values (from saved
residual output in SYSTAT) can be used to determine if outliers are a problem. According to
Huber (1981), a maximum leverage value<= 0.20 is safe, 0.20-0.50 is risky, and> 0.50 is
unsafe. If the maximum leverage value is large, the multiple- R 2 may not have as much
predictive power (Stevens 1996).

C.1.2 Homogeneous Variance and Independence of Residuals
Homogeneity of variance and independence of residuals were examined using a plot of residuals
versus estimate values (Stevens 1996). According to Stevens (1996), ifthe variance is
homogeneous and the residuals are independent, the plot should not have any patterns or clusters
discernible; the residuals should be randomly scattered about the line residuals= 0. If the
subjects were randomly sampled, the residuals should appear to be independent (Wilkinson et al.
1996).
136

The homogeneity of the variance across factor levels for ANCOVA (if used for the analysis) was
determined using scatterplot matrices. This method allows the homogeneity of variances to be
viewed for both the dependent variable and the covariate (Wilkinson et al. 1996).

C.2 Results: Tube Experiments (Chapter 2)- Sonotube Experiment
C.2.1 Normal Distribution
Visually, the residuals for both the top and bottom tube sections appeared to be normally
distributed (Figures C-1 - C-4). The mean and standard deviation of the residuals was 0, 4.57
(top sections) and 0, 4.18 (bottom sections). Therefore, 95% of the residuals should lie within±
9.14 (top) or 8.36 (bottom), which they appeared to do. Maximum leverage for the top sections
was 0.23, and for the bottom sections was 0.20, which indicated a slightly risky, but acceptable
level of leverage. The one sample K-S tests statistically showed that the residuals for top and
bottom sections follow a normal distribution (p = 0.293, and 0.940).

C.2.2 Homogeneous Variance and Independence of the Residuals
For both top and bottom tube sections, the residuals were well distributed around zero (Figures
C-5 and C-6), and there were no obvious patterns, indicating both homogeneity of variance and
independence. For the top sections (analyzed with an ANCOVA), the variance also appeared to
be homogeneous across factor levels (Figures C-7- C-9). The scatter ofthe points was
comparable, both within factors, and across factor levels. The normal curves were also similar
across factors, with the exception of the "fallow" (no-plant) type and population, which, due to
the small sample size, was somewhat less normal than the other groups.

137

C.J Results: Tube Experiment (Chapter 2)- Polytube Experiment
C.J.t Normal Distribution

The residuals appeared to be normally distributed. A histogram, fitted with a normal curve
(Figure C-10 and C-12) indicated some gaps in the residual data from the top tube section
ANOV A that may be of concern. The residual data from the bottom section ANOV A also may
be problematic as the distribution of the histogram was skewed (Figures C-11 and C-13). The
mean and standard deviation of the residuals for the top sections was 0.000 and 4.449 and for the
bottom sections was 0.000 and 3.719, respectively. There were several values outside the bounds
of2 standard deviations for both tube sections but the maximum leverage values were 0.200 and
0.200, which is within the safe range. The K-S tests confirmed that the residuals resulting from
the top (p = 0.154) and bottom (p = 0.412) statistical tests reasonably followed a normal
distribution.

C.3.2 Homogeneous Variance and Independence of the Residuals
A scatterplot of residuals versus fitted values for both the top and bottom sections were not as
randomly distributed about the line residual = 0 as the residuals from the Sonotube Experiments
(Figures C-14 and C-15). However, the sample size was very small for the Polytube Experiment,
and since there were no linear or grouping trends and the experimental design was completely
randomised then it can be assumed that the homogeneous and variance and independent residual
assumptions have been satisfied (Wilkinson et al. 1996).

138

C.4 Results: Field Study (Chapter 3)
C.4. 1 Normal Distribution
Visually, the residuals appeared to be normally distributed (Figures C-16 and C-17). A onesample K-S test showed that the residuals, with a mean ofO and a standard deviation of0.343,
followed a normal distribution (p = 0.465). Maximum leverage was 0.172, indicating that
outliers were not a problem.

C.4.2 Homogeneous Variance and Independence of the Residuals
The scatterplot of the residuals versus estimate (Figure C-18) showed some clustering. Because
there were no distinct patterns in the residuals, and it was known that the trees were randomly
sampled, the clustering was acceptable. The homogeneity of the variance was also checked
across factor levels (Figures C-19- C-22). There appears to be no patterns of concern.

