integrated wildlife intensive stry research · 2002-07-26 · report of the integrated wildlife...
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REPORT OF THE INTEGRATED WILDLIFE INTENSIVE FORESTRY
RESEARCH PLANNING WORKSMOP
INTEGRATED WILDLIFE INTENSIVE STRY
RESEARCH
REPORT OF THE INTEGRATED WILDLIFE INTENSIVE FORESTRY RESEARCH PLANNING WORKSHOP
Peter J. McNamee Michael L. Jones Robert R. Everi t t Michael J. Staley
David Tait
ESSA Environmental and Social Systyems Analysts Ltd.
Vancouver, B . C .
April 30, 1981
Province of British Columbia
This Publ icat ion i s IWIFR-4
. .
. .
M in is t ry o f Forests, Research Branch EP 915 Minis t ry o f Environment, F ish and W i l d l i f e B u l l e t i n B-19
The views expressed i n this report are those o f the authors and not necessarily those o f the sponsoring agencies.
Copies o f t h i s r e p o r t may be obtained, depending on supply from:
Research Branch Min is t ry o f Forests 1450 Government Street Victor ia, B.C. V8W 3E7
or
Fish and Wi ld l i fe Branch Min is t ry o f Environment Parliament Buildings Victor ia, B.C. V8V 2x5
i
EXECUTIVE SUMMARY
Concern for wi ld l i fe i n the management of second growth s tands on Vancouver Island has increased recently as more and more of the island comes under intensive s i l v i - c u l t u r a l management. The heightened awareness of the problems of integrated management of f o r e s t s and wi ld l i f e on Vancouver Is land prompted the Minis ter ies of Forests and Environment t o i n i t i a t e a 5 year project , cal led t h e Integrated Wildlife-Intensive Forestry Research (IWIFR) program. T o help plan the program, the Technical Working Group (TWG) of the IWIFR program sponsored a f ive day research planning workshop i n North Vancouver, B r i t i s h Columbia during January 19-23, 1981. The workshop was conducted u s i n g the methodology of Adaptive Environmental
' Assessment and Management and had the following objectives:
(a) develop a framework'for cooperation and communi- ca t ion between wi ld l i f e and f o r e s t r y i n t e r e s t s ;
(b) develop a conceptual framework, i n the g u i s e of a computer simulation model, t o u s e a s a g u i d e i n developing a research plan for IWIFR;
(c) develop a s e t of hypotheses about important processes i n the system under s t u d y ;
(d ) develop a framework for testing hypotheses, and provide a bas i s for eva lua t ing the re la t ive importance of different processes; and
(e) resolve the quest ion of the level of d e t a i l f o r research in the program.
ii
The focus of the workshop was t h e ' c o n s t r u c t i o n of a numerical s i m u l a t i o n model which i n t e g r a t e d t h e h y p o t h e s e s of p a r t i c i p a n t s abou t i m p o r t a n t p r o c e s s e s a n d d y n a m i c s of f o r e s t r y a n d w i l d l i f e c o n c e r n s . T h i s r e p o r t is a s y n t h e s i s of workshop proceedings and subsequent model s i m u l a t i o n s and a n a l y s i s a n d is t h e r e f o r e a g u i d e f o r d e v e l o p i n g a r e s e a r c h p l a n f o r IWIFR.
The b u i l d i n g a n d a n a l y s i s of t h e simulation model is used i n t h e r e p o r t t o d e v e l o p t h i s r e s e a r c h p l a n n i n g g u i d e . The model is described i n terms of i t s t e m p o r a l a n d s p a t i a l c h a r a c t e r i s t i c s a n d t h e i m p o r t a n t l i n k a g e s b e t w e e n e a c h of i t s component subsystems - v e g e t a t i o n , timber, deer, e l k a n d p r e d a t o r s . A d e t a i l e d d i s c u s s i o n of e a c h of t h e submodels i s t h e n g i v e n . P a r t i c u l a r a t t e n t i o n is p a i d t o t h e h y p o t h e s e s i m p l i c i t i n t h e f u n c t i o n a l r e l a t i o n s h i p s t h a t were d e v e l o p e d a t t h e w o r k s h o p . I n i t i a l s i m u l a t i o n resul ts from a number of s c e n a r i o s d e v e l o p e d b y t h e p a r t i c i p a n t s d u r i n g t h e w o r k s h o p a r e p r e s e n t e d .
The a c t u a l p r o c e s s of c o n s t r u c t i n g t h e s i m u l a t i o n model d u r i n g t h e workshop and examining i t s b e h a v i o r r e v e a l e d c o n c e p t u a l a n d i n f o r m a t i o n n e e d s w h i c h r e p r e s e n t def ic iencies i n u n d e r s t a n d i n g of t h e p r o c e s s e s a n d d y n a m i c s o f f o r e s t s a n d w i l d l i f e . I d e n t i f i c a t i o n of these needs is c r i t i c a l t o the deve lopmen t of a r e s e a r c h p l a n for IWIFR.
The r e s u l t s of r e s e a r c h u n d e r t a k e n t o meet these needs c a n be used a s r e f i n e m e n t s t o t h e e x i s t i n g submodels. T h e s e r e f i n e m e n t s require new c o n c e p t u a l i z a t i o n of p a r t s o f t h e e x i s t i n g model, a d d i t i o n of impor tan t components t h a t were l e f t o u t of t h e i n i t i a l model, or t h e a c q u i s i t i o n of be t te r data . However , i t is s t r o n g l y recommended t h a t a t h o r o u g h a n a l y s i s of t h e c o n c e p t s a n d d a t a used t o d e v e l o p t h e p r e s e n t model be conduc ted be fo re any model
.
iii
refinements are made. N o refinements which add t o model complexity should be made u n t i l the dynamics of the current version are well understood.
The conceptual deficiencies are restated as hypotheses about system processes and dynamics. Alternate hypotheses a re s ta ted and suggestions are given as to how t h e hypotheses may best be tes ted . Most of these a re in te rd isc ip l inary i n nature and span fo res t ry and wildlife concerns. There- fore research on any of the hypotheses w i l l benef i t enormously from an in t e rd i sc ip l ina ry approach. The c a r e f u l design of an experimental forest management plan to provide an arena for evaluating deer, elk and predator responses to a va r i e ty of management ac t ions is encouraged.
iv
ACKNOWLEDGEMENTS
We thank a l l the workshop par t ic ipants for the i r cooperation and productive contribution to the success . of t h i s e f f o r t , I n p a r t i c u l a r , Don Eastman and R i c k E l l i s of the Technical Working Group of the IWIFR Program ass i s t ed i n coordinating and organizing the workshop. Their effor ts are appreciated.
Many of the comments and c r i t i c i sms by pa r t i c ipan t s of the d raf t vers ion of the report proved valuable i n the ana lys i s of ideas presented i n p a r t s 8 and 9. We f e l t that these comments were important enough t o be included i n an appendix to the repor t .
We a l s o thank Monique Gutierrez for preparing the f igures and Joan Anderson for t y p i n g the report .
V
TABLE OF CONTENTS
EXECUTIVE SUMMARY
1 .0 INTRODUCTION ................................... 1 1.1 AEAM Methodology .......................... 2
2.0 BOUNDING THE IWIFR SIMULATION MODEL ............ 5 2.1 A c t i o n s ................................... 5 2.2 I n d i c a t o r s ................................ 6 2.3 Space ..................................... 6 2.4 Time ...................................... 8 2.5 S u b m o d e l D e f i n i t i o n ....................... 9 2.6 Looking Outward ........................... 10 2.7 S p a t i a l . S i t e a n d V e g e t a t i o n 1 0
C h a r a c t e r i z a t i o n ....................... 3.0 VEGETATION SUBMODEL ............................. 14
3.1 P e r e n n i a l s ................................ 14 3.2 Annuals ................................... 18 3.3 E f f e c t o f L i g h t L imi ta t ion on C a r r y i n g 18
3.4 A r b o r e a l L i c h e n s .......................... 18 3.5 F o r a g e A v a i l a b l e f o r B r o w s i n g ............. 21 3.6 E f f e c t s o f S i t e P r e p a r a t i o n ............... 21 3.7 F e r t i l i z a t i o n ............................. 21
C a p a c i t y ...............................
4.0 TIMBER SUBMODEL ................................ 23 4.1 I n f l u e n c e o f W i l d l i f e ..................... 25
4.1.1 B r o w s i n g E f f e c t s ................... 25 4.1.1.1 Stem Mortal i ty ............ 25 4.1.1.2 Changes i n Growth ......... 25
4.1.2 Direct I n f l u e n c e ................... 27 4.2 H e i g h t .................................... 27 4.3 Timber Volume ............................. 27 4.4 S t a n d D e n s i t y ............................. 27 4.5 Crown Closure ............................. 29 4.6 Live Crown Rat io .......................... 29 4.7 F o l i a g e Biomass A v a i l a b l e t o W i l d l i f e ..... 32
5.0 DEER SUBMODEL .................................. 33 5.1 S n o w f a l l .................................. 33
5.1.1 Snow Reaching the Canopy ........... 33 5.1.2 Snow Reaching the Ground ........... 34 5.1.3 Food Covered by Snow ............... 35
5.2 Movement .................................. 40
5.2.2 Escape Cover ....................... 43 5.2.3 Food ............................... 43
5.2.1 Winter Range ....................... 42
vi
TABLE OF CONTENTS ( c o n t I d )
Paqe
5 .3 Feed ing and Ene rgy I n t a k e .................. 47 5.4 S u r v i v a l ................................... 5 1 5 .5 Reproduct ion ............................... 53
6.0 ELK SUBMODEL .................................... 58 6 . 1 S e a s o n a l S i t e U t i l i z a t i o n .................. 58
6 . 1 . 1 S e a s o n a l D i g e s t i b l e E n e r g y .......... 59 6.1.2 Escape Cover ........................ 60 6 . 1 . 3 P h y s i c a l C o n s t r a i n t s ................ 63 6 . 1 . 4 C a l c u l a t i o n of S e a s o n a l S i t e
U t i l i z a t i o n ...................... 65
6 . 2 . 1 S e a s o n a l E n e r g y R e q u i r e m e n t s ........ 65 6 . 2 . 2 S u r v i v o r s h i p ........................ 66 6.2.3 Fecundity ........................... 70 6 .2 .4 Popu la t ion Change ................... 70
6 .2 Popula t ion Dynamics ........................ 65
7.0 PREDATION AND HUNTING ........................... 71. 7 . 1 D i s t r i b u t i o n o f P r e d a t i o n ..........,........ 7 1 7 .2 The Genera l Model .......................... 71 7 . 3 I n f l u e n c e o f Escape Cover .................. 7 3 7.4 Wolf P r e d a t i o n ............................. 73
7.4.1 Deer-Wolf Interact ions .............. 76 7 . 4 . 1 . 1 F u n c t i o n a l R e s p o n s e ........ 76 7.4 .1 .2 Numer ica l Response ......... 78
7.4.2 E l k - W o l f I n t e r a c t i o n s ............... 78 7.5 Bear P r e d a t i o n ............................. 8 1 7 . 6 C o u g a r P r e d a t i o n ........................... 8 1
7.6.2 Elk-Cougar I n t e r a c t i o n s ............. 8 1 7 .7 Hunt ing .................................... 83
7 . 6 . 1 D e e r - C o u g a r I n t e r a c t i o n s ............ 8 1
8 .0 RESULTS OF THE WORKSHOP ......................... 85 8 .1 The Concep tua l Mode l ....................... 85 8 . 2 C o n c e p t u a l a n d I n f o r m a t i o n Needs ........... 85
8.2.1 V e g e t a t i o n .......................... 87 8.2.1.1 Competition ................ 87 8.2.1.2 F o r a g e A v a i l a b i l i t y ........ 87 8.2.1.3 Effects of S i l v i c u l t u r a l
Pract ices ............... 88 8 . 2 . 1 . 4 A l t e r n a t e R e p r e s e n t a t i o n
of V e g e t a t i o n ........... 8 8
I
vii
TABLE OF CONTENTS (cont ' d )
Page
.
f
8.2.2
8.2.3
8.2.4
8.2.5
8.3 Model 8.3.1 8.3.2 8.3.3 8.3.4
8.4 Model 8.4.1 8.4.2
8.4.3
Timber ............................... 89 8.2.2.1 Effec ts of Animal Browsing .. 89 8.2.2.2 Direc t Ef fec ts of Wildl i fe .. 90 8.2.2.3 Effec ts of S i l v i c u l t u r a l
Prac t ices ................ 92 8.2.2.4 Foliage Production .......... 92 8.2.2.5 Influence of Other Vegetation
on Timber ................. 92 Deer ................................. 93 8.2.3.1 Snow ........................ 93 8.2.3.2 Movement .................... 94 8.2.3.3 Feeding ..................... 96 8.2.3.4 Survival and Reproduction ... 97
8.2.4.1 Escape Cover ................ 97 8.2.4.2 Food Ava i l ab i l i t y ........... 98 8.2.4.3 Surviv.orship and Fecundity .. 98 Predation and Hunt ing ................ 99 8.2.5.1 Seasonal Distribution of
Predation ................ 99 8.2.5.2 Functional Responses ........ 100 8.2.5.3 Numerical Responses ......... 100 8.2.5.4 Wolf Predation .............. 101 8.2.5.5 Bear Predation ............ ..lo3 8.2.5.6 Cougar Predation ............ 105 8.2.5.7 Predator-Predator Inter-
ac t ions .................. 105 8.2.5.8 Hunt ing ..................... 105 8.2.5.9 Escape Cover ................ 106 8.2.5.10 Predator Population Dynamics
Behaviou. ............................. 108 Baseline Scenario .................... 1 0 9 "Tree Farm" Scenario ................. 113 "Wildlife Farm" Scenario ............. 1 1 4 Predation Scenario ................... 116
Refinements ........................... 1 1 6 Vegetation ........................... 118 Timber ............................... 118 8.4.2.1 Effec t s of Browsing ......... 118 8.4.2.2 Direct Effects of Wildl i fe .. 1 1 9 Deer ................................. 1 1 9 8.4.3.1 Snow In te rcept ion ........... 1 1 9 8.4.3.2 Food Preferences ............ 120 8.4.3.3 exploitation........^.. ..... 120
E l k .................................. 97
8.2.4.4 Emigration .................. 99
viii
TABLE OF CONTENTS (cont I d)
Page
8.4.4 E l k ................................. 120 8.4.4.1 Escape Cover ............... 120 8.4.4.2 Food Preferences ........... 121 8.4.4.3 Emigration ................. 121
8.4.5 Predation and Hunting ............... 121 8.4.5.1 Seasonal Distribution of
Predation ............... 121 8.4.5.2 Functional and Numerical
Responses of Predators to Prey Density ......... 122
8.4.5.3 Wolf Predation ............. 122 8.4.5.4 Cougar Predation ........... 122 8.4.5.5 Escape Cover ............... 123
9.0 RESEARCH RECOMMENDATIONS ..,...................... 124 9.1 The Importance of Interdisciplinary
Hypotheses .............................. 124 9.2 Vegetation ................................. 125
9.2.1 Competition ......................... 125 9.2.2 Forage Availability ................. 125
9.3 Timber ..................................... 126 9.3.1 Browsing Effects .................... 126 9.3.2 Direct Effects of Wildlife .......... 126 9.3.3 Competition From Other Vegetation ... 127
9.4 Deer ....................................... 127 9.4.1 Snow ................................ 127 9.4.2 Movement ............................ 128 9.4.3 Feeding ............................. 129 9.4.4 Survival and Reproduction ........... 130
9.5 Elk ........................................ 131 9.5.1 Effects of Snow ..................... 131 9.5.2 Movement ............................ 132 9.5.3 Escape Cover ........................ 132 9.5.4 Forage .............................. 133 9.5.5 Emigration .......................... 134
9.6 Predation and Hunting ...................... 134 9.6.1 Functional Responses ................ 135 9.6.2 Numerical Responses ................. 136 9.6.3 Escape Cover ........................ 137
10.0 LITERATURE CITED ................................ 138
11.0 LIST OF PARTICIPANTS ............................ 140
APPENDIX ........................................ 143
ix
LIST OF FIGURES
Page
Genera l charac te r i s t ics of the hypothetical region . . . . . . . . . . . . . . . . O . . O O . . . ~ O . . ~ . . . ~ . . . . . O . O e . 1 2
2.1 ., ..