C.5 Results: Birch Genecology (Chapter 4)
C.S.l Normal Distribution
A histogram, fitted with a normal curve, indicated that the residuals followed a normal
distribution (Figures C-23 and C-24). The mean and standard deviation of the residuals was
0.000 and 0.264; most of the residuals were within± 2 standard deviations, although there were a
few values less than --0.500. The maximum leverage value was 0.318, which was a slightly risky
level. However, a K-S test with a mean ofO.OOO and standard deviation of0.264 showed that the
residuals were normally distributed (p = 0.485).

139

C.5.2 Homogeneous Variance and Independence of the Residuals

A scatterplot of residuals versus estimate values had good random scatter (Figure C-25), which
suggested homogeneity of variance and independence of the residuals. Scatterplot matrices of
resistance versus diameter across treatment levels showed that the variance was homogeneous
across treatment levels as the normal curves for each level of the treatment were similar (Figures
C-26 - C-29).

140

C.6 Figures and Tables

35

0.3

30
"U

0

0.2 -g

c:::s 20
0

(.)

::l.

i5"
:::1

""0

15

~

m

!!l

10
5
0.0
20

10
0
RESDUAL

Figure C-1 Sonotube Experiment. Histogram fitted with a normal curve of the residual data
resulting from the ANCOVA for the top sections of the tube.

c

3

0

0

=s
.c 2

Q

-.::
0
i5
iii
E

0

z 0
~
~... -1

,>

~ -2
Q)

Cl.

~ -3

0
0

-10

0

RESDUAL

10

20

Figure C-2 Sonotube Experiment. Normal Probability plot of the residual data resulting from the
ANCOVA for the top sections of the tube.

141

30

0 .2

"U

0

-o
0

;::l.

cr

c

::J

~

-o

0

v

0 .1

10

-5

0
5
RESOOAL

~
OJ

!!l

10

Figure C-3 Sonotube Experiment. Histogram fitted with a normal curve of the residual data
resulting from the ANOVA for the bottom sections of the tube.

c

3

.Q

-s
,Q 2
i;

15

"ii
E

...
... 0
0

z

.£
G)
~

"ii

>
'C
G)

ti
4)

-1
-2

Q.
X

w -3

-10

9

-5

0
5
RESDUAL

10

15

Figure C-4 So no tube Experiment. Normal probability plot of the residual data resulting from the
ANOVA for the bottom sections of the tube.

142

20r-----r-----.-----.-----.
0
Q

10 1-

0

Figure C-5 Sonotube Experiment. Plot of residuals versus estimate values from the ANCOVA for
the top sections of tube.

~

~

~

~

~

~

~

~

~

-

10 ....
c
()

...J

<(

zs

-

iii

w
It:

I II>

a

~r

-

18

19

0

0

12

~~

13

~

14

~

15

~

16

ESTIMATE

~

17

Figure C-6 Sonotube Experiment. Plot of residuals versus estimate values from the ANOVA for the
bottom sections of tube.

143

w

0::
:::::>
f--

(1)

6
2

w
z
~
(/)
0

Tube Size

(/)

w

0::

MOISTURE RESISTANCE

Large
Medium
Small

Figure C-7 Sonotube Experiment. Scatterplot matrix of shear resistance (kPa) and soil moisture
content(%) by tube size.

w

0::
:::::>

~

6
2

w

(.)

z
~
(/)

Plant Type

(jj

w

0::

MOISTURE RESISTANCE

Birch
No-plant
Pine

Figure C-8 Sonotube Experiment. Scatterplot matrix of shear resistance (kPa) and soil moisture
content(%) by plant type.

144

w

0::

:;:)

1-

~

0

2

Population

--1
-- 2
- --- 3
--- 4
-

-5

.....

.. 8

....... 6
--7

MOISTURE RESISTANCE

Figure C-9 Sonotube Experiment. Scatterplot matrix of shear resistance (kPa) and soil moisture
content(%) by population, where popluation 1 is no-plant, population 2 is pine, and populations 38 are birch at elevations 700-1200.

c

:l
0

u

o LJ::::J:2t:::::J..__LLJ_t:::l:::,.c:LJo .o
-20

-10

0

RESDUAL

10

20

Figure C-10 Polytube Experiment. Histogram fitted with a normal curve of residuals from top
sections.

145

r

~

~

~0 10

u

5

c:..._L,._L,._L--L--L--L--L...-;:t=...""--L-----JO .0

0

10

20

RESDUAL

Figure C-11 Polytube Experiment. Histogram, fitted with a normal curve of residuals from bottom
tube sections.

c0

3

~ 2

ti

a

"ii
E

5
z 0

E
CD
::I

"ii

>
"C
CD

uCD

-1
a

-2

a.
X
w -3
-20

0
0

-10

0

10

20

RESDUAL

Figure C-12 Polytube Experiment. Probability plot fitted with a line of best fit for the top sections
of tube.

146

3

c
0

'S
2
Ll

0
D

~

0

iii
E

0

z
~

a!
::J

iii

>

-1

..

'0
a!

-2
0
a!

a.
X
w -3

-10

0

RESDUAL

10

20

Figure C-13 Polytube Experiment. Probability plot fitted with a line of best fit for the bottom
sections of tube.

20
0

10_J

<(

i5

1ii
w

D

00

0

' I •~
~

0
0

0:::

-10 1-

-20
10

0

8

0

20
30
ESTIMATE

0

-

-

40

Figure C-14 Polytube Experiment. Scatterplot of residuals against estimate values for the top
sections of tube.

147

20

0

10 -

a

....J

<(

::J
Cl

w

0::

00

0

1ii

Or-

-10

10

<g

i

J

8
0

15

-

20

oo

ca

a

"

ESTIMATE

Q

Q

I
I

0

25

30

Figure C-15 Polytube Experiment. Scatterplot of residuals against estimate values for the bottom
sections of tube.

Figure C-16 Field Study. Histogram, fitted with a normal curve of residuals from the ANCOVA
analysis in the Field Tests.

148

c

4

0

'§

.0

~

i5

m
E

5
z

E -1
Q)

:::s

m
>

u

Q)

ti
Q)

a.
X
w -4
-2

0

0
RESDUAL

-1

2

Figure C-17 Field Study. Normal probability plot of residuals from the ANCOVA analysis in the
Field Tests.

2
Cl

__J

<(

0

:::J
0

D

ii)

w

0:::

-1

I)

Ill
Cl

-2

-1

0

ESTIMATE

2

Figure C-18 Field Study. Residuals versus estimate values from ANCOVA.

149

0::

LU

1-

w

~
c:(

Ci
LU

u

z
~
(/)
C7.i

w

0::

~

.•

I

Plant Type

I

DIAMETER

RESISTANCE

--

BIRCH
PINE

Figure C-19 Field Study. Scatterplot matrix of diameter (log transformed) and resistance (log
transformed) by plant type.

0::

w
w

1----

2

<(

0

w

(._)

z
~
Ul

Location

(fj

- - Aleza Lake
Gregg Creek

w

0::

DIAMETER

RESISTANCE

----

Red Rock

Figure C-20 Field Study. Scatterplot matrix of diameter (log transformed) and resistance (log
transformed) by location.

150

0::

w
.....

:::2!:A
-w

<(

0

m ~r of

DIAMETER RESISTANCE

t~m

- - 1.000
- - 2 .000
---- 3 .000
- - - 4 .000

Figure C-21 Field Study. Scatterplot matrix of diameter (log transformed) and resistance (log
transformed) by number of stems.

~ ~t ti n

DIAMETER

RESISTANCE

~n it

None
Moderate
High

Figure C-22 Field Study. Scatterplot matrix of diameter (log transformed) and resistance (log
transformed) by vegetation density.

151

40

'§

30

0

u 20
10
L....l.....e:=I......I.....J.....L.....J.....J........L....L......J.....J.:::....._-.JO .O

-0 .5

0.0
RESDUAL

0.5

1 .0

Figure C-23 Genecology Study. Histogram fitted with a normal curve of the residuals resulting
from the ANCOVA.

c0

~

i;;

2

0

ii
E

5

z 0
Q)

~

CIS

>

-1

"0

~ -2

8.
X

w

D

0

D

~~

-1 .0

~

-0.5

~

0.0
RESDUAL

0.5

~

~

1.0

Figure C-24 Genecology Study. Probability plot fitted with a line of best fit of the residuals
resulting from the ANCOVA.

152

-

1 .0

0.5 ....
....J

<(

::J
0
(ii

0.0 1-

w

a::

'\,0

~

-0 .5 1-

Cb

6

0

7

Cl

I)

o•

i~

'6

..

~

0

a
-1 .0

<><1)

I) ~~
: "I) ~
I)

G

~

..

g

0

0

-

0

-

II

~
0

ESnMATE

8

9

Figure C-25 Genecology Study. Scatter plot of the residuals versus estimate values from the
ANCOVA.

w

(_)

z

Seed Source

~

Eaglet
Lee Creek

(I)

w
a::

Porcupine

DIAMETER

RESISTANCE

Skeen a

Figure C-26 Genecology Study. Scatterplot matrix of resistance to vertical uprooting (log
transformed) and tree ground line diameter (log transformed) across seed sources.