3.1
.: 4.1
4 . 2
4 . 3
4 . 4
4 . 5
4 . 6
5.1
5 . 2
5 . 3
5 . 4
5 . 5
5 . 6
5 . 7
5 . 8
5.9
Effec ts of overstory biomass on vegetation carrying capaci ty ................................ 20
Effec t of browsing on stand age.................. 26
Stand height as a function of stand age.......... 28
Stand volume................,..,.......,....,,... 28
Natural stem mortality ........................... 30
Effec t of stem removal on crown closure. . . . . . . . . . 30
Live crown ratio. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31
Relationship between crown closure and the depth of snow on a s i t e fo r va r ious l eve l s of snowfall. 37
The e f f e c t of snow depth on the proportion of t o t a l food actually not covered by snow.......... 38
Relationship between sn.owfa11 and the proportion of to ta l l i chens ava i lab le for feed ing . , . ........ 39
Components of the winter range value criterion... 4 4
Components of the escape cover value criterion. .. 4 5
The e f f e c t of t o t a l a v a i l a b l e food on a s i t e ’ s value as feeding habitat . . . . . . . . . . . . . . . . . . . . . . . . . 4 6
The multi-species disc equation .................. 50
The e f f e c t of the winter energy balance on winter survival......................^...^.,..^^. 5 6
The e f f e c t of winter and spring energy intake on n a t a l i t y ...................................... 5 7
X
L I S T OF FIGURES ( c o n t ' d )
6 . 1
6 . 2
6 .3
6 . 4
7 . 1
7.2
7.3
7.4
7.5
7 . 6
7.7
8.1
8.2
8 . 3
8 . 4
8.5
8.6
Paqe
E l k escape c o v e r as d e f i n e d by s t a n d h e i g h t a n d s t a n d d e n s i t y ............................... 64
E x t e n s i o n of u t i l i z a t i o n p o t e n t i a l from a c e l l w i t h complete c o v e r t o n e i g h b o u r i n g c e l l s w i t h no cover . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 64
E n e r g e t i c cost of moving i n snow f o r e l k . . . . . . . . 69
Ef fec t o f food a v a i l a b i l i t y on e l k s u r v i v a l . . . . . 6 9
V u l n e r a b i l i t y f a c t o r for deer based on escape cover . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75
F u n c t i o n a l r e s p o n s e s of wo lves t o f a w n d e n s i t y and a d u l t deer d e n s i t y .......................... 77
Numer ica l r e sponse of wolves t o deer d e n s i t y .... 79
F u n c t i o n a l r e s p o n s e o f w o l v e s t o e l k d e n s i t y .... 80
F u n c t i o n a l r e s p o n s e of bear t o f a w n d e n s i t y . . ... 8 2
F u n c t i o n a l r e s p o n s e of couga r t o deer d e n s i t y ... 82
H u n t e r h a r v e s t r a t e s as a f u n c t i o n o f deer d e n s i t y ......................................... 8 4
T h e c o n c e p t u a l model.. . . . . . . . . . . . . . . . . . . . . . . . . . 86
A l t e r n a t e h y p o t h e s e s a b o u t s t a n d m o r t a l i t y r e s p o n s e t o an ima l b rows ing ..................... 9 1
A l t e r n a t e h y p o t h e s e s about l o n g - t e r m e f f e c t s o f an ima l b rows ing ................................. 9 1
A l t e r n a t e h y p o t h e s e s about f u n c t i o n a l r e s p o n s e s of wolves t o deer. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 0 2
A l t e r n a t e h y p o t h e s e s about t h e n u m e r i c a l r e s p o n s e s of wolves t o deer. . . . . . . . . . . . . . . . . . . . . 104
Predator f u n c t i o n a l r e s p o n s e t o p r e y d e n s i t y a s e x p r e s s e d by t h e disc e q u a t i o n ............... 107
xi
LIST OF FIGURES (cont 'd )
Paae
8 . 7 Si te in i t ia l iza t ion for base l ine scenar ios ....... 1 1 0
8.8 Woo6 harvest trends under three scenarios ........ 111 8.9 Deer and elk population trends under three
scenarios ........................................ 1 1 2
8 . 1 0 Input conditions for "wildlife farm" scenario .... 115
8.11 Model behaviour for predation scenario ........... 117
xii
LIST O F TABLES
Page
2.1
2.2
2.3
3.1
3.2
3 . 3
3.4
3.5
4.1
5.1
5.2
5.3
5.4
5.5
5.6
6.1
6.2
L i s t of act ions developed a t the I W I F R workshop............ ........................... 6a
L i s t of indicators developed a t the I W I F R workshop..... . . . . . . . . . . . . . . . . .O. . . . . . . . . . . . . . . . 7
Looking outward matrix for the I W I F R model..... 11
Vegetation parameters for Coastal Douglas Fir wet subzone... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 5
Vegetation parameters for Coastal Western Hemlock dry s u b z o n e . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16
Vegetation parameters for Coastal Western Hemlock wet subzone... . . . . . . . . . . . . . . . . . . . . . . . . . 1 7
Parameters for arboreal lichen dynamics........ 19
Ef fec ts of s i t e p repa ra t ion on vegetation.. . . .. 22
Management act ions implemented i n the timber submodel.. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 24
Slopes of the snow depth-food coverage r e l a t ionsh ip ................................... 36
Weighting f ac to r s used for determining the re la t ive va lue of s i t e s a s deer habi ta t . . . . . . . . 41
Seasonal energy conversion factors from annual forage biomass.... ...................... 48
Parameters for the multi-species disc equation. 49
Parameters used i n surv iva l ra te ca lcu la t ions . . 52
Parameters used i n reproduction calculations. . . 55
Seasonal food preferences for elk. . . . . . . . . . . . . . 61
Temporal u t i l i za t ion ra tes for e lk . . . . . . . . . . . . . 62
xiii
6.3
6 . 4
6.5
6.6
7.1
7.2
7 . 3
LIST OF TABLES (cont'd)
Page
Potential survivorship rates far elk ........... 67
Average daily caloric requirements for elk ..... 67
Maximum average daily mortality rates due to starvation ................................... 68
Maximum average daily reduction in fecundity due to star vat ion.................^.^.....^..^^ 68
Seasonal distribution of predation ............. 72
Functional responses of predators .............. 74
Numerical responses of predators ............... 74
.
1 . 0 INTRODUCTION
Concern for wi ld l i fe i n the management of second-growth s t a n d s on Vancouver Island has increased recently as more and more of the island comes under i n t e n s i v e s i l v i c u l t u r a l management. The heightened awareness of the problems of integrated management of f o r e s t s and wi ld l i f e on Vancouver Island prompted the Minis t r ies of Forests and Environment t o i n i t i a t e a 5 year project , cal led the Integrated Wildl i fe- Intensive Forestry Research ( I W I F R ) program, for research on the e f f ec t s of s i l v i c u l t u r a l p r a c t i c e s i n second-growth stands on wildl i fe populat ions.
Pro jec ts of t h i s magnitude a re inevi tab ly . d i f f i c u l t t o des ign e f f ec t ive ly . The scope of the IWIFR p ro jec t '
touches on s i lvicul ture , forest ecology, wildl i fe biology, and socio-econoniic considerations and involves numerous agencies and individuals w i t h par t icu lar perspec t ives , expectat ions, and biases . Although in i t i a l ly t he r e sea rch questions a l l seem relevant and important to answer, i t is c r i t i c a l t h a t t h e key research quest ions are ident i f ied ea r ly i n the program. Carefu l s t ruc tur ing of the research p lan becomes a necessi ty when research is being done under limited bud-gets i n both money and time.
Simulation models are powerful tools for ident i fying c r i t i ca l r e sea rch ques t ions . The consequences of a large number of hypotheses and assumptions can be quickly examined and evaluated. The simulation modelling workshop, as part of the Adaptive Environmental Assessment Methodology ( A E A M ) ,
is a usefu l mechanism to cons t ruc t a simulation model of a resource system. I t a l lows research special is ts t o formalize and expl ic i t ly s ta te their understanding of the
- 2 -
system and i ts components, i den t i fy c r i t i ca l a s sumpt ions w i t h i n each d i sc ip l ine , ident i fy the in te rac t ions among subsystems, and identify important research questions w i t h i n and among d i sc ip l ines .
The Technical Working Group (TWG) of I W I F R sponsored a simulation modelling workshop i n North Vancouver on January 2 0 - 2 4 , 1981. The spec i f ic ob jec t ives of the workshop were to:
(a) ‘develop a framework for cooperation and communication between wi ld l i f e and f o r e s t r y i n t e r e s t s ;
( b ) develop a conceptual framework, i n the guise of a computer simulation model, to use as a guide in
developing a research p l a n for IWIFR;
(c) develop a s e t of hypotheses about important processes i n the system under s t u d y ;
( d ) develop a framework for tes t ing hypotheses , and provide a bas is for eva lua t ing the re la t ive importance of d i f fe ren t p rocesses ; and
(e) resolve the question of the level of d e t a i l f o r research i n the program.
I t was agreed a t the beginning of the workshop t h a t e lk , dee r , and their predators would be the only wildlife species considered i n the workshop.
1.1 AEAM Me thodology
Tradi t iona l ly , research programs concerned w i t h resource management issues have attempted to fund as many p ro jec t s a s possible which appear t o be important issues of concern. Li t t le thought is given to coordination of research between d i sc ip l ines or t o c r i t i c a l e v a l u a t i o n of pa r t i cu la r p ro j ec t s
- 3 -
i n the l i g h t of the dynamics of other par ts of the system. The , r e su l t is a s e r i e s of research experiments on very spec i f i c pa r t s of a problem which have l i t t l e or no relevance to other pieces of the system.
Over the l a s t decade a tool popularly known as " the modelling workshop'' has been developed by environmental s c i e n t i s t s and systems analysts at the University of Br i t i sh Columbia and the In t e rna t iona l In s t i t u t e fo r Applied Systems Analysis i n Austria. The methodology overcomes many of t r a d i t i o n a l p i t f a l l s of l a rge ' i n t e rd i sc ip l ina ry r e sea rch programs (Holling, 1 9 7 8 ) .
The focus of a simulation modelling workshop is t o cons t ruc t a quan t i t a t ive dynamic simulation model of the system under s t u d y . The development of the simulation model fo rces t he pa r t i c ipan t s t o view the i r a reas of i n t e r e s t i n the context of the whole system, thereby promoting interdisciplinary understanding of the system under s t u d y .
Simulation models require expl ic i t information. I n the workshop, spec ia l i s t s a r e fo rced t o be precise about their assumptions. This objectivity exposes conceptual uncertainties about system behaviour and ident i f ies research ques t ions tha t a re c r i t i ca l to inves t iga te before the system dynamics can be accurately predicted.
The workshop is usual ly 5 days i n length and proceeds roughly as follows. First, the problem and the system are clearly defined and bounded. T h i s is done by s t a t i n g the possible human intervent ions, or act ions, which can be performed on the system and the measures of system performance, or indicators, which pa r t i c ipan t s use t o evaluate the consequences of act ions. The model i t s e l f includes those processes which a re requi red to t rans la te
- 4 -
the act ions to the indicators . The system is then temporally and spa t ia l ly def ined . The number and s i z e of s p a t i a l u n i t s t o be modelled and the number and length of time s teps are def ined. The system is then divided into 3 - 6
subsystems: these represent the major discipl inary concerns represented a t the workshop. Each pas t i c ipan t is assigned t o a subgroup, each subgroup having the respons ib i l i ty of developing a submodel of a specific subsystem.
Second, the information transfers among subsystems are defined. Each subgroup m u s t e x p l i c i t l y s t a t e t h e i n f o r - mation it r equ i r e s t o make predictions about how i t s subsystem w i l l change i n one time s tep . These information transfers represent specific hypotheses about how the dynamics of pa r t i cu la r pa r t s of the system are re la ted to the dynamics of other par ts of the system. I t is during t h i s exerc ise , known as "looking outward", that interdisciplinary communication becomes e s s e n t i a l .
Third, the submodels for each subsystem are constructed. Each subgroup must conceptualize the processes needed t o predict the re levant indicators and information requested by other subgroups, given the relevant actions and information they have requested from other subgroups.
Fourth, the submodels are linked together into the f u l l simulation model. The complete model is "run" under a va r i e ty of scenarios to explore the consequences of various hypotheses about system structure. T h i s exercise def ines c r i t i ca l hypotheses (and therefore research p r i o r i t i e s ) which m u s t be t e s t ed t o improve the co l lec t ive understanding of the system. The workshop concludes w i t h a discussion of the preceding days ' act ivi t ies .
- 5 -
2.0 BOUNDING THE IWIFR SIMULATION MODEL
IWIFR is a research program charged w i t h improving t h e understanding and predict ion of wildl i fe responses to s i lvicul tural manipulat ions of second-growth fo re s t s . To t h i s end, description of the feasible management a l t e rna t ives , or actions, and the measures used to eva lua te t he e f f ec t s of ac t ions on the bio-physical system, or indicators, begin to desc r ibe t he r ea l i s t i c limits of the system which w i l l be considered during the workshop. The system t o be simulated is further defined by placing the actions and ind ica tors i n a manageable s p a t i a l and temporal framework.
2 . 1 Actions
Actions, i n the context of the IWIFR programs, a r e the feas ib le human intervent ions which can a l t e r t he c h a r a c t e r i s t i c s of second-growth f o r e s t s and wi ld l i f e populations. I t is important to define the actions as single interventions (e.g. , scarification) rather than multiple, or a c l a s s o f , intervent ions (e.g., s i t e p r e p a r a t i o n ) . Pa r t i cu la r components of the system may respond d i f f e r e n t l y to spec i f i c ac t ions which are of ten grouped in to one generic category.
During the workshop f o r e s t - r e l a t e d a c t i o n s f e l l i n t o a few s e t s which tended t o be app l i ed a t pa r t i cu la r s t ages of forest development, while wildlife-related actions could be grouped into the broad ca tegor ies of enhancement and control (Table 2 . 1 ) . I n addi t ion , there were a s e r i e s of possible .actions suggested by pa r t i c ipan t s which would not d i rec t ly manipula te the fores t o r wi ld l i fe b u t could influence the dynamics of both.
- 6 -
2 . 2 Indica tors
Indicators are those measurements which individuals use to evaluate the s ta te , or heal th , of a system. They are the l i n k s between the simulation model and the par t ic ipants ' "mental" model of the system. Different people use different measures of system performance and it is therefore important t o compile a comprehensive s e t of i nd ica to r s t ha t represent the in te res t s of a l l pa r t i c ipa t ing agenc ie s and groups. T h i s ensures that the simulation model remains relevant to the concerns of a l l p a r t i c i p a n t s .
The indicator l i s t generated a t t h e workshop r e f l ec t ed t h e two major a reas of focus - fo re s t ry and w i l d l i f e
(Table 2 . 2 ) .
2.3 Space
The i n i t i a l d i s c u s s i o n of t he spa t i a l r e so lu t ion of the model was s t r a igh t fo rward . Pa r t i c ipan t s f e l t a hypothe- t ical watershed of 80 km2 i n a rea , d iv ided in to 1 0 0 equal- s ized u n i t s of 8 0 hectares would be adequate to represent the s p a t i a l dynamics of re la t ive ly i so la ted popula t ions of deer and e l k , and could be used t o . r e a l i s t i c a l l y s i m u l a t e f o r e s t management p rac t i ces s u c h as c lear -cu t t ing .
D i f f i cu l t i e s a rose l a t e r i n the workshop when par t ic ipants rea l ized tha t the in te rna l dynamics of a s i t e could only be appl ied to the en t i re s i te . Fac tors s u c h a s micro-habitat differences i n spec i f i c a r eas w i t h i n a s ing le s i t e could not be considered.
The scope of any model, however, is a compromise between the specific, enabling examination of very specif ic hypotheses and the general, enabling examination of general
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T a b l e 2 . 2 L i s t of i n d i c a t o r s d e v e l o p e d a t t h e IWIFR Workshop
I. Forest-Related i. volume (m3/ha)
ii. s t a n d d e n s i t y ( s t e m s / h a )
i v . t r e e h e i g h t ( m ) v . % b r u s h c o v e r
v i . % crown cover
v i i i . debr i s d e n s i t y i x . r o t a t i o n age
iii. p i e c e s i z e volume (m3/tree)
v i i . mean annua l i nc remen t (m3 /ha , m3/stem)
x . " w i l d l i f e s i t e index"*
11. Wildlife-Related i,
ii. iii.
i v .
v i . v i i .
v i i i .
i x ,
x i .
V.
X .
number and d i s t r i b u t i o n of e l k (by age and s ex c lass ) number a n d d i s t r i b u t i o n of deer (by age and s ex class) a g e - s p e c i f i c b i r t h r a t e s body we igh t ( k g ) a n t l e r s i ze (score) * number k i l l e d by h u n t e r s calf t o cow r a t i o a d d i t i o n a l ' m o r t a l i t y as a r e s u l t of e n v i r o n m e n t a l
number. of p r e d a t o r s by p r e d a t o r t y p e seedl ing m o r t a l i t y from brows ing ( s t ems /ha ) h e i g h t growth r e d u c t i o n from browsing ( m )
f a c t o r s *
*not implemented.
N.B.: I1 i i i - v i i i refer t o e l k and deer
- 8 -
c la s ses of hypotheses. Given the objectives of t h e workshop, (Section 1) a broad perspective which would permit evaluation of t h e importance of var ious c lasses of hypotheses, such as predation versus food l imi t a t ion i n w i ld l i f e dynamics, was necessary. Participants recognized that the single model w i t h one hundred 80 ha. s i t e s developed a t t h e workshop could not address hypotheses a t every level of d e t a i l b u t could address general hypotheses a t a broad sca le .
2 . 4 Time - The time horizon of the model was agreed to be 2
fo re s t ro t a t ions . T h i s would mean a simulation length of 200 years on the poores t s i t e s . I n i t i a l ly , fo re s t ry i n t e re s t s sa id tha t the dynamics of an establ ished and growing f o r e s t were slow enough to allow a model i t e r a t i o n of 5 or 1 0 years. However, t h e i n t e rac t ion between the fores t and wi ld l i f e , i n terms of animal damage and population responses to changing habitat conditions,can occur on a f a s t e r time sca le . Many of the plant species are annuals; others p u t on a f l u s h of .
annual growth. E l k and deer have an annual cycle of mating, wintering, calving, and summer feeding. Yet, dispersal responses and processes of the wildlife occur over periods of time shorter than one year. I t was decided to le t the model have an annual time step and allow for implicit seasonal representat ion i n the submodels i f necessary. The wi ld l i f e submodels considered 3 seasons: winter (November - February) , spring (March - May) , and summer (June - October) .
- 9 -
2.5 Submodel Defini t ion
Having def ined the spat ia l and temporal bounds of the model, as well as the key i n p u t s and outputs, the system was divided into 5 subsystems. The c r i t e r i a fo r p rope r division are: minimization of information transfers between subsystems (each submodel simulated a r e l a t i v e l y isolated, se l f -contained par t of the whole system) , e f f i c i e n t divis ion of the expert ise of the participants such that each subsystem represents the concerns of a particular subgroup of s p e c i a l i s t s , and' f a i r l y e q u a l programming workloads for each member of the workshop s t a f f .
Par t ic ipants agreed tha t deer , e l k and predators were separate subsystems. The predator subgroup members were given the charge of deciding among themselves which types of predators to consider . Because hunters can "switch" from one ungulate species to another, the predator submodel was to cons ider the e f fec ts of h u n t i n g as wel l .
Pa r t i c ipan t s a l so i n i t i a l ly ag reed t o d iv ide the biological habi ta t for wildl i fe according to the success iona l s ta tus of a s i te . Therefore , one subsystem was t o have been "early" succession and another "late" succession. T h i s concept was l a t e r abandoned because of t h e d i f f i c u l t y i n def in ing b io logica l ly meaningfu l c r i te r ia for d iv is ion and because the processes for predicting changes i n hab i t a t s t ruc tu re would have t o be conceptualized twice. As an a l te rna te , the b io logica l habi ta t was divided into a subsystem which considered the dynamics of primary wood product species, called "t imber" and a subsystem which considered the dynamics of o ther p lan ts , ca l led "vegeta t ion" .
- 10 - 2.6 Lookinq Outward
The purpose of looking outward is to def ine the p ieces of information a pa r t i cu la r subsystem requires from a l l other subsystems to predict how that subsystem w i l l behave dynamically. T h i s is a qual i ta t ive ly d i f fe ren t ques t ion than the t r ad i t i ona l , which requires lists of "factors which a f f ec t " a pa r t i cu la r component of a system. The product of t h i s exercise is an interact ion matr ix , w i t h the columns specifying what information a subsystem requires from each of the other subsystems l isted on the rows (Table 2.3). The diagonals are crossed out because those represent t h e i n t e r n a l dynamics of each subsystem, a t a s k l e f t t o t h e subgroups to cons ider .
We s t ress tha t each p iece of information l is ted i n the matrix represents a specific hypo.thesis. For example, the elk subgroup required from the timber subgroup debris height and cover., The hypothesis is that the presence and amount of debris has a s i g n i f i c a n t e f f e c t on t h e a b i l i t y of e lk to dis t r ibute themselves .
2.7 S p a t i a l , S i t e and Vegetat ion Character is t ics
Considerable time was spen t a t t he workshop i n def ining a minimum s e t of cha rac t e r i s t i c s fo r each s i t e . Again, there were t r adeof f s t o be considered, t h i s time between spending a g rea t dea l of time descr ibing the physical a t t r ibutes of t h e hypothetical system and spending time considering the processes and hypotheses envisioned by par t ic ipants as important i n system dynamics. The general topographic and biogeoclimatic features of the region had t o be derived by t h e pa r t i c ipan t s and are given
i n Figure 2 . 1 . The fo l lowing charac te r i s t ics had t o be spec i f ied for each s i te and therefore derived by the
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p a r t i c i p a n t s t o be ab le to s imula te t h e model on t h e l a s t day:
(a ) s tand age ( b ) s i t e index (c ) tending regime ( d ) establishment regime (plant ing v s . na tura l ) ( e ) s i t e p r e p a r a t i o n regime ( f ) harvesting regime (harvest or no harvest) (9) s lope ( h ) aspect
The dynamics of the following plant species were simulated:
Perennials - (a) salmonberry ( b ) e lderberry (c) willow ( d ) s a l a l (e) huckleberry ( f ) cedar
Annuals - (9) s k u n k cabbage ( h ) sword fe rn ( i ) deer fern ( j ) fireweed ( k ) other "weeds"
(1) arboreal l ichen ( m ) Douglas f i r ( n ) western hemlock
The presence or absence of each plant on a s i t e was a function of subzone and moisture regime.
- 1 4 -
3.0 VEGETATION SUBMODEL
The v e g e t a t i o n submodel.was r e s p o n s i b l e for p r o v i d i n g f o r a g e f o r t h e deer and e l k s u b g r o u p s , g i v e n r e l a t i v e c r o w n biomass from t h e t i m b e r s u b g r o u p a n d p r e v i o u s f e e d i n g l e v e l s from t h e w i l d l i f e g roups . The dynamics had t o a l so be
r e s p o n s i v e t o t h e f o r e s t r y m a n a g e m e n t p r a c t i c e s s i m u l a t e d i n t h e model.
A major concep tua l p rob lem wi th t he submode l was d e f i n i n g t h e components of t h e v e g e t a t i o n t o b e s i m u l a t e d . Due t o t h e l imi ted time a v a i l a b l e i n t h e w o r k s h o p t h e subgroup was f o r c e d t o compromise between g a t h e r i n g d a t a t o set i n i t i a l c o n d i t i o n s for t h e submodel a n d c o n s i d e r i n g a l t e r n a t e h y p o t h e s e s about v e g e t a t i o n d y n a m i c s a n d r e s p o n s e s t o f e e d i n g by w i l d l i f e . T h e s u b g r o u p f i n a l l y decided t o consider the dynamics of s i x p e r e n n i a l s p e c i e s , f i v e t y p e s o f a n n u a l s , a n d a r b o r e a l l i c h e n s . However t h e v a s t d a t a . r e q u i r e m e n t s g e n e r a t e d by t h i s l i s t of v e g e t a t i o n p r e c l u d e d i n c l u s i o n o f p r o c e s s e s s u c h a s c o m p e t i t i o n among t h e f o r a g e t y p e s .
3 . 1 P e r e n n i a l s
The s i x p e r e n n i a l s p e c i e s w e r e assumed t o grow l o g i s t i c a l l y :
biomasst+l = biomass t + r * biomasst (1-biomasst/K)
where r is t h e i n t r i n s i c g r o w t h r a t e , K is t h e c a r r y i n g c a p a c i t y and b iomass t is t h e amount l e f t a f t e r f e e d i n g b y w i l d l i f e . The r and K paramete r s were estimated for each s p e c i e s i n e a c h moisture type and subzone (Tables 3 .1 - 3 .3 )
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3.2 Annuals
I t was assumed that the biomass of each of the f ive groups of annuals was s imply their carrying capaci ty (K). As w i t h the perennials the carrying capacity was dependent on species, moisture and subzone.
3.3 Ef fec t of L i g h t Limitation on,Carrying Capacity
The carrying capaci ty of both annuals and perennials was assumed t o be a function of l i g h t penetration through the canopy formed by the timber species (Figure 3.la, 3 . l b ) . The surrogate for avai lable l i g h t was taken to be the r a t io of actual t imber fol iage to maximum possible timber foliage (Section 4 . 7 ) .
3 . 4 Arboreal Lichens
Arboreal lichens begin growing i n t he fo re s t a f t e r the canopy closure decreases,usually when t ree matur i ty is reached. There was no convenient way to detect the reduct ion i n crown closure given the present model s t ruc ture . A s
a n a l t e rna te , l i chens were assumed to begin growing when the stand age reached 50. Lichen biomass was assumed to increase t o a maximum biomass according t o an annual growth r a t e . Both parameters ( i .e. , maximum biomass and annual growth r a t e ) were dependent on subzone and moisture type (Table 3 . 4 ) .
T h i n n i n g was assumed t o reduce lichen biomass by the same proportion as the propoStion of stems removed. Clear cut t ing e l iminated l ichens a l together .
- 19 -
Table 3 . 4 Parameters for arboreal lichen dynamics.
North aspect K yea r s t o K
South apsect K years t o K
CWHw
dry average moist wet
CWHd
dry average moist wet
CDFw - dry aver age moist wet
5 0 0
200
0
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2 0 0
0
0
0
100 0
0 0
2 0 0
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1 8 0 0
5 0 0
2 0 0
0
1 2 0 0
2 0 0
0
0
5 0 0
1 0 0
0
0
1 0 0
1 5 0
200 -
130
200
200
200 -
I( = carrying capacity (kg/hectare)
- 20 -
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0 a a
a a
I I I 0 .I .2 .3 .4 .5 .6 .7 .8 .9 1.
I
Y
0 LL
c
0
PROPORTION .OF MAXIMUM POSSIBLE FOLIAGE BIOMASS
Figure 3.1 Effects of overstory biomass on vegetation carrying capacity. Fw = fireweed; S = skunk cabbage; S = sword fern; Df = Deer $ern; W = willow; Eb = Eldergerry; = Salmonberry; Sa = Salal; Hb = huckleberry; = cedar.
- 21 -
3.5 Forage Available for Browsing
During the workshop there was considerable confusion over t h e amount of the forage species avai lable as food for deer and e lk . A decision was made t o make 1 0 % of the standing crop of both annuals and perennials and 13% of arboreal l ichens avai lable as food for deer and e lk . T h i s l inear re la t ionship is s u r e l y inaccurate and m u s t be improved.
3 .6 Ef fec ts of S i te Prepara t ion
Burning, scar i f i ca t ion and herbicide appl icat ion were implemented i n t h e timber submodel. The e f f e c t of these act ions was t o r e s e t t h e standing biomass of the vegetation species the year the t rees were harvested, according to t h e type of s i t e p repa ra t ion and the response of each species to t he d i f f e ren t k i n d s of s i te p repara t ion (Table 3 . 5 ) . The biomasses were r e s e t a s a f r ac t ion of carrying capaci ty .
3 . 7 F e r t i l i z a t i o n
Fer t i l i za t ion could be specif ied by the user a t any time i n the simulation and was assumed to increase the carrying capacity of a l l p e r e n n i a l s and annuals by 1 0 %
for 5 years.
Ua
J
oc
sa
m
mu
a0
4-1
Om
c
u
-4 a
um
CllW
0
.m
ocn
-4 a
uu
ca
,
Ua
J
wc
aJu cnLC W
aJ
>a
GO
ou
00
cc
-4 -4
uu
cam
hu
ma
, acn
W
aJ
a m
l-ll-ldo
mo
0
0
11
11
1
0
rl
- 23 -
4.0 TIMBER SUBMODEL
The r e s p o n s i b i l i t i e s of the timber subgroup were t o produce a dynamic conceptualization of t r e e and forest growth, given a range of s i l v i c u l t u r a l a c t i o n s and wi ld l i f e browsing leve ls . The submodel had t o be responsive to an a r ray of stand establishment and tending/harvesting regimes as well as wildlife browsing. I t had t o produce those variables which the other subgroups had ident i f ied as important information l i n k s i n the looking outward exercise.
The possible act ions for each s i te are given i n Table 4 . 1 ; one act ion from each c lass was specified for each s i t e . The var ious act ions were hypothesized to have different consequences for development of other vegetation (Section 3 ) as wel l as debr i s l eve ls and coverage.
The f o r e s t model considered each si te as being even- aged and of a s i n g l e spec ies , e i ther Douglas f i r or western hemlock. State-dependent (as opposed t o time-dependent) stand growth models e x i s t f o r B.C. fo res t s (e .g . , Mi tche l l , 1 9 7 5 ) b u t t hey a r e a t an inappropriate level of resolut ion for the purposes of the workshop. Instead, a very simple representation of f o r e s t growth was constructed, taking care to ensure tha t the dynamics were responsive i n a r e a l i s t i c manner t o s i l v i c u l t u r a l p r a c t i c e s and wildlife impacts. The basic dr iving var iable for the submodel was the time s i n c e i n i t i a t i o n of stand development ( n o t t h e same as time s ince s tocking) , ca l led "s tand age" . Par t ic ipants fe l t tha t , fo r the purposes of the workshop the dynamics of both timber species could be regarded as the same. I t was necessary to spec i fy which species was growing on a s i t e because of the d i f fe ren t ia l feed ing preferences of wildl i fe (Tables 5 . 4 , 6 . 1 ) .
- 24 -
Table 4 . 1 Management a c t i o n s i m p l e m e n t e d i n t h e timber submodel.
I . S i t e P r e p a r a t i o n i. n o t h i n g
iii. sca r i fy ii. burn
i v . herb ic ide
11. R e g e n e r a t i o n S t o c k i n g ( / h a ) I n i t i a l S t a n d Age ( y r s ) i. n a t u r a l 500-1500 -3 t o -7
ii. a r t i f i c i a l 1 5 0 0 0
111. Tend ing and Harves t % Debris Cover Debris H e i q h t ( m ) i . space t h i n n i n g 1 0 0 1 . 0
t h i n n i n g 30 1 . 0 iii. c lear c u t t i n g 50 0 .5
ii. commerc ia l
- 25 -
4 . 1 I n f l u e n c e o f W i l d l i f e
E l k a n d d e e r were h y p o t h e s i z e d t o a f f e c t stem m o r t a l i t y a n d c h a n g e s i n g r o w t h .
4 . 1 . 1 Browsing E f fec t s
4 . 1 . 1 . 1 Stem M o r t a l i t y
T h e p r o p o r t i o n o f stems k i l l e d was assumed t o be d i r e c t l y r e l a t ed t o p r o p o r t i o n of f o l i a g e e a t e n i n a y e a r , s u c h t h a t 50% o f t h e stems were k i l l e d i f 50% o f t h e f o l i a g e was removed by w i l d l i f e . T h i s r e l a t i o n s h i p was assumed t o
be i ndependen t o f t r e e a g e or s i ze . T h e h y p o t h e s i s i m p l i c i t i n t h i s r e l a t i o n s h i p is t h a t t h e p r o b a b i l i t y o f d e a t h f r o m browsing fo r a n i n d i v i d u a l t ree is l i n e a r l y r e l a t e d t o i t s r e l a t i v e f o l i a g e l e v e l s a n d i n d e p e n d e n t of t r ee s i z e .
3.1.1.2 Changes in Growth
S t a n d g r o w t h c o u l d be changed by browsing. The w i l d l i f e s u b g r o u p s c o u l d n o t d e r i v e a p p r o p r i a t e f e e d i n g r e l a t i o n s h i p s t o c a l c u l a t e p e r c e n t a g e of leaders e a t e n . T h e t i m b e r s u b g r o u p t h e r e f o r e h y p o t h e s i z e d t h e r e l a t i o n s h i p b e t w e e n p e r c e n t leader loss a n d p e r c e n t f o l i a g e e a t e n was t h a t g i v e n i n F i g u r e 4 . la ; t h i s was t h e n u s e d t o r e d u c e s t a n d a g e ( F i g u r e 4 . l b ) . Note t h a t , e v e n i f a l l leaders were e a t e n , s t a n d a g e r e d u c t i o n would o n l y b e 0.9 yea r s . The h y p o t h e s i s i m p l i e d i n . t h i s r e l a t i o n s h i p is t h a t a n i m a l f e e d i n g c a n n e v e r c o m p l e t e l y h a l t s t a n d d e v e l o p m e n t a n d t h a t t h e s t a n d c a n a l w a y s e v e n t u a l l y a t t a i n c h a r a c t e r i s t i c s i t w o u l d u n d e r c o n d i t i o n s of n o b rows ing . Tree c h a r a c t e r i s t i c s a r e h y p o t h e s i z e d t o n e v e r b e p e r m a n e n t l y a l t e r e d by browsing.
- 26 -
0 30 100 O/o LEADERS EATEN
J 0 I00
O/o FOLIAGE BIOMASS EATEN
Figure 4 . 1 E f f e c t of browsing on s t a n d age.
- 27 -
4 . 1 . 2 Direct I n f l u e n c e
The w i l d l i f e s u b g r o u p c o u l d n o t d e r i v e a p p r o p r i a t e r e l a t i o n s h i p s t o c a l c u l a t e p e r c e n t a g e o f stems k i l l e d . T h e r e was c o n s i d e r a b l e u n c e r t a i n t y i n t h e d i r e c t e f f e c t s o f w i l d l i f e . I t was a s s u m e d t h a t t h e d i r ec t damage t o t h e s t a n d by d e e r a n d e l k , s u c h a s t r a m p l i n g , was n e g l i g i b l e a n d was n o t i n c l u d e d i n t h e m o d e l .
4 . 2 H e i q h t
H e i g h t g r o w t h was h y p o t h e s i z e d t o be a f u n c t i o n of s t a n d a g e a n d s i t e i n d e x ( F i g u r e 4 . 2 ) . S t a n d a g e was r e s e t a f t e r c lear c u t t i n g a c c o r d i n g t o t h e r e g e n e r a t i o n p o l i c y ( T a b l e 4 . 1 ) I incremented by 1 e v e r y s i m u l a t e d c a l e n d a r y e a r , a n d reduced b y b r o w s i n g ( S e c t i o n 4 . 1 . 1 . 2 ) . U n d e r s t o r y v e g e t a t i o n was assumed t o n o t a f f e c t t i m b e r g r o w t h .
4 . 3 Timber Volume
Volume o f t imber was assumed t o be a f u n c t i o n o f h e i g h t a n d i n i t i a l s t o c k i n g ( F i g u r e 4 . 3 ) .
4 . 4 S t a n d D e n s i t y
C h a n g e s i n s t a n d d e n s i t y were h y p o t h e s i z e d t o be d e t e r m i n e d by n a t u r a l m o r t a l i t y , s p a c i n g a n d t h i n n i n g a c t i o n s , a n d a n i m a l b r o w s i n g ( S e c t i o n 4 . 1 . 1 . 1 ) .
Na tu ra l m o r t a l i t y was a p p l i e d t o stems a f t e r removal from t h i n n i n g a n d a n i m a l f e e d i n g . A n a t u r a l d e c l i n e i n s t a n d d e n s i t y was p o s t u l a t e d ( F i g u r e 4 . 4 ) a n d t h e a c t u a l s t a n d d e n s i t y was t a k e n t o b e t h e d e n s i t y a f t e r t h i n n i n g
3
- 28 -
STAND AGE - Figure 4 . 2 S t a n d h e i g h t as a f u n c t i o n o f s t a n d age.
.
Index
I n dex
Initial Stocking (Stems/ha)
F i g u r e 4 . 3
J 0
STAND HEIGHT, m 50
S t a n d volume.
- 29 - a n d a n i m a l f e e d i n g or t h e d e n s i t y a f t e r t h i n n i n g , a n i m a l f e e d i n g , a n d n a t u r a l d e a t h , w h i c h e v e r was t h e lesser . T h e r e f o r e , n a t u r a l m o r t a l i t y i m m e d i a t e l y a f t e r a s p a c i n g i s u s u a l l y 0 , u n t i l s t a n d h e i g h t b e c o m e s l a r g e e n o u g h . The s t and was r e p l a n t e d i f t h e r e were less t h a n 700 stems/ hectare a t a s t a n d age of 2 y e a r s a n d t h e s t a n d h a d b e e n e s t a b l i s h e d by p l a n t i n g .
4 . 5 Crown C l o s u r e
Crown c l o s u r e was assumed t o be a f u n c t i o n of a n n u a l h e i g h t i n c r e m e n t a n d stem removal . I t was a s s u m e d t h a t t he re wou ld be an added crown closure of 8% f o r e v e r y meter i n c r e m e n t i n s t a n d h e i g h t . Therefore , a s t and becomes c o m p l e t e l y c l o s e d when the s tand he ight becomes 12 .5m. The crown opened as stems were removed by t h e c o m b i n e d e f f e c t s of a n i m a l d a m a g e , s p a c i n g a n d / o r t h i n n i n g , a n d n a t u r a l m o r t a l i t y ( F i g u r e 4 . 5 ) .
4 . 6 L i v e Crown Rat io
Live c rown r a t i o was assumed t o be s imply a f u n c t i o n of s t a n d h e i g h t ( F i g u r e 4 . 6 ) w i t h two of t h e i n t e r p o l a t i o n p o i n t s s e t by i n i t i a l s t o c k i n g . Maximum l i v e c r o w n r a t i o i s t h e r e f o r e r e a c h e d more r a p i d l y i n a h i g h - s t o c k e d s t a n d t h a n i n a low-stocked s t a n d , r e f l e c t i n g t h e i n f l u e n c e o f i n t r a - t r e e c o m p e t i t i o n . C a l c u l a t i o n of h e i g h t t o l i v e crown was t h e r e f o r e :
h e i g h t t o l i v e c r o w n = h e i g h t x ( l - l i v e c r o w n r a t i o )
- 30 -
IO00
0
Figure 4.4 Natural stem mortali ty. Stand density is taken to be the stems l e f t a f t e r a l l o t h e r m o r t a l i t y , o r stems calculated from the curve below, whichever is lower.
Figure 4.5
% STEMS REMOVED
Effec t of stem removal on crown closure. Stems can be removed by animal damage, s i l v i c u l t u r a l p rac t i ces , and na tura l mor ta l i ty .
- 31 -
0 l-
W > A &. -
1 500 IO00
e o z n g
HEIGHT, m
Figure 4 . 6 Live crown r a t i o .
- 3 2 -
4 . 7 Foliage Biomass Avai lable to Wildl i fe
Tree foliage biomass regress ions ex is t for B.C.
f o r e s t s (Kimmins, pers . comm.) , b u t require knowledge of t ree a t t r ibutes other than those t h e model was ca lcu la t ing ( s u c h as d iameter a t b reas t he ight ) . Therefore , i t was assumed t h a t a t r e e produced a kilogram of foliage for every meter of crown length ava i lab le to wi ld l i fe . The crown length ava i lab le to wi ld l i fe was the l i ve crown length i f
the height was less than 2m, 2m minus h e i g h t t o l i v e crown i f t h e height was greater than 2m and the he igh t t o l i ve crown was less than 2 m , or 0 if the h e i g h t t o l i v e crown was greater than 2m.
The other vegetation subgroup requested proportion of maximum possible fol iage biomass for the par t icu lar subzone to ca l cu la t e s t and c losu re e f f ec t s on vegetation growth. A surrogate index used:
stand height maximum stand height x (crown closure)
for subzone
T h i s i n d e x r e a c h e d 1 0 0 % when s t a n d h e i g h t r e a c h e d
maximum and the overstory become completely closed.
- 3 3 -
5 . 0 DEER SUBMODEL
The general charge of the deer subgroup was t 6 b u i l d
a population model of black-tailed deer by developing a s e r i e s of hypotheses specifying how the species responds t o i ts environment. The group wasspecifically concerned w i t h describing how the environment influences movement, feeding, survival and reproduction w i t h i n t h e s p a t i a l s t r u c t u r e described i n Section 2 . 3 . Much of t h i s information was considered to be season specif ic ; t h u s the funct ional re la t ion- s h i p s developed for these processes , or a t least their parameters, were of ten d i f fe ren t for the th ree seasons considered (Section 2 . 4 ) .
Information provided by the deer subgroup to o the r groups included the number of deer i n each age and sex c lass , the amount of food of each of the 1 4 types consumed over the ent i re year on each s i t e (kg/ha) and an index of the qua l i t y of escape cover on each s i t e .
The deer subgroup was also responsible for developing a model of winter snowfal l for the area. The snow submodel w i l l be d e s c r i b e d f i r s t , a s i t has important implications t o some of the re la t ionships d i scussed la te r i n t h i s sect ion. I t w i l l be followed by a descr ip t ion of each of the processes mentioned above: movement, feeding, survival and reproduction.
5 . 1 Snowfall
5 . 1 . 1 Snow Reaching the Canopy
Snow was assumed t o occur only i n winter . To r ea l i s t i ca l ly r ep resen t na tu ra l t empora l va r i a t ion i n snowfall patterns, the winter was divided into three d i s t i n c t
- 3 4 -
p e r i o d s . T h e p o t e n t i a l s n o w f a l l d e p t h i n e a c h p e r i o d was a l l o w e d t o v a r y ( p o t e n t i a l d e p t h is d e f i n e d as t h e d e p t h of snow which would be on t h e g r o u n d i f t h e r e were n o c a n o p y ) .
An a d d i t i o n a l c o m p o n e n t , n o t i n c l u d e d . i n t h e model d u r i n g t h e w o r k s h o p b u t s i n c e i n c o r p o r a t e d , made the amoun t of s n o w r e a c h i n g t h e c a n o p y i n t h e " m i d d l e s u b z o n e " 50% of t h a t i n t h e " u p p e r " s u b z o n e a n d i n t h e "low" subzone 1 0 % o f t h a t i n t h e " u p p e r " . s u b z o n e . T h e r e d u c t i o n f a c t o r s at tempt t o mimic t h e g e o g r a p h i c a l v a r i a t i o n i n s n o w f a l l .
T h e l e n g t h o f e a c h p e r i o d ' w a s a l s o a l l o w e d t o v a r y , p r o v i d e d t h a t t h e sum o f a l l t h r e e p e r i o d s was a l w a y s e q u a l t o t h e t o t a l l e n g t h of t h e w i n t e r p e r i o d (Section 2 . 4 ) .
T h e s e p e r i o d s do n o t n e c e s s a r i l y r e p r e s e n t t h r e e c o n s e c u t i v e p e r i o d s of time. R a t h e r , t h e y r e p r e s e n t a g r o u p i n g o f a l l d a y s of w i n t e r i n t o t h r e e classes c o r r e s p o n d i n g t o "low", "med ium" , and "h igh" snowfa l l . A k e y a s s u m p t i o n h e r e is t h a t t h e e f f e c t of s n o w f a l l on t h e p r o c e s s e s s u c h as f e e d i n g a n d s u r v i v a l is i n d e p e n d e n t of t h e s e q u e n c e of s n o w f a l l e v e n t s .
5 .1 .2 Snow Reachinq the Ground
The a c t u a l d e p t h o f snow on t he g round on a s i t e was h y p o t h e s i z e d t o be a f u n c t i o n o f t h e d e p t h o f snow r e a c h i n g t h e c a n o p y a n d t h e e f f e c t i v e n e s s o f t h a t c a n o p y a t i n t e r c e p t - i n g s n o w . T h e f o l l o w i n g r e l a t i o n s h i p was d e f i n e d t o i n c o r p o r a t e t h e s e two e f f e c t s ( F i g u r e 5.1) :
snow d e p t h o n s i t e ( i ) = snow r e a c h i n g 1 - crown closure i n w i n t e r p e r i o d ( j ) canopy on s i t e on s i t e ( i )
( i ) i n w i n t e r 1 p e r i o d ( j )
- 35 -
S i t e s w i t h t rees l ess than two meters i n height were assumed . t o have no in t e rcep t ion capab i l i t i e s . T h i s r e l a t ionsh ip implies that a completely closed canopy w i l l prevent any snow from reaching the ground, regardless of the amount of the snow reaching t h e canopy.
5 .l. 3 Food Covered by Snow
Having calculated the depth of snow on each s i t e f o r each winter period, i t was necessary to decide what proportion of food was unavai lab le to wi ld l i fe due t o snow cover. Each food type-was assigned to a he ight c lass and t h e proportion of food l e f t uncovered i n each c lass was defined by t h e fol lowing re la t ionship:
proportion uncovered = 1 . 0 - ESD * depth of snow on s i t e ( i ) on s i t e ( i )
where ESD is the he ight c lass spec i f ic s lope of t h i s re la t ionship (Table 5 . 1 ) . T h i s s lope increases as t h e height of t h e p lan t decreases,makingrsmaller plants unavai lable a t r e l a t ive ly sma l l snow depth.
Special consideration had t o be g iven to l i chens . I t was assumed tha t the amount of snowfall reaching the canopy i n a par t icular snowfal l per iod would r e f l e c t t h e in t ens i ty of snowfal l dur ing that per iod. I t was assumed that the proport ion of t o t a l l i c h e n s on the ground ac tua l ly avai lable for feeding upon would decrease as the amount of snow reaching the canopy increased (Figure 5.3;.
- 36 -
Table 5 . 1 Slopes of the snow depth - food coverage re la t ionship .
Food Type
salmonberry elderberry willow s a l a l huckleberry cedar s k u n k cabbage sword fe rn deer fern fireweed arboreal l ichens douglas f i r hemlock
Slope
01 .01 .01 .0143 .01 .0067 .025 .025
.025
.025 0.0 .0067 .0067
- 3 7 -
In rc 0 In
rc) - c u .
W 3 ' O N n O U 9 NO Hld30 MONS
0
U a, -4 m a c 0
a -d m
4
m a,
. u 3 F
- 30 -
9 x
.II)
- 39 -
_...
1
0 0 -
0 rr)
0 In 0 <u
318Vl lVAV SN3H311 lW101 JO NOllUOdOUd
- 4 0 -
5.2 Movement
Deer were assumed t o modify t h e i r d i s t r i b u t i o n among s i t e s a t the beginning of each season and to maintain that same distribution throughout the season. Sites were se lec ted on the basis of the i r re la t ive habi ta t va lue accord ing to three cr i ter ia : .winter range, escape cover and food. Each of t h e s e c r i t e r i a was weighted according t o i t s r e l a t i v e importance. The weighting factors varied w i t h seasonal and subzone (Table 5.2). For example, s i t e s had zero value as winter range 'habitat i n summer. Likewise,winter range i n winter was weighted more heavily i n the higher subzones.
I t was unreasonable t o d i s t r i b u t e d e e r t o s i t e s based . ..
on the value of each site individually because each individual s i t e was considered homogeneous. A s i te ra re ly p rovided a good mix of the three necessary qual i t ies . Habi ta t for snow pro tec t ion ( i . e . , old growth, canopy closed) , for example is poor habitat for feeding because of low l i g h t penetrat ion. I
Deer aggregate to groups of s i t e s which col lect ively provide good hab i t a t . I nd iv idua l s i t e s were therefore aggregated into blocks of fou r s i t e s having a common node. No one s i t e was a member of more than one block of four. Thus
there were 24 four-site blocks for which the accumulated (over the four s i tes) habi ta t value was ca lcu la ted . The proportion of deer occupying each block was calculated from the following relationship:
proportion i n = accumulated value 2 4 accumulated block ( i ) of block ( i) c [value of ]
i=l block ( i)
- 41 -
Table 5 . 2 Weighting f ac to r s used for determining the re la t ive va lue of s i t e s a s dee r hab i t a t . 1 - CDf-Wet; 2 - CWH-Dry; 3 - CWH-Wet.
Season
Spring
S umme r
Winter
Subzone
1 2 3
1
2 3
1 2 3
Winter range
0 0 0
0 0 0
0 . 4
.5
Escape cover
. 2
. 2
. 2
. 5
.5 05
.5
. 2
0
Food
. a -
. a
. a
. 5
.5 05
.5
. 4
.5
- 4 2 -
The accumulated habitat value of a block was computed a s a weighted sum of i t s value for winter range, escape cover and forage. The next three subsections describe how the three abovementioned c r i t e r i a were used t o p r e d i c t t h e habi ta t value of a s i t e .
5 .2 .1 Winter Range
Four components were included i n t h e ca l cu la t ion of a s i te ' s value as winter range: crown closure, proportion of t o t a l food tha t was " t a l l " , a s p e c t and l ichens. Snow depth direct ly considered. Since s i te select ion was made a t the beginning of a season i t was assumed that the deer would
dis t r ibute themselves on the basis of where they expected snowfal l to be a problem rather than were it turned out t o be a problem during that particular winter. I n essence they had to "decide where t o spend the winter" without knowing what the weather would be l ike tha t win ter .
Figure 5.4a demonstrates the relationship between crown closure on a s i t e and i ts value as winter range. This v a l u e was set equal to z e r o f o r all sites w i t h t r e e s
less than 2 meters i n h e i g h t ( i . e . , t h e s i t e was completely unsui table a s winter range).
Perennials (Section 2.7) were considered to be " t a l l " food ( i . e . , more l i k e l y t o be ava i lab le when snow is on the ground). The proportion of a l l a v a i l a b l e food biomass w h i c h fell in to the " ta l l " ca tegory was also considered a measure of the value of a si te as winter range.
~ l l s i t e s having a norther ly aspect were considered o n l y 20% as valuable as winter range as those having a souther ly aspect .
- 4 3 -
Final ly , Figure 5 .4bdescr ibes t h e r e l a t ionsh ip between ava i lab le l i chens on a s i t e and i ts value as winter range. The overal l value of a s i te as winter range was therefore given by the following relationship:
value of s i t e ( i ) = crown closure * proportion as winter range value e f f e c t of food
biomass t h a t is " t a l l "
* . 2 i f aspect ava i lab le l i chen I * I [is north value effect
5 . 2 . 2 Escape Cover
Two components were considered i n evaluating a s i t e ' s quali ty as escape cover habitat: tree stem density and t r e e height (Figures 5.5a, 5 . 5 b ) . The overal l value of the s i te as escape cover habi ta t was simply the product of these two components. T h i s value was suppl ied to the predator submodel, before b e i n q modified by i ts weighting f ac to r , t o p rov ide an indicator of the vu lnerabi l i ty of deer to predators on a p a r t i c u l a r s i t e .
5 . 2 . 3 Food - The t o t a l d i g e s t i b l e biomass of food (summed over
a l l food types) 2er hectare available i n t h e season under consideraticn was assumed s u f f i c i e n t t o c h a r a c t e r i z e t h e value of a par t icu lar s i te as feed ing habi ta t (F igure 5 .6) .
.
I .o
O L 0 60
CROWN CLOSURE , *I'
1 I
30. 70. '
AVAILABLE LICHENS Kq/ha
Tigure 5 . 4 Components of t h e winter range value criterion: ( a ) e f f e c t of crown closure: ( b ) e f f e c t of ava i lab le l i chens .
STEMS /HECTARE
I
HEIGHT OF TREES , m
Figure 5 .5 Components of the escape cover value cri terion: ( a ) e f f e c t of stem density; ( 5 ) e f f e c t of t ree he ight .
- 4 6 -
0
- 4 7 -
5 . 3 Feeding and Energy Intake
The timber and other vegetation submodels provided the deer submodel w i t h t h e t o t a l biomass ava i lab le of each food type by s i t e i n u n i t s of kilograms per hectare. These were converted into season specif ic quant i t ies represent- ing the kilocalories per hectare of ava i l ab le d iges t ib l e biomass for each food type on each s i t e (Tab le 5 . 3 ) . Next the average over a l l s i t e s w i t h i n a single block was computed for each food type. These values were fur ther modified i n winter according to the depth of snow on each s i t e i n each snowfall period.
Each food type had a season specific preference value and the following relationship was employed ( the m u l t i - species disc equat ion, Charnov 1 9 7 3 ) to ca lcua te the amount of each food type eaten per animal per day on each s i t e :
amount(kcal/deer/ = maximum kcals x preference value day) eaten of eaten when for food type ( j ) food type ( j ) food not
. o n s i t e ( i ) l i m i t i n g /
x amount (kcal/ha) /searching + 1 4 preference of food type ( j ) / ef f ic iency c value for ava i lab le on s i t e ( i ) / parameter
j=1 food type ( j )
x amount (kcal/ha) of food type ( j ) ava i lab le on s i t e ( i )
The parameters used for t h i s re la t ionship a re found i n Table 5 . 4 while Figure 5 . 7 depicts the form of t h i s re la t ionship for the case where only one food type is preferred.
- 48 -
Table 5.3
Food Type
Seasonal energy conversion factors- from annual forage biomass. These factors are intended to reflect phenological changes i n both the avai labi l i ty and calor ic value of each food type . En t r i e s i n kcal/kg of forage biomass.
Season
Spring Summer Winter ~~~~ ~
Salmonberry Elderberry W i llow S a l a l Huckleberry Cedar Skunk Cabbage Sword Fern Deer Fern Fireweed Other weeds Arboreal lichens Douglas F i r Hemlock
3230 3534 3534 3250 4297 4 000 3800 3380 3250 4120 2280 2620 4000 3620
2500 2000 2500 3250 5120 3750 2500 3750 4380 6120 2500 3380 4620 5750
1400 1800 1800 2000 3150 2250
0 1880 1750
0 600
1380 2750 2380
- 4 9 -
Table 5.4 Parameters for the multi-species disc equation used in the calculation of deer food consumption.
Searching efficiency parameter (kcal/ha) 9.0 x 1 0 ~
Season Spring Summer Winter
Maximum ration 2600 2400 2000 (kcal/deer/day)
Preference Indices Salmonberry Elderberry Willow Salal Huckleberry Cedar Skunk Cabbage Sword Fern. Deer Fern Fireweed Other weeds Arboreal lichen Douglas Fir Hemlock
.1
.08
.01
.08
.01
.01
.02
.1
. 3
.2
.01
.08
0.
0.
.1 0. 0.
. 0 5
. 2 5 0. 0. 0.
.02
. 3 5
. 2
.01
.02 0.
0. 0. .01
s .1 . 2 . 1 5
.01
.02
.06
. 4
.02
.02
0.
0.
- 50 -
- 51 -
Exploitation was not considered i n subgroup discussions b u t has since been added t o t h e model. Deer a re now constrained to eat ing the avai lable biomass, or t h e i r requirements,whichever is l e s se r . T h i s implies that crowding and in te r fe rence e f fec ts a re no t impor tan t i n deer feeding.
F ina l ly , t h e total annual consumption of each food type on each s i t e was calculated and removed from the available food.
5.4 Survival
A l l morta l i ty except tha t resu l t ing from predation was assumed to o c c u r d u r i n g w i n t e r . B a s e l i n e a g e a n d sex
spec i f ic win ter surv iva l ra tes (no t i n c l u d i n g predation are given i n Table 5.5. The amount of snowfall during winter was hypothesized to in f luence t h e ene rge t i c cos t s of deer by hindering locomotion. The energy costs of locomotion were computed for each s i te for each of t h e three winter snow- f a l l periods u s i n g the following relationship:
EL = ( S D Y ) (BMR) (1 + CH X (SDP x (1 - S D N / F B ) ) ) ,
where EL = locomotory cos ts for snowfa l l per iod (kca l ) , SDY = number of days i n snowfall period, BMR = basal metabolic rate (kcal/day) ,
CH = e f f e c t of chest height on locomotory c o s t s l SiIP = snow depth I SDN = snow densi ty (assumed c o n s t a n t ) ,
FB = snow densi ty above which s i n k i n g does not occur.
Energy intake and cos t s were summed over the three snowfall periods and a "corrected energy balance'' computed:
- 52 -
m
0
c .PI 5
m
-d
c
rn m
Q)
In
In
0
rl n . a
E-l
PP
00
..
h
rl a u Y
Y
m
In
0
04
rl
X X
m
do
rl
rl
0
.
h
rl a Y
u
Y
co
m
-em
wm
m
PI-
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LE:
rl
I 0
cvcv
ww
00
..
mm
00
4.4
xx
m
a
P-e
rld
.
.
m
dW
o
m
oco
rl . coco
..
cv I rl
ww
00
..
mm
00
rl
rl
xx
w
w
mo
r
lN
.
.
-0
04
rl
cv
r
lr
l
coco
..
kiz
m
cv I
rn c
- 5 3 -
corrected energy = intake - locomotary balance for on s i t e ( i ) cos t s on s i t e ( i ) s i te ( i )
"I
where WMR = metabolic requirement over entire winter.
T h i s corrected energy balance value i s age and sex s p e c i f i c because animals of different age and sex have different metabolic requirements and chest heights . All parameters of these relationships are provided i n Table 5.5.
T h i s corrected energy balance was hypothesized t o affect winter survival (Figure 5 . 8 ) . The weighted (by t h e proportion of deer on each site) summed over -a11 sites of these age and sex specif . ic values was used t o modify the base- l ine winter survival ra tes .
5 . 5 Reproduction
Bi r ths were assumed t o occur a t t h e s t a r t of the summer. Basel ine age specif ic natal i ty ra tes are given i n Table 5 . 6 . These values were assumed t o be influenced by energy intake during the previous winter and spring season, w i t h the spring effect being approximately three times a s inf luent ia l as the win ter e f fec t . Thus , the age spec i f ic cor rec ted energy intake was computed fo r each s i t e u s i n g the following relat ionship:
corrected energy = winter energy + spring in take for s i te in take ene.rgy ( i )
r3 x WHX + SMR]
- 5 4 -
where SMR = metabolic requirements over entire spring (Table 5.6). Figure 5.10 demonstrates the effect of corrected energy intake on natality. A weighted sum over all sites is computed and used to modify the baseline natality rates.
- 55 -
Table 5.6 Parameters used i n reproduct ion calculat ions.
Age Baseline Spring metabolic na ta l i ty ra tes requi rement ( seasonal )
0-1
1-2
2-3
3
0.
.91
1.27
1.69
1 .15 X l o 5 (kcall
1 .8 x 1 0 5
2.03 x l o 5 2.03 x l o 5
- 56 -
I .o
0.8
-3. - 2. -1. -.7 0
CORRECTED ENERGY BALANCE
1.
Figure 5 . 8 The e f fect of t h e winter energy balance on winter s u r v i v a l .
- 5
7 -
0
- sa -
6.0 ELK SUBMODEL
The e lk subgroup was responsible for developing a conceptual framework that integrated the behavioural and
* population responses of e l k t o changing habi ta t s t ructure and ab io t ic condi t ions . E l k were assumed t o move throughout the watershed i n response to availab'le escape cover, thermal cover, and quant i ty and qua l i ty of forage. Inadequate mixes of ava i lab le food and cover d u r i n g various periods of the year and a t varying stages of t he an ima l ' s l i f e cyc le were hypothesized t o d e t r i m e n t a l l y a f f e c t t h e p o t e n t i a l survivorship and fecundi ty ra tes of the population.
The e lk submodel was' composed of 2 subsections. The f i r s t s e c t i o n e v a l u a t e d t h e s e a s o n a l s u i t a b i l i t y of each s i t e f o r e l k u t i l i z a t i o n . T h i s was used to define seasonal move- ment pa t t e rns of e lk w i t h i n t h e watershed. The second sect ion integrated the qual i ty and quant i ty of forage over t h e s i t e s and seasons to generate survivorship and fecundity ra te modi f ie rs and used these i n a sex and age s t ruc tured population model.
6 . 1 Seasonal S i te Ut i l iza t ion
The elk subgroup recognized that the movement dynamics of elk are determined by a complex of ecological processes and that the re la t ive importance of the processes var ies seasonal ly . I n the spr ing, e l k a re found on south aspect slopes, taking advantage of the ear ly new spring growth of specif ic forage species . During periods of the h o t summer, e l k l i k e l y move to a r eas w i t h thermal cover on north aspect s lopes. E l k are physically excluded during t h e winter from
- 59 -
areas w i t h very deep snow, while other areas have l imited u t i l i t y because. snow depth reduces the quantity of ava i lab le forage. E l k a lso cont inuously aggregate to areas w i t h , or near, adequate predator escape cover.
I t was decided to mimic movement dynamics of e lk by d i r e c t l y r e l a t i n g t h e u t i l i z a t i o n of a s i t e t o i ts r e l a t i v e s u i t a b i l i t y , and d e f i n i n g s i t e s u i t a b i l i t y i n terms of those ecological a t t r ibutes importznt i n determining population responses.
S u i t a b i l i t y was hypothesized t o be a function of t h e seasonal digest ible energy i n the forage, modified by s i t e and season specif ic physical constraints , and t h e a v a i l a b i l i t y of escape cover:
s u i t a b i l i t y i j = diges t ib le phys ica l [~~~~~~ Of l i Imodi f ie rs cons t ra in t ] i j i
where i i s t h e s i t e and j is the season. Escape cover is evaluated only once annually. Both modifiers were scaled between 0 and 1. The l eve l of u t i l i z a t i o n of a s i t e was therefore given by:
96 s u i t a b i l i t y i j / C s u i t a b i l i t y i j
i = O
6 . 1 . 1 Seasonal Digestible Energy
The contr ibut ion from each potential forage species to the seasonal disgest ible energy avai lable to e lk on a
s i t e was the product of the available annual biomass of t h e species ir, the s i t e , t he k i loca lo r i e s of d iges t ib l e food sns!.-;y ?er kilogram for that species for a given season,
- 60 -
and a seasonal species preference factor that ranged between 0 and 1. Available annual biomass had t o be modified seasonally to adjust for within-year changes i n p lan t ava i l - ab i l i t y (Sec t ion 5 . 3 ) . For example, an herbaceous annual may have zero k i loca lor ies of food energy i n t h e winter s imply because i t i s no longer available. The species preference factor s imulates the apparent preferences shown by e lk for par t icu lar spec ies and the seasonal var iab i l i ty of those preferences. A s i t e w i t h a moderate biomass of a h i g h l y preferred browse species would have a higher value than a s i t e w i t h a la rge biomass of re la t ively unpreferred browse and e lk would spend more time and consume more forage in the p re fe r r ed s i t e . The seasonal forage preference va lues a r e l i s t ed i n Table 6 .1 .
The seasonal digest ible energy ' for a s i t e was ca l cu la t ed ' by simply summing the individual digestible energy over a l l s p e c i e s each season.
6 . 1 . 2 Escape Cover
Adequate elk escape cover was def ined as any s i t e w i t h i n c r i t i c a l minimum and maximum s tand dens i t ies of t rees greater than a minimum c r i t i c a l h e i g h t (Figure 6 . 1 ) . Any s i t e w i t h i n these cons t r a in t s was assigned an escape cover value of 1. The upper s tand densi ty was never real ized on the managed s tands.
S i t e s w i t h inadequate escape cover b u t ad jacent to s i t e s w i t h good escape cover were assumed t o be p a r t i a l l y u t i l i z a b l e . For example, elk could forage i n a port ion of a c l ea r cu t a s long as adequate escape cover was nearby. The escape cover value of 2 s i t e w i t h inadequate cover was re la ted t o the nearness of t ha t s i t e t o t he nea rby s i t e w i t h maximum cover value. Therefore, a
- 61 -
Table G . l Seasonal food preferences for elk.
Species Spring Summer-Fall Winter
Salmonberry Elderberry Willow Salal Huckleberry Cedar S k u n k Cabbage Sword Fern Deer Fern Fireweed Other Weeds Douglas F i r
Western Hemlock Arboreal Lichen
.6
. 3
.4 0.
.1 0.
1. .4
0.
.1 1. 0.
0. 0.
1. .5 .5
0. . 3
0. .8
0. 0.
.1 1. 0.
0.
0.
0.
1. 1.
. 4
. 4
.5 0. .2 .6
0.
.5
.2
.1
.4
- 6
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UU
N a0
LCLC
3"
(v
W a,
d
Q
E
m
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cJ
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(v
(v
-0
4
....
(v
(v
(v
P
....
CJC
VD
O
rl
....
(v(v
(va
....
NNaa
....
iJ 0
v)
m c
U
0" z
5 c
U 3
VI
0
'r
l c
U
....
(U
Cv
rJ
cJ
....
cJ
rJ
VI
(v
.
.e
.
CvcV
Trw
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(v-P
aa
. ....
....
PJ
m-P
a
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NC
VV
IO
rl
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(vc
vw
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VI ....
cucvw
m
VI
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NC
VC
VC
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....
- 63 -
s i t e w i t h adequate escape cover conferred an escape cover value of 0 .5 t o neighbouring si tes w i t h inadequate cover that shared a common s ide , and an escape cover value of 0.25 t o neighbouring si tes w i t h inadequate cover that shared only a common corner (Figure 6 . 2 ) . The "edge e f fec t" o r the e f fec t of c lear cut s ize could be explored by changing the magnitude of the influence of s i t e s w i t h adequate cover on adjacent s i t e s . E l k were assumed.to not use si tes w i t h an escape cover value of 0 . 0 . As a r e su l t , t he term "adequate cover" .
does notmean that the e lk are invulnerable to predat ion or w i l l not suffer thermal s t ress , b u t r a the r , e lk w i l l not be found i n areas w i t h "inadequate" access to cover.
6 .1 .3 Physical Constraints
Phys ica l cons t ra in ts were hypothesized t o a f f e c t t h e s u i t a b i l i t y of a s i t e t o e l k . The e lk subgroup used s i t e subzone, moisture type and aspect as indicators of physical s i t e s u i t a b i l i t y and seasonally modified the relative importance of each t o r e f l e c t changes i n preferences of e lk for dif ferent physical locat ions throughout the year .
The e f f e c t s of snow on s i t e s u i t a b i l i t y were considered. The winter was divided into three per iods of var iab le durat ion t h a t represented three depths of snowfall (Section 5 . 1 ) . These d i f fe ren t depths of snow were a l s o assumed t o a l t e r t h e a v a i l a b i l i t y of the understory forage (Section 5 . 1 . 3 ) . The elk subgroup also assumed s i t e s wi th snow over 1 . 2 m average depth on the ground were unavai lable to e lk .
- 6 4 -
2
0 I I I 50 IO00 2000
STAND DENSITY , Stems/ha
F i g u r e 6 . 1 E l k e s c a p e c o v e r a s d e f i n e d by s t a n d h e i g h t a n d s t a n d d e n s i t y
- 65 -
6 . 1 . 4 Calculation of Seasonal Si te Uti l izat ion
The s u i t a b i l i t y of a s i t e f o r e l k use was ca lcu la ted as the product of i t s seasonal digestible energy, escape cover value, scaled between 0 and 1, and seasonal physical s u i t a b i l i t y , a l so sca led between 0 and 1. The product r ep resen ted t ha t s i t e ' s ava i l ab le ca lo r i c food value for elk. The r e l a t i v e c a l o r i c food value represented the level of u t i l i z a t i o n of t h a t s i t e by elk, or the proportion of a season the elk population would spend feeding i n t ha t s i t e .
6 .2 P o p u l a t i o n Dynamics
The population dynamics of e lk were simulated u s i n g an age class population model w i t h four age c l a s ses - fawns, yearlings, . two year olds, and adults, for each sex. The maximum assumed surv ivorsh ip ra tes a re l i s ted i n Table 6.3. The maximum assumed fecundi ty ra tes were . 8 and .95 per 2 year old and adul t e lk respect ively. These rates could a l l be reduced i f there was insuf f ic ien t ca lor ic forage value (Section 6 . 1 . 4 ) i n the watershed to meet the ca lor ic requirements of the population.
6 . 2 . 1 Seasonal Energy Requirements
The seasonal energy requirements for the elk population were determined by the product of the number of e lk i n each age and sex c lass and the average seasonal caloric require- ments spec i f ic to each age and sex class (Table 6 . 4 ) . The metabol ic ra tes incorporate differences i n weights, l ac t a t ion cos t s , r u t t i ng cos t s and growth cos ts . I n winter ,
- 66 -
e lk were assumed t o s u f f e r an ex t r a locomotion c o s t i n the presence of snow fo r t hose s i t e s w i t h a snow depth less than 1 . 2 m (Figure 6 . 3 ) . The elk population's winter metabolic r a t e was t h u s modified by the depth of snow i n each s i t e and the proportion of time the population spent i n each s i t e .
6 . 2 . 2 . Survivorship
The elk subgroup assumed t h a t t h e potent ia l survivor- sh ip r a t e s fo r each age and sex c lass would be reduced by inadequate available energy. The reduction i n surv iva l was assumed t o depend on both the severity and duration of the shortage.
These e f f e c t s were simulated by ca lcu la t ing an average da i ly mor t a l i t y r a t e fo r each age and sex c l a s s a s a function of t h e r a t i o of ava i l ab le ca lo r i e s i n the watershed to t h e caloric requirements of the elk population (Figure 6 . 4 ) . I n the model, the function is characterized by two parameters: the maximum da i ly mor t a l i t y r a t e and t h a t r a t i o of ava i lab le ca lor ies to requi red ca lor ies (or dens i ty of food per e l k ) a t which t h e mor ta l i ty ra te would be reduced t o h a l f of i t s maximum value (Table 6 . 5 ) .
Average da i ly mor t a l i t y r a t e s were converted to , seasonal or "snow period" mortal i ty ra tes and were combined over a l l seasons and per iods to give year ly survivorship rate modifier for each age and sex c lass .
- 67 -
Table .6.3 Potent ia l surv ivorsh ip ra tes for e lk .
Ma l e Female
ca I f .80 .80
yearl ing .85 .9
two year old .94 .94 a d u l t .75 09
Table 6.4 Average daily caloric requirements (kcal/day) for e lk by sex, age c l a s s and season.
Class Spring Summer Winter
M F M F M F
calf 4180 3540 4180 3540 3396 2877
yearl ing 6550 5960 6550 5960 5324 4840 two year old 7040 7257 7040 7257 5720 5540 a d u l t 8070 8325 8070 ' 8325 6560 6365
68 -
aJ 5
U
x
- 6 9 -
SNOW DEPTH m
Figure 6 .3 Energet ic cost of moving i n snow for e l k a s a mult iple of the e lk 's basic metabol ic -. r a t e .
W I- a a
> 3 cn a
3 a n
p """""""""""_
01
AVAILABLE ENERGY
REQUIRED ENERGY Kcal
Figure 6 . 4 Ef fec t of food a v a i l a b i l i t y on e lk su rv iva l . 9 and c1 are age-class and sex spec i f ic and a r e summarized i n Table 6 .5 . The func t iona l form of fecundity reduction is the same.
- 70 -
6.2.3 Fecundity
The two year old and adult female fecundity rates were also modified u s i n g t h e r a t i o of ava i l ab le ca lo r i e s t o required calor ies . As i n the survivorship modifier the func t iona l re la t ionship needed two parameters: the maximum average daily percent reduction i n fecundity as a r e s u l t of food shortages and t h a t r a t i o of ava i l ab le ca lo r i e s t o required calor ies a t which the average daily reduction i n the fecundi ty ra te would be half of i ts maximum value (Table 6.6). These average daily reductions i n the fecundity rates were mult ipl ied by the number of days i n the season or snow period to generate seasonal reductions i n the fecundity rates and combined t o reduce the maximum annual fecundity rates for the apropriate sex and age c lasses .
Forage was removed from each s i t e i n proport ion to the total calor ic requirements of e lk , t he ava i l ab i l i t y of each browse spec ies , and t h e s i t e u t i l i z a t i o n .
6.2.4 Population Chanqe
E l k were aged annually u s i n g the natural survivorship r a t e s and the survivorship modifiers (Section 6.2.2) and calves were produced u s i n g the maximum fecundi ty ra tes and the fecundity modifiers (Section 6.2.3). The sex r a t i o of calves was assumed t o be constant a t 50%.
The elk subgroup assumed tha t e lk would emigrate from the watershed i f the total e lk populat ion exceeded 60 animals. The sex ratio for the emigrants would be 7 0 % males.
- 71 -
7.0 PREDATION AND HUNTING
The p r e d a t i o n a n d h u n t i n g s u b g r d u p was r e s p o n s i b l e for d e v e l o p i n g a conceptua l f ramework for p r e d i c t i n g t h e e f f e c t s o f p r e d a t o r s a n d h u n t e r s on deer and e l k p o p u l a t i o n s , g i v e n a g e a n d s e x s p e c i f i c d e n s i t i e s of deer and e l k and e s c a p e c o v e r .
The s u b g r o u p c o n s i d e r e d p r e d a t i o n b y w o l v e s , c o u g a r s , and bear.
7 . 1 D i s t r i b u t i o n of P r e d a t i o n
Predators were h y p o t h e s i z e d t o r e s p o n d d i f f e r e n t l y t o d e n s i t i e s of young of t h e y e a r a n d a l l o t h e r p r e y . Predator k i l l s were a p p o r t i o n e d to e a c h s e x a n d / o r a g e g r o u p w i t h i n t h o s s two p o p u l a t i o n classes a c c o r d i n g t o t h e r e l a t i v e abundance of each g roup .
P r e d a t i o n r a t e s were ca lcu la ted a n n u a l l y a n d a p p o r t i o n e d s e a s o n a l l y a c c o r d i n g t o T a b l e 7 . 1 .
7 . 2 The G e n e r a l Model
P r e d a t i o n was s i m u l a t e d u s i n g c l a s s i ca l p r e d a t o r - p r e y t h e o r y , w i t h f u n c t i o n a l a n d n u m e r i c a l r e s p o n s e s ( S o l o m o n , 1 9 4 9 ) . The model e x p l i c i t l y c o n s i d e r s c h a n g e s i n t h e number of k i l l s p e r p r e d a t o r i n r e s p o n s e t o c h a n g e s i n p r e y d e n s i t y ( f u n c t i o n a l r e s p o n s e ) a n d c h a n g e s i n t h e n u m b e r of p r e d a t o r s i n r e s p o n s e t o c h a n g e s i n p r e y d e n s i t y ( n u m e r i c a l r e s p o n s e ) .
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- 7 3 -
Predation is one of the most-studied and best under- stood ecological process. The use of well-understood models ensured that t h e b io log ica l i n t e rp re t a t ion of the uncer ta in t ies i n modelling predation on e lk and deer could be easi ly t ranslated into wel l -def ined research quest ions. The types of funct ional and numerical responses used i n the model a re summarized i n Tables 7 . 2 'and 7 . 3 ,
In te rac t ion between predators was assumed n o t t o occur.
7 . 3 Influence of Escape Cover
Escape cover for deer and e lk was assumed t o a f f e c t t he i r vu lne rab i l i t y t o p reda t ion by reducing the number of prey avai lable t o predators. A vu lne rab i l i t y f ac to r based on the proportion of the reg ion c lass i f ied as good escape cover was calculated (Figure 7 . 1 ) . Every animal is vulnerable t o predation w i t h no escape cover and only 5 0 9
of t h e t o t a l popu la t ion is vulnerable to predat ion w i t h maximum escape cover.
7 . 4 Wolf Predation
Wolf packs on Vancouver Is land are small and wolves have been seen h u n t i n g s i n g l y or i n pa i r s . Because of t h e small pack s i z e , wolf functional responses were defined i n terms of k i l l s per wolf rather than than k i l l s per pack.
- 7 4 -
T a b l e 7 . 2 F u n c t i o n a l r e s p o n s e s of p r e d a t o r t o p r e y .
Deer E l k
W o l v e s d e n s i t y d e p e n d e n t d e n s i t y d e p e n d e n t when d e e r d e n s i t y is low
B e a r d e n s i t y d e p e n d e n t d e n s i t y d e p e n d e n t
C o u g a r d e n s i t y d e p e n d e n t d e n s i t y d e p e n d e n t
T a b l e 7 . 3 N u m e r i c a l r e s p o n s e of p r e d a t o r s t o prey.
Deer E l k
Wo l v e s d e n s i t y d e p e n d e n t d e n s i t y i n d e p e n d e n t
Bear d e n s i t y d e p e n d e n t d e n s i t y i n d e p e n d e n t
Ccucar d e n s i t y d e p e n d e n t d e n s i t y i n d e p e n d e n t
- 75 -
I I I .3 .5 1.0
' PROPORTION ESCAPE COVER
- 7 6 -
7.4.1 Clser-\<olf I n t e r a c t i o n s
7 . 4 . 1 . 1 F u n c t i o n a l R e s p o n s e
A major u n d e r l y i n g a s s u m p t i o n i n t h e model is t h a t dee r and wolf form a t i g h t l y c o u p l e d p r e d a t o r - p r i y s y s t e m . I t was t h e r e f o r e h y p o t h e s i z e d t h a t t h e r e is a r a n g e o f deer d e n s i t i e s w i t h i n w h i c h t h e y e a r l y f o o d r e q u i r e m e n t s of an
a d u l t wolf ( a b o u t 8 2 0 kg ) a re almost s o l e l y s a t i s f i e d by d e e r . S e c a u s e o f t h i s a s s u m p t i o n t h e wolf f u n c t i o n a l r e s p o n s e t o f a w n s ( F i g u r e 7 . 2 a ) a n d w o l f f u n c t i o n a l r e s p o n s e to a d u l t s ( F i g u r e 7.2b) had t o be d e v e l o p e d s i m u l t a n e o u s l y . I n d e v e l o p i n g t h e f u n c t i o n a l r e s p o n s e s , f a w n s were assumed to t i e iqh t g kg a n e a d u l t s 5 4 k g . T h e f u n c t i o n a l r e s p o n s e t o a d u l t s ( F i g u r e 7 . 2 ) d e p e n d s c r i t i c a l l y o n t h e f a w n - a d u l t r a t i o . More a d u l t s a r e t a k e n b y p r e d a t o r s as t h e f a w n - a d u l t r a t i o d e c r e a s e s . T h e h y p o t h e s i z e d r e l a t i o n s h i p b e t w e e n fawns k i l l e d p e r w o l f p e r y e a r a n a t h e f a w n d e n s i t y ( F i g u r e 7 . 2 ) is S- shaped . The a s sumpt ions i n t h i s r e s p o n s e form a re :
( a ) w o l v e s p r e y o n a l t e r n a t e sources of p r e y a t low d e n s i t i e s of deer ;
( b ) t h e r e e x i s t s a t h r e s h o l d d e n s i t y a t which deer become a l m o s t t h e sole source of food f o r w o l v e s ; and
( c ) t h e r e e x i s t s a n o t h e r t h r e s h o l d d e n s i t y a t which r a t i o of fawn t o a d u l t b i o m a s s i n t h e w o l f ' s d i e t becomes c o n s t a n t .
T h e t h re sho ld d e n s i t i e s depend on the fawn-adul t r a t i o . F i g u r e s 7 .2a and 7 . 2 b show t h e two f u n c t i o n a l r e s p o n s e s f o r a f a w n - a d u l t r a t i o o f 1 . 0 .
- 7 7 -
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5 IO ADULT DEER / Km2
F i g u r e 7 . 2 F u n c t i o n a l r e s p o n s e s of wolves t o fawn d e n s i t y ( a ) a n d a d u l t d e e r - d e n s i t y (b).
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7 . 4 . 1 . 2 Numerical Responses
I t was hypothesized that wolf abundance would not change i n the deer density range w i t h i n which t h e i r food requirements are pr imari ly sat isf ied by deer and the fawn- a d u l t r a t i o i n wolf k i l l s increases w i t h increasing d e n s i t y (Figure 7 . 2 ) . The concept of deer a d u l t equivalents is simply t h a t s i x fawns are equivalent i n biomass to one adul t deer . I t was assumed t h a t wolves show a positive numerical response due to increased pup surv iva l and immigration when deer densities become-greater than 1 2 deer adult equivalents/km and a negative numerical response due to decreased pup su rv iva l , s t a rva t ion , and emigration a t d e n s i t i e s less than 6 deer adult equivalents/km . Wolves a re assumed t o s h i f t 2
t o a l te rna te p rey sources a t deer d e n s i t i e s less than 6 adult equivalents/km2 b u t not be a b l e t o make up for t h e decrease i n food from deer predation ( F i g u r e 7 . 3 )
2
7 . 4 . 2 E l k - W o l f In te rac t ions
Wolves. were hypothesized to prey primarily on e lk calves . The form of the functional response of wolves t o
. elk (Figure 7 . 4 ) assumes tha t the number taken is constant
2 as long as deer are the primary food source for wolves (i.e., deer densi t ies greater than 6 adult equivalents/km ) .
Iiolves show a l inear functional response to e lk d e n s i t y , xeasured i n e lk adul t equivalents , for deer dens i t ies l e s s than 6 adult equivalents/km2 ( 4 elk calves are approximately equal t o one e l k a d u l t ) .
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- 79 -
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Figure 7 . 3 Numerical response of wolves t o deer d e n s i t y .
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ELK ADULT EQUIVALENTS /Km2
F i g u r e 7 . 4 F u n c t i o n a l response of wolves to elk d e n s i t y .
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7.5 Bear Predation
Bears prey only on fawns and only i n t h e summer i n t h e model. Bears are hypothesized to have n o numerical response to p rey dens i ty ; a constant 6 bears i n t h e watershed is assumed. The bear functional response to fawn dens i ty (Figure 7 . 5 ) is l inear up t o 9 k i l l s per bear per year a t 1 0 fawns/km2 and c o n s t a n t a t 9 k i l l s w i t h greater prey dens i t i e s .
7 . 6 Couqar Predation
Cougars are hypothesized to show n o numerical response to e i the r dee r o r e lk .
7 . 6 . 1 Deer-Couaar In te rac t ions
The mode-l assumes a constant 2 cougar and 2 k i t t e n s and t r e a t s them as 3 cougar adult equivalents. The cougar functional response to deer density (Figure 7 . 6 ) is assumed l inear up t o a threshold of 50 deer k i l l s per cougar per year a t 1 0 deer/km2 and c o n s t a n t a t 50 k i l l s w i t h g rea te r prey densi t ies . The fawn-adult k i l l r a t i o is assumed t o be 4 : l .
7 . 6 . 2 Elk-Cougar In te rac t ions
Cougars are assumed t o have a density-independent functional response to elk. T h i s implies they have n o handling time when preying on e lk . The model cu r ren t ly assumes each cougar k i l l s 1 . 6 calves and 0 .4 adults per year.
- 8 2 . -
F i g u r e 7 . 5
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F i g u r e 7 . 6 F u n c t i o n a l response of couga r t o deer d e n s i t y .
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7.7 Huntinq
T h e m o d e l d o e s n o t e x p l i c i t l y c o n s i d e r t h e d y n a m i c s of h u n t i n g , b u t t h e h a r v e s t r a t e f u n c t i o n i m p l i c i t l y i n c l u d e s i n c r e a s e s or d e c r e a s e s i n h u n t i n g e f f o r t i n r e s p o n s e t o d e e r d e n s i t y ( F i g u r e 7 . 7 ) . T h e d e c l i n e i n t h e h a r v e s t r a t e a s d e e r p o p u l a t i o n s i n c r e a s e from low d e n s i t i e s is b a s e d o n t h e a s s u m p t i o n t h a t t h e r e is a g r o u p o f h u n t e r s who a lways k i l l t h e same number of d e e r o v e r a r a n g e of low d e e r d e n s i t i e s . Less e f f i c i e n t h u n t e r s become more s u c c e s s f u l a t h i g h e r d e e r d e n s i t i e s u n t i l a maximum h a r v e s t r a t e is reached . The t o t a l number o f deer t aken b y h u n t e r s is a l l o c a t e d b y a g e a n d s e x u s i n g t h e f o l l o w i n g p r o p o r t i o n s :
f a w n y e a r l i n g s a d u l t ( 2 + )
Ma l e .os .50 .25
Female .05 .075 .075 I
The e l k h u n t was n o t m o d e l l e d as i t was n o t b e l i e v e d t o b e s i g n i f i c a n t b e c a u s e of t h e c u r r e n t permit s y s t e m for l i c e n s i n g e l k h u n t e r s .
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F i g u r e 7 . 7 Hunter harves t ra tes as a function Of deer . dens i t y .
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8 . 0 RESULTS OF THE WORKSHOP
8 . 1 The Conceptual Model
Once t h e s u b m o d e l s were c o n s t r u c t e d t h e y were l i n k e d t o g e t h e r u s i n g t h e i n f o r m a t i o n t r a n s f e r s i d e n t i f i e d i n t h e l o o k i n g o u t w a r d e x e r c i s e ( S e c t i o n 2 . 6 ) . The complete model is a complex of n u m e r o u s r e l a t i o n s h i p s w i t h i n a n d b e t w e e n s u b m o d e l s b u t a c o m p r e s s i o n a n d s i m p l i f i c a t i o n o f t h e c o m p l e t e m o d e l ( F i g u r e 8 .1 ) g i v e s a b r o a d u n d e r s t a n d i n g of t h e causal r e l a t i o n s h i p s b e t w e e n c o m p o n e n t s o f t h e model. Many of t h e processes o u t l i n e d i n t h e c o n c e p t u a l model a.re i n f l u e n c e d b y t h e p h y s i c a l c h a r a c t e r i s t i c s o f t h e , r e g i o n s u c h as s u b z o n e , m o i s t u r e t y p e , a n d aspect and many of t h e processes, s u c h a s s n o w f a l l a n d food p r e f e r e n c e s , v a r y s e a s o n a l l y .
Not a l l l i n k s d e f i n e d i n t h e l o o k i n g o u t w a r d e x e r c i s e w e r e i n c l u d e d i n t h e model b u i l t a t t h e w o r k s h o p . T h e s e o m i s s i o n s h a v e b e e n n o t e d i n t h e p r e v i o u s s u b m o d e l d e s c r i p - t i o n s a n d , w i l l b e d i s c u s s e d i n S e c t i o n s 8 . 2 , 8 . 4 , and 9 .
8 . 2 C o n c e p t u a l a n d I n f o r m a t i o n Needs
The a c t u a l p r o c e s s o f b u i l d i n g a model of a b i o l o g i c a l s y s t e n a l w a y s r e v e a l s d e f i c i e n c i e s i n c o n c e p t u a l i z a t i o n a n d u n d e r s t a n d i n g o f s y s t e m p r o c e s s e s a n d d y n a m i c s . I n t h e c o n t e x t of t h e o b j e c t i v e s o f t h e w o r k s h o p , i d e n t i f i c a t i o n o f t h e s e d e f i c i e n c i e s is c r i t i c a l l y i m p o r t a n t i n d e v e l o p i n g a r e s e a r c h p l a n for I W I F R . T h i s s e c t i o n w i l l b e d e v o t e d t o a formal i d e n t i f i c a t i o n of t h e s e c o n c e p t u a l a n d i n f o r m a t i o n n e e d s . S i n c e most of t h e s e needs were u n c o v e r e d d u r i n g t h e s u b g r o u p d i s c u s s i o n s t h e y will b e c a t e g o r i z e d a c c o r d - i n g t o the submode l w i th wh ich t hey a re most c l o s e l y a s s o c i a t e d .
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Section 9 will define these conceptual and information needs as research hypotheses while emphasizing the importance of considering their interdisciplinary nature.
8.2.1 Vegetation
8.2.1.1 Competition
There was assumed to be no competition among understory species. This is clearly unrealistic. However, it may not be necessary to explicitly consider inter-specific competition among plants to evaluate the impact of changes in vegetation on deer and elk. A more detailed consideration of the effect of plant competition in the model on deer and elk populations should be pursued before the importance of competition can be assessed.
8.2.1.2 Forage Availability
The proportion of vegetation biomass that is available as food is presently assumed to be 10% of the standing crop of perennials and annuals and 13% of the standing crop of arboreal lichens. This is an oversimplification: the actual proportion will be species-dependent as well as a function of biomass and history of browsing (Noy-Meir, 1975). Yore accurate predictions of available food are necessary to examine mors carefully any hypothesis of food limitation on deer and elk.
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8.2.1,3 Effec ts of S i lv i cu l tu ra l P rac t i ces
Again, i f hab i t a t is a c ruc ia l l imi t ing f ac to r t o wi ld l i fe popula t ions , a ca re fu l review should be done of t h e e f f e c t s of s i l v i c u l t u r a l a c t i v ' i t i e s on hab i t a t . P re sen t ly , s i l v i cu l tu ra l p rac t i ces a r e assumed t o simply change the biomass of vegetation. Long term e f f e c t s a r e conceptualized i n a crude and non-dynamic fashion. T h i s
conceptual gap is cent ra l to unders tanding e f fec ts of second-growth management on wi ld l i f e and should be invest i - gated.
8 . 2 . 1 . 4 Alternate Representation of Vegetation
Twelve vegetat ion types are present ly s imulated. The s t a t i c d e s c r i p t i o n of t h e vegetation submodel was time- consuming and prevented adequate discussion of vegetation growth, competition, and responses to t imber growth, si lvi- cu l tu ra l p rac t i ces and browsing, a l l p o t e n t i a l l y c r u c i a l research questions for the IWIFR Program. Important conceptual deficiencies could be better defined i f an a l te rna te s t ruc ture could be derived for vegetation dynamics.
A simplification of the vegetation to 3-4 types would.
improve understanding of t h e in te rac t ions between vegetation and wi ld l i f e . One possible aggregation of species would be into grasses , forbs , shrubs, and l ichen: cer ta in ly the f i r s t t h r e e may have s imi la r growth responses t o canopy closure (XcConne11 and S m i t h , 1 9 7 0 ) . Doubtless several o ther b io logica l ly rea l i s t ic aggrega t ions a re a l so conceivabls.
- 89 - Such a compression of t h e vegetation would make i t
poss ib l e t o examine c l e a r l y t h e c r i t i c a l i n t e r a c t i o n s , between e lk and deer browsing and forage dynamics, and help def ine bet ter experiments to tes t sensi t ive hypotheses concerning those interactions.
8 . 2 . 2 Timber
A better conceptual framework for predict ing s tand dynamics can ce r t a in ly be constructed. However, the c r i t e r i o n t o use i n deciding what conceptual and infor- mation gaps e x i s t i n the present framework is t h a t any improvements to conceptual understanding should enhance the ab i l i t y t o p red ic t w i ld l i f e r e sponses t o fo re s t s t ruc tu re , no t t he ab i l i t y t o p red ic t commerical timber supply. Therefore, the conceptual and information gaps i n t h e wood submodel discussed below refer only to those involving t imber- wi ld l i fe in te rac t ions .
8 . 2 . 2 . 1 Ef fec ts of Animal Browsing
8 . 2 . 2 . 1 . 1 Mortal i ty
Browsing is presently hypothesized t o a f f e c t stem mortal i ty and growth. The l e v e l of mortal i ty is assumed t o have a 1:l re la t ionship w i t h the l eve l of foliage consumption by wildl i fe . Al ternate hypotheses (Figure 8 .2) may r e f l e c t a more real is t ic biological representat ion. There is cer ta inly evidence that the re la t ionship is nonl inear for other herbivores w i t h similar feeding patterns (Horn, 1 9 7 1 ) . The form of the re la t ionship is also l ikely dependent on t r ee s i ze . I t may be Type 3 for very small trees, suggesting extreme s e n s i t i v i t y t o f o l i a g e removal, and changes t o
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Type 1 a s the tree matures, s u g g e s t i n g decreas ing sens i t iv i ty t o f o l i a g e removal w i t h increasing s ize .
8 . 2 . 2 . 1 . 2 Growth
Browsing is present ly assumed to on ly a f f ec t growth by re ta rd ing the ra te of stand development. Furthermore, removal of conifer fol iage is assumed to no t ever ha l t stand development. Therefore browsing cannot permanently a l t e r t he cha rac t e r i s t i c s o f a t r ee . An a l ternate hypothesis is t h a t browsing can permanently a l t e r t h e c h a r a c t e r i s t i c s of a t ree (F igure 8 . 3 ) . Again, regarding the wildlife as
grazers of photosynthetic material , the permanent damage hypothesis is c e r t a i n l y a v iab le a l te rna t ive (Shepherd , e t a l . , 1 9 7 9 ) .
The two conceptual problems outlined above a re c ruc ia l because wildlife are hypothesized to respond to a number of stand parameters such as density, height, and crown r a t i o (Sect ions 5 , and 6 ) .
8 . 2 . 2 . 2 Direct Effects of Wildlife
The e f f e c t s of trampling and general physical disruption of young timber is presently not simulated. These processes probably affect the mortali ty of timber rather than i t ' s growth. Trampling may break young stems or permanently bend them over, thereby removing them from the future s tock of commercially valuable timber. Again, t h i s impact i s probably related t o bo th t ree s ize and animal density,
- 91 -
I
5 W I- Cn
Figure E.2 Alternate hypotheses about stand mortality response t o animal browsing. ( 2 ) is hypothesis presently embedded i n model; (1) and ( 3 ) are a l t e rna t ives .
f
Browsing STAND AGE "+
Fisi;:t .:.3 Alternate hypotheses about long-term effects of animal browsing. (1) represents hypothesis present ly embedded i n model; browsing simply retards develop- ment, no t the t ree charac te r i s t ics ; ( 2 ) is an a l t e r n a t e ; browsing permanently changes t r e e c h a r a c t e r i s t i c s .
8 .2 .2 .3 E f f e c t s of S i l v i c u l t u r a l Practices
Stem r e m o v a l b y j u v e n i l e s p a c i n g : or commercial t h i n n i n g i s p r e s e n t l y a s s u m e d t o o n l y a f f e c t c r o w n closure. An i m p l i c a t i o n of t h i s h y p o t h e s i s is t h a t t r ee d i m e n s i o n s a t a g i v e n a g e a r e t h e same for a n y s t a n d d e n s i t y . O t h e r f o r e s t g r o w t h s i m u l a t o r s ( S t a g e , 1 9 7 3 ; M i t c h e l l , 1 9 7 2 ) c o n s i d e r t h e e f f e c t o f s t a n d d e n s i t y o n v a r i a b l e s t h a t h a v e b e e n i d e n t i f i e d a s i m p o r t a n t i n t h e d y n a m i c s of e l k and dee r , s u c h as h e i g h t a n d c r o w n r a t io . T h i s is a c o n c e p t u a l g a p t h a t w i l l have t o be f i l l e d t o i n c r e a s e u n d e r s t a n d i n g of f o r e s t r y - w i l d l i f e i n t e r a c t i o n s .
8 . 2 . 2 . 4 F o l i a g e P r o d u c t i o n
F o l i a g e p r o d u c t i o n is assumed t o be a f u n c t i o n o f c r o w n l e n g t h . Nore r e a l i s t i c a l l y , i t is p r o b a b l y a f u n c t i o n of c r o w n v o l u m e ( M i t c h e l l , 1 9 7 5 ) , or some o t h e r c o m b i n a t i o n of t r e e a t t r i b u t e s ( K i m m i n s , p e r s . comm.). T h i s i n f o r m a t i o n gap i s c r u c i a l because b rows ing by e l k a n d d e e r is t i g h t l y c o u p l e d t o t h e r e l a t i v e biomasses of p l a n t s ( S e c t i o n s 5
and 6 ) .
8 . 2 . 2 . 5 I n f l u e n c e o f O t h e r V e g e t a t i o n o n T i m b e r
Compe t i t i on be tween timber and other v e g e t a t i o n is p r e s e n t l y h y p o t h e s i z e d n o t t o o c c u r , or n o t t o be important. T h i s i m p l i e s t h a t t h e s t a n d c a n a l w a y s o u t - c o m p e t e o t h e r v e g e t a t i o n a n d r e d u c e i t s biomass b y s h a d i n g ( S e c t i o n 3 . 3 ) . ' a r t i c i p a n t s s t a t e d t h a t t h i s was n o t a l w a y s t h e case and t h a t s u f f i c i e n t l y d e n s e v e g e t a t i o n c a n sometimes s e v e r e l y r e t a r d or c o n p l e t e l y h a l t g r o w t h of commercial t i m b e r s p e c i e s .
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The ques t ion to be answered is: what is the inf luence of vegetation on the development of commercial timber? I t
is a conceptual gap w h i c h m u s t be f i l l e d i f understanding of wi ld l i fe responses to fores t s t ruc ture a re to be improved.
8 .2 .3 Deer
8 . 2 . 3 . 1 Snow
8.2.3.1.1 Snow Intercept ion
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The current vers ion of the model assumes t h a t h e i g h t does not affect a t r e e ' s snow in te rcept ion capabi l i t i es provided the tree i s greater than 2 m t a l l . An a l t e r n a t e h y p o t h e s i s is t h a t l a rger t rees will in te rcept more snow, qiven the same degree of crown closure i n t h e s tand.
Second, t h e assumption that 1 0 0 % crown closure w i l l r e s u l t i n complete snow in te rcept ion , regard less of the amount of snow reaching the canopy, is u n r e a l i s t i c , a t least for very heavy snowfalls.
Both of these assumptions effectively imply t h a t s i t e s w i t h r e l a t i v e l y young t r e e s w i t h dense canopies provide excellent winter range. T h i s does n o t match w i t h the perceptions of some workshop pa r t i c ipan t s a s to what cons t i t u t e s gocd winter range.
8 . 2 . 3 . 1 . 2 Food Covered by Snow
The l inear re la t ionship between the depth of snow on the ground and the proportion of food of a par t icular type l e f t uncovered impl ic i t ly assumes t h a t food is d i s t r ibu ted uniformly over the height of the plant . For n o s t perennials
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t h i s is u n r e a s o n a b l e s i n c e much o f t h e lower p a r t s of t h e s e p l a n t s a r e woody. For most food t y p e s a v a i l a b l e i n w i n t e r t h i s h y p o t h e s i s i m p l i e s t h a t more food w i l l b e c o v e r e d a t a p a r t i c u l a r d e p t h of snow than wou ld ac tua l ly be e x p e c t e d .
T h e s e n s i t i v i t y of t h e model t o c h a n g e s i n t h i s a s s u m p t i o n h a s n o t b e e n e x p l o r e d . S u c h a n a n a l y s i s would be
w o r t h w h i l e b e f o r e a l l o c a t i n g s u b s t a n t i a l e f f o r t t o s t u d y i n g f o l i a g e h e i g h t d i s t r i b u t i o n s f o r a v a r i e t y of f o o d s p e c i e s .
8 . 2 . 3 . 1 . 3 E f f e c t s o f S n o w f a l l on L i c h e n A v a i l a b i l i t y
T h i s i n t e r a c t i o n p o s e d c o n s i d e r a b l e c o n c e p t u a l d i f f i c u l t i e s d u e t o t h e a b s e n c e of a p r e c i s e t e m p o r a l s e q u e n c e of s n o w f a l l s i n w i n t e r . T h e l i n e a r r e l a t i o n s h i p b e t w e e n s n o w f a l l a n d l i c h e n a v a i l a b i l i t y may b e r e a s o n a b l e a s a f i r s t a p p r o x i m a t i o n b u t t h e d u r a t i o n of t h e h e a v y s n o w f a l l p e r i o d may b e e q u a l l y , i f n o t more i m p o r t a n t , i n d e t e r m i n i n g s e a s o n a l l i c h e n a v a i l a b i l i t y . For example , i t may be more r e a s o n a b l e t o assume t h a t d u r i n g t h e h e a v y s n o w f a l l p e r i o d , snowfa l l s occur f r e q u e n t l y e n o u g h t o e f f e c t i v e l y reduce l i c h e n a v a i l a b i l i t y t o zero w h i l e low s n o w f a l l p e r i o d s may i m p l y s n o w f a l l s i n f r e q u e n t e n o u g h t o have n o i m p a c t o n l i c h e n
s u p p l y
8 . 2 . 3 . 2 Novemen t
The bas ic c o n c e p t u a l q u e s t i o n r e g a r d i n g movement concerns how d e e r s e l ec t h a b i t a t . C o n s i d e r a b l e e f f o r t was d e v o t e d t o c o n c e p t u a l i z i n g t h i s s e l e c t i o n p r o c e s s . The p rob lems faced i n p e r f o r m i n g t h i s c o n c e p t u a l i z a t i o n c a n be d i v i d e d i n t o t h r e e c lasses : t i m i n g of d e c i s i o n s , se lec t ion
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c r i t e r i a and s p a t i a l e x t e n t of concern.
F i r s t , i t was assumed that the animals made the i r movement d e c i s i o n a t t h e s t a r t of each season. T h i s is probably reasonable for spring and summer, since deer appear to demonst ra te fa i r ly h i g h f i d e l i t y t o p a r t i c u l a r r e g i o n s during those times of the year. However, i n winter t h i s
assumption (as discussed i n Section 5.3.1) implies that the animals select habi ta ts before knowing how severe the winter w i l l be . I n other words, deer distributions are not affected by snowfall. More information is needed to decide whether deer do actually move i n response t o changes i n snowfall .
Second, the select ion cr i ter ia w h i c h the deer use to eva lua te the po ten t ia l of d i f f e ren t a r eas a s hab i t a t may be too simple. For example t h e escape cover criterion does not include debris or understory vegetation as components, while the feeding habi ta t cr i ter ion assumes t h a t a l l food types are equally important i n determining a s i t e ' s v a l u e , i r respec t ive of deer preferences. I n addi t ion the method of weighting and aggregat ing the cr i ter ion for each s i te may be conceptually inadequate. I t may be more reasonable when calculat ing the value of a four-s i te block to consider on ly t he s i t e w i t h the highest value for each cri terion. For example, i f a s ingle s i te comprises excel lent winter range b u t is lumped w i t h t h r e e o t h e r s i t e s having poor winter rar,ge ( i . e . , no t rees greater than 2 m ) , t h e ove ra l l winter rar,ge value of that block m i g h t be u n r e a l i s t i c a l l y 1 ow .
T h i s problem is l i nked t o t h e t h i r d c l a s s of conceptual problems related to deer movement. Is a block of f o u r s i t e s ( t o t a l a r e a - 3 2 0 ha) a reasonable representation of the "sphere of operation" of a deer during an e n t i r e season, or do deer consider an area larger (or smaller) than
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t h i s i n evaluating a p a r t i c u l a r s i t e ? The observed relatively h i g h f i d e l i t y of deer to a p a r t i c u l a r s i t e w i t h i n a season suggests that one need not consider larger areas. However, t h i s question needs to be evaluated more carefu l ly s ince it has important implications to the overall conceptualization of t h e deer model.
8 .2 .3 .3 Feeding
The quan t i t i e s used to convert to ta l annual new growth in to seasonal ca lor ic abundance of each food type (Table 5 . 3 ) deserve more attention than they received during the workshop. Some values were simply guessed a t due t o time cons t r a in t s and should be ca re fu l ly reviewed to ensure their accuracy.
The l i s t of re la t ive p references for the 1 4 food types (Table 5 . 4 ) was developed from information on the incidence of these food types i n deer rumen. S u c h information clearly r e f l ec t s t he i n t e rac t ion between preference and a v a i l a b i l i t y of food and w i l l be badly biased unless a l l food types were equally abundant when the deer were feeding.
True preferences are difficult to establish without
careful experimentation. However, knowledge of such preferences and how they d i f fe r among food types is c e n t r a l i n determin- i n g the level of d e t a i l a t which vegetation m u s t be considered to understand the consequences of deer-food interactions (Section 8 . 2 . 1 . 4 ) .
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8 . 2 . 3 . 4 S u r v i v a l a n d R e p r o d u c t i o n
T h e p o p u l a t i o n d y n a m i c s of d e e r i n t h e m o d e l a r e e x t r e m e l y s e n s i t i v e t o c h a n g e s i n t h e e n e r g e t i c s - s u r v i v a l a n d e n e r g e t i c s - n a t a l i t y r e l a t i o n s h i p s d e s c r i b e d i n S e c t i o n s 5.4 and 5.5. A l l o t h e r p r o c e s s e s d e s c r i b e d i n S e c t i o n 5 a f f e c t d e e r p o p u l a t i o n s o n l y t h r o u g h these two r e l a t i o n s h i p s . Much a t t e n t i o n s h o u l d b e f o c u s s e d o n c a r e f u l l y a s s e s s i n g t h e h y p o t h e s e s t h a t w e n t i n t o d e v e l o p i n g t h e s e r e l a t i o n s h i p s a s well as t h e a c c u r a c y o f t h e i r p a r a m e t e r s . T h e s e n s i t i v i t y of deer s u r v i v a l t o w i n t e r e n e r g y d e f i c i t s is of p a r t i c u l a r impor t ance .
8 .2 .4 E l k
8.2.4.1 Escape Cover
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A c r i t i c a l a s s u m p t i o n i n t h e h y p o t h e s i z e d i n f l u e n c e of e s c a p e c o v e r is t h a t e l k r e q u i r e e s c a p e c o v e r t o be p r e s e n t b e f o r e t h e y w i l l f o r a g e i n a n area. An a l t e r n a t e , e q u a l l y v i a b l e h y p o t h e s i s is t h a t e l k p r e f e r a reas w i t h a d e q u a t e e s c a p e c o v e r b u t w i l l use any area t h a t h a s a d e q u a t e f o r a g e i f f o r a g e i s l i m i t i n g . T h e s e are two e x t r e m e h y p o t h e s e s , a n d c o m b i n a t i o n s of them a r e e q u a l l y f e a s i b l e . E l k may c o n t i n u a l l y t r a d e o f f b e t w e e n t h e v a l u e o f c o v e r a n d f o r a g e .
A more b a s i c c o n s i d e r a t i o n is t h e c o n c e p t u a l i z a t i o n of e s c a p e c o v e r a s a f u n c t i o n o f t i m b e r d e n s i t y a n d h e i g h t . T h i s h y p o t h e s i s i m p l i e s t h a t u n d e r s t o r y v e g e t a t i o n and d e b r i s d o n o t c o n t r i b u t e t o e s c a p e c o v e r . T h i c k undergrowth of h e r b a c e o u s v e g e t a t i o n or h i g h d e b r i s l e v e l s may i n f a c t p r o v i d e good c o v e r f o r e l k , e s p e c i a l l y t h e y o u n g e r , s m a l l e r a g e - c l a s s e s . Thomas e t a l , ( 1 9 7 9 ) have found d e b r i s t o be an impor t an t componen t o f e scape cove r .
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The a t t r i b u t e s of t h e t i m b e r i n a s t a n d which were h y p o t h e s i z e d t o d e f i n e e s c a p e c o v e r may be improper . I t i s d i f f i c u l t t o i m a g i n e , f o r e x a m p l e , t h a t 8 0 35m t a l l t r e e s / h a p r o v i d e e q u a l l y g o o d e s c a p e c o v e r a s 1000 2.5m t a l l t rees /ha .
T h e c o n c e p t u a l i z a t i o n of e s c a p e c o v e r , b o t h i t s d e f i n i t i o n a n d i t s i m p o r t a n c e t o e l k i n s e l e c t i n g h a b i t a t , m u s t b e c r i t i c a l l y e x a m i n e d .
8 . 2 . 4 . 2 Food A v a i l a b i l i t y
I t was h y p o t h e s i z e d t h a t e l k u s e l e v e l s o f a v a i l a b l e f o o d e n e r g y t o p a r t i a l l y d e t e r m i n e movement . Avai lab le e n e r g y was assumed t o i n c l u d e t h e c o n c e p t s o f f o o d p r e f e r e n c e a n d s e a s o n a l f o r a g i n g h a b i t a t s . I t embodied t h e b i a s t h a t e l k p r e f e r e n c e s , a s m e a s u r e d b y t h e i r s e l e c t i o n of foods a n d e n v i r o n m e n t s , r e f l e c t s t he i r r e q u i r e m e n t s , or i n g r a i n e d h a b i t s . A l t e r n a t i v e l y , a s i n t h e e s c a p e c o v e r h y p o t h e s e s , e l k may o n l y b e d o i n g w h a t t h e y p r e f e r t o do. N e c e s s i t y n a y force r a d i c a l c h a n g e s i n t h e i r d i e t s b u t n o t i n c u r a n y a p p r e c i a b l e d e t r i m e n t a l e f f e c t s .
V e r y s i m p l y , t h e c o n c e p t t h a t food a v a i l a b i l i t y is
c r i t i c a l i n d e t e r m i n i n g elk movement and d i s t r i b u t i o n p a t t e r n s n u s t b e c l o s e l y e x a m i n e d .
S . 2 . 4 . 3 S u r v i v o r s h i p a n d F e c u n d i t y
T h e s u r v i v o r s h i p a n d f e c u n d i t y r e l a t i o n s ( F i g u r e 6.4) were m e a n t t o c a p t u r e t h e h y p o t h e s i s t h a t f o o d d e n s i t i e s c o u l d a d v e r s e l y a f f e c t e l k p o p u l a t i o n d y n a m i c s . T h e h y p o t h e s i s
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is that forage density, integrated over a r e l a t ive ly l a rge a rea , is an appropriate index of forage value. An a l t e r n a t e hypothesis is t h a t t h e d i s t r i b u t i o n of food i n the environment may be t h e c r i t i c a l f a c t o r . For example, a pocket of dense, h i g h qual i ty forage may be f a r more va luable to e lk i n terms of survivorship and fecundity, than a l a r g e t o t a l biomass'of low densi ty , evenly dis t r ibuted forage.
8 . 2 . 4 . 4 Emigration
Alternate hypotheses about immigration and emigration could dramatical ly affect p tedict ions of the dynamics of an elk population. A t present , an a rb i t ra ry car ry ing capac i ty is used to prevent the buildup of a large densi ty .of e lk i n the watershed. Total population density is assumed t o be the only determinant of e l k emigration from t h e watershed. B u t , r e l a t i v e food ava i l ab i l i t y pe r e lk may be a more biological ly real is t ic indicator than s imple populat ion s ize . Unfor tuna te ly , exper iments to t es t the sens i t iv i ty of t h i s hypothesis would be expensive and time consuming.
8 . 2 . 5 Predation and H u n t i n q
8 . 2 . 5 . 1 Seasonal Distribution of Predation
Seasonal predation is calculated by a l locat ing annual preda t ion ra tes to t h e three seasons u s i n g the f ixed proportions i n Table 7 . 1 .
The weakness of t h i s approach is that the annual ra te is calculated based on the prey population size immediately a f t e r fawning and calving seasons. The seasonal ra tes a re not sens i t ive t o the actual seasonal populat ion s izes .
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If some process other than predation reduces a prey population, the model does not adjust the amount of predation t o r e f l e c t the change because the all-seasonal rates are based on the populat ion s ize a t the beginning of the summer. An improve- ment i n understanding w i l l be gained by developing re la t ionships tha t p red ic t seasonal p reda t ion ra tes from seasonal prey densit ies. .
8 . 2 . 5 . 2 Functional Responses
A l l of t h e functional responses discussed i n Section 7 .0
were "best guess" hypotheses. Before much f a i t h can be put i n these hypotheses, data needs to be gathered i n t h e f i e l d or re t r ieved from the ava i lab le l i t e ra ture . Both the assump- t ions about density dependence or independence and the specific parameters were not based on strong evidence.
8 . 2 . 5 . 3 Numerical Responses
A l l of the numerical responses discussed i n Section 7 were "best guess'' hypotheses. Before much f a i t h can be p u t i n these hypotheses, data needs to be gathered i n the f ie ld o r re t r ieved from the ava i l ab le l i t e r a tu re . Both the assumptions about density dependence or independence and the specific parameters were not based on strong evidence.
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8.2.5.4 Wolf P r e d a t i o n
8 . 2 . 5 . 4 . 1 F u n c t i o n a l R e s p o n s e s t,o Deer
T h e h y p o t h e s i s u n d e r l y i n g t h e f u n c t i o n a l r e s p o n s e s t o f a w n a n d a d u l t d e n s i t i e s ( F i g u r e 7 . 1 ) are q u i t e c o m p l e x . T h e c o m p l e x n a t u r e of t h e s e h y p o t h e s e s c a n b e i l l u s t r a t e d by c o m p a r i s o n w i t h a s e t o f s i m p l e r h y p o t h e s e s ( F i g u r e 8 . 4 ) . T h e s e s i m p l e r h y p o t h e s e s s t a t e t h a t a t h i g h d e n s i t i e s o f b o t h f a w n s a n d a d u l t s t h e p r e d a t o r s become s a t u r a t e d a n d t h e r a t i o of fawns t o a d u l t s i n t h e t o t a l k i l l b e c o m e s c o n s t a n t . A t lower d e n s i t i e s t h e p r e d a t o r s c a n n o t s a t i s f y t h e i r r e q u i r e m e n t s f r o m t h e c o m b i n e d s o u r c e s of f a w n s a n d a d u l t s a n d b o t h f u n c t i o n a l r e s p o n s e s d e c l i n e as d e n s i t i e s d e c l i n e . T h e a c t u a l s l o p e s of t h e c u r v e d e p e n d o n t h e f a w n t o a d u l t r a t i o i n t h e p o p u l a t i o n s . T h e s o l i d l i n e ' i n F i g u r e 8 . 4 r e p r e s e n t s a h i g h e r f a w n - a d u l t r a t i o t h a n t h e do t t ed l i n e .
To g e n e r a t e t h e f u n c t i o n a l r e s p o n s e t o a d u l t s shown i n F i g u r e 7 . l b from t h e r e l a t i o n s h i p shown i n F i g u r e C.4b i t was n e c e s s a r y t o assume t h a t t h e r e e x i s t s a r a n g e o f d e n s i t i e s where a decrease i n t h e d e n s i t y of b o t h a d u l t s a n d f a w n s w i l l r e s u l t i n a r e d u c t i o n i n p r e d a t i o n o n f a w n s w h i c h w i l l be compensa ted fo r b y i n c r e a s e d p r e d a t i o n on a d u l t s . T h i s a s s u m p t i o n is m a n i f e s t e d as t h e humped r e s p o n s e o f F i g u r e 7 . 2 b - T h e e x a c t m e c h a n i s m t h a t w o u l d g e n e r a t e s u c h a r e s p o n s e is u n c l e a r .
T o g e n e r a t e t h e S - s h a p e d f u n c t i o n a l response t o fawns shown i n F i g u r e 7 . 2 a from F i g u r e 8 . 4 b r i t was n e c e s s a r y t o assume a s w i t c h f rom deer t o e l k a n d o t h e r f o o d s o u r c e s a t low d e n s i t i e s . I t was h y p o t h e s i z e d t h a t a t e n d e n c y t o w a r d s l a r g e r p a c k s wou ld b e n e c e s s a r y t o i n c r e a s e p r e d a t i o n p r e s s u r e on e l k .
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Fiqure G. 4
32
24
16
8
0 I 5 IO
FAWN / K m 2
0 1
~~
I 5 ' IO ADULT DEER / Km2
Alternate hypotheses about funct ional responses of wolves to deer . The so l id l ine represents a h i g h fawn-adult r a t i o , th,e dotted a Low fawn-adult r a t i o .
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8.2.5.4.2 Functional Response t o E l k
Wolves a re assumed t o feed on elk only when deer dens i t i e s a r e low. T h i s hypothesis was based on l i t t l e understanding and m u s t be reconsidered.
8.2.5.4.3 Numerical Response of Wolves t o Deer
The numerical response (Figure 7 . 3 ) is another complex hypothesis that is b e s t i l l u s t r a t e d by pos tu la t ing a simpler alternate hypothesis (Figure 8.5). The simple hypothesis s t a t e s t ha t a s t he dens i ty of deer increases , t h e dens i ty of wolves increases proport ional ly . To generate the numerical response (Figure 7.3) from the 'a l ternate hypothesis (Figure 8.5), it was necessary to hypothesize the existence of a range of deer densi t ies where the wolves would show no response to increasing deer density. The exact mechanism for lack of response is unclear. I n the model, i t is d i rec t ly re la ted to the assumpt ion tha t there ex is t s a range of deer density where the wolves' food requirements a re met by a d i e t composed e n t i r e l y of deer. Whether s u c h a range exis ts is an open question.
8.2.5.5 Bear Predation
Bear predation was simply represented and the hypothesized re la t ionships were best guesses. Bears may prey on animals other t h a n fawns and a t times of the year other than summer. The present funct ional form for bear predation and the k i n d s of wildlife bear prey upon m u s t be c lose ly examined.
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cu E Y
.I 50
.075
0
DEER A0UL.T EQUIVALENTS / Km2
F i g u r e 8 . 5 A l t e r n a t e h y p o t h e s i s a b o u t t h e n u m e r i c a l r e s p o n s e of wo lves t o d e e r .
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8.2.5.6 Cougar Predation
The conceptual gaps i n the process of cougar predation are the same as those for bear predation. T h i s oversimplif i - ca t ion i n the case of cougars is a major weakness because of the magnitude of cougar predation on deer. The en t i r e a r ea of cougar predation represents significant conceptual gaps i n understanding.
8.2.5.7 Predator-Predator Interactions
The model assumes tha t there is no in t e rac t ion between predators. While some concern was raised over the possible in t e rac t ions between wolves and cougars, there is l i t t l e evidence to support hypotheses about s u c h i n t e rac t ions . Information on t h i s area of the predator question is completely absent; i ts importance is unknown.
8.2.5.8 Hunting
The dynamics of hunters were not expl ic i t ly considered i n the h u n t i n g r e l a t ionsh ip . The harves t ra te re la t ionship developed (Figure 7.7) made gross assumptions about the behavioural responses of hunters to deer densi ty . T h i s re la t ionship represents a best guess hypothesis and m u s t be reconsidered.
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8.2.5.9 Escape Cover
The concept of escape cover is poorly defined and t h e e f f e c t of escape cover on the vu lnerabi l i ty of p rey t o predation and hunting is poorly conceptualized. The index of vu lne rab i l i t y used i n t h e model is based on an aggregate measure of t h e proportion of the area that is sui table escape cover. T h i s index affects the numb.er of animals that are ava i lab le to p reda tors .
The Holling (1959) disc equation offers i n s i g h t i n t o how vulnerabi l i ty may af fec t p reda t ion :
T a No t A ( N o ) = 1 + aTh No
where No = prey densi ty ,
A ( N o ) = number of at tacks per predator ,
T t = t o t a l time predator and prey are exposed,
a = r a t e of successful search, and
Th = time spent handling (pursuing, capturing and eating) each prey.
Changes i n escape cover can modify the functional response (Figure 8 . 6 ) i n three ways.
1.
2 .
3 .
The prey density (No) can be def ined as vulnerable prey as was done ' in the model;
the ra te of successful search (a) can be modified t o r e f l e c t t h e d i f f i c u l t y a predator has i n f inding prey: or
the handling time (Th) can be modified to r e f l e c t t h e d i f f i c u l t y a predator has i n pursuing and capturing prey.
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No PREY DENSITY
Figure 8.6 Predator functional response to prey density as expressed by the disc equation.
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Changes i n prey density (No) and i n t he r a t e of successful search (a) will both modify the slope of the funct ional response a t low prey dens i t ies and changes i n handling time ( T h ) w i l l a f f e c t t h e maximum r a t e s of a t tack a s well as t h e slope.
A detailed examination of t h e specif ic predator-prey systems i s needed to carefully formulate hypotheses about t h e e f f e c t of escape cover on t h e functional responses of predators.
8 . 2 . 5 . 1 0 Predator Population Dynamics
A major m i s s i n g piece of t h e puzzle is an understanding of the population dynamics of predators and hunters. T o
f u l l y understand t h e predator-prey systems it may be necessary t o include the population processes ( b i r t h , mor ta l i ty , reproduction) for the predators. However, i t is n o t c l ea r that the behaviour of t h e model would be q u a l i t a t i v e l y different or that the research planning object ives would be bet ter served by i n c l u d i n g predator population dynamics.
8 . 3 Model Behaviour
Three scenarios were s imula ted on ' the l as t day of the workshop: a basel ine scenario, represent ing a simulation of ex is t ing fores t ry management regimes for each s i t e and the unmanaged dynamics of w i l d l i f e and their predators : a " t r e e farm" scenario, i n w h i c h the goal was t o maximize flow of commercial timber from the area: and a "wi ld l i f e farm" scenario, i n 'which the goal was t o maximize production of deer and e lk from t h e area. Because of the extreme
- 109 - e f f e c t s of predation on wildl i fe populat ions, these three scenarios are presented below without predation. A fourth scenario showing the e f fec ts of predation i s presented a t the end.
Output f1:onc the workshop model simulations is u s e f u l because it provides a focus for discussion and evaluation of the model and hypotheses. However, exact numerical output is not important because the model is s t i l l crude and preliminary. I t is more u s e f u l t o examine changes i n trends of var iab les under d i f f e r e n t management ac t ions and hypotheses.
8.3.1 Baseline Scenario
Input conditions for t h i s scenar io a re g i v e n i n Figure 8.7. One s i t e per year was harvested; the specif ic s i t e was chosen a t random from the potent ia l candidates .
The' annual harvest of wood (Figure 8 . 8 ) shows a mean removal of about 7 0 , 0 0 0 cubic meters. The f luc tua t ions i n the harvest come frorrh commercial t h i n n i n g s and the fac t that stands are not harvested immediately upon reaching 36m i n height. If not harvested they keep accumulating height and therefore volume. The large d i p a t about year 15 is because no s i t e s were 36m i n height that year and the peak i n about year 20 is because there were a la rge number of s i t e s commercially thinned that year.
Deer populations increase consistently from t h e i i i n i t i a l s t a r t i n g v a l u e of 4 5 0 animals and reach 4 0 0 0 animals i n 30 years, about an 8% increase per year. (Figure 8 .9) . Food never becomes l i m i t i n g t o dee r , even a t the h i g h levels reached i n the l a te r years . T h i s i s l i k e l y due to the absence of density-dependence i n the deer feeding processes (Section 5)
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Site Preparation
0 1 0 0 0 0 0 0 0 1 0 1 0 1 0 0 0 1 0 0 1 0 1 0 0 1 0 1 0 1 0 1 0 1 0 1 1 0 1 1 1 0 1 1 1 1 1 1 1 0 0 1 1 0 1 1 1 1 1 1 1 1 0 1 0 1 0 1 0 1 0 1 1 0 1 0 1 0 0 1 0 1 0 0 1 1 1 1 0 1 0 0 1 0 0 1
o - no site preparation 1 - burning all harvested sites are planted
. Initial Stand Age
M M M 0 20 20 40 45 50 50 50 50 M M 0 15 0 30 45 45 55 55 55 55 M M 5 5 20 40 55 55 60 60 60 60 M PI 10 5 30 45 55 60 60 65 65 70 I”I N ?I M 30 40 55 60 60 65 65 70 M - mature >f 11 Fl PI 20 40 55 55 60 60 60 60 M H $1 M 10 40 40 50 50 50 55 55 M Pl M M 10 20 30 30 30 45 45 45
Tending and Harvest
3 3 3 3 1 1 1 1 1 2 2 2 3 3 3 1 1 1 1 1 2 2 2 2 3 3 1 1 1 1 1 2 2 2 2 2 1 1 1 2 2 2 2 2 1 2 2 3 1 1 1 2 2 2 2 3 2 2 2 3 1 1 1 1 1 1 1 2 2 2 2 2 3 3 1 1 1 1 1 1 2 2 2 2 3 3 3 1 1 1 1 1 1 2 1 2
1 - space at 6m to 375 stems/ha
2 - space at 6m to 500 s tems/ha harvest at 36m
thin at 25m t o 250 s tems/ha harvest at 36m
3 - harvest at 36m
Figure E.: Initial site conditions f o r baseline scenario.
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F i g u r e 8 . 6
0 - \ U
" I YEAR 30 -
8 Annual Timber Harvest. 8aseline Scenario B
0 rc.
cn Q) L
c 200
4 I YEAR 30
Annual Timber Harvest. Wood Farm Scenario
350
0 I I YEAR 30
Annual Timber Harvest. Oeer Farm Scenario
woods harvest t r e a d s under thrett senezio
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4 000
a LJ w Q
# -
J I YEAR 30
60
I Y E A R
.
30
Figure 8.$ Deer and elk population trends unde r three scenarios . E l k show t h e same trend i n all three nodel runs.
- 113 - and the absence of nega t ive e f fec ts