153

~ .#..
w

W
0::

•

• • -

I

DIAMETER RESISTANCE

Stocktype

- - 4150
- 515A

Figure C-27 Genecology Study. Scatterplot matrix of resistance to vertical uprooting (log
transformed) and tree ground tine diameter (log transformed) across stocktypes.

Nursery

DIAMETER RESISTANCE

- - Kalamalka
- Red Rock

Figure C-28 Genecology Study. Scatterplot matrix of resistance to vertical uprooting (log
transformed) and tree ground tine diameter (log transformed) across nurseries.

154

w
z

(.)

~
(i.i

,

w • ! ,_

-.

..

I

0::

DIAMETER RESISTANCE

Pruning Treatment
- - No pruning
One pruning
- -

Figure C-29 Genecology Study. Scatterplot matrix of resistance to vertical uprooting (log
transformed) and tree ground line diameter (log transformed) across pruning treatments.

155

Appendix D
Graphs of the data (top sections) for the Sonotube and Polytube
Experiments (Chapter 2).
D.l Sonotube Experiment
Birch, 700 m, large tube
~
~

150 r--- - -

~~

-

~

120

/

~ ~
40
30

~

10

I

v

~
\ 1\

v'

\

JV

~~~~

~

\1
~~

/'\_I

I v
I
I
I

~

\
\

,r
~

10

so

/ v

\

I
1\ I

~ 100

:
~

~

/\ I v

130

~
~
-" .--- -- - - - - - - - - - - -- - - - - -- - - - - -----j

~

\.

m~

~~

m

m~m

\
\
\

~m

m~m~
~~

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~

~~~~~~

t

t

t

~~

~~~

~ ~ ~ ~ ~ ~ ~

~~~~~~~~~~~~~~~~~~~~

~~

·c.Y. ·c9. ·...:! ·_..l. · .,., ·6' ·a ·<1' ·19_ ·c.Y. ·_..l. ·...:! ·6' ·.,., ~ ·a ·c.Y. ·c9. ·...:! ·_..l. · .,., ·6' ·a ~ ·d! ·c.Y. ·_..l. ·...:! ·6' {;. <1' {;.
~~

~~

~~

~~

~~

~

Time (hour minutes seconds)

156

Birch, 800 m, small tube
180
170
160
150
140
130
- 120
~ 110
~ 100
c

.!
.,

ii

~

90

80
70
60
50
40
30
20
10
0

,,

.... I

,-

-

/\.

I

AI

I

1
AI
/II
/
II
1\ I
"
1

V

I

~

r\

\1 ~

u

A..

"

d ' " A
~
v • v \

/V

-'

Birch, 900 m, medium tube
180
170

160
150
140
130
_120

.

~ 110

u
c

Ill
Ill

'iii

Ill

a::

100
90

80

70
60
50
40
30
20
10
0
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

~~~~~~~~~~ ~ ~ ~~~~~ ~~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~

~~~~~~~~~~~~~~~~~~~

~~~~~~~~~

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
~~~~~~~~~~~
~
~~~
~
~
Time (hour minutes seconds)

157

Birch, 1000 m, small tube
180
170
160
150
140
130
- 120
~ 110
~ 100
c

!

.1\

,. .r \ r.1\\

90

80
Ui 70
& 60
50
40
30
20
10
0

.fV'
AI \A

,.

J

1

\

",., \

\JV"""\.

\r

A

\
\

.......

t ~

~
~

~

'"'"

~~~~~~~~~~~~~~~~~~~~~~~~~~~~

~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~

~~~~~~~~~~~~~~~~~~~~~~~~~~~~

~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~ ~

Time (hour minutes seconds)

Birch, 1100 m, large tube
180
170
160
150
140
130
- 120
~ 110

I

r

~

100

!

11 I
80
I 1
70
... I V
60
I
I
50
I
40
.. I
30
/V
A
20
1- '
10 I - '

c

Ui

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158

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180
170
160
150
140
130
- 120
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3 100
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Pine, 735 m, small tube
180
170
160
150
140
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80
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159

Pine, 735 m, large tube
180
170
160
150
140
130
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c:

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180
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140
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110

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No-plant, fine textured soil
180
170

l

160
150
140
130
120

..

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Time (hours minutes seconds)

165

No-plant, coarse textured soil

180
170
160
150
140
130

120

..

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110
100
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Time (hours minutes seconds)

166

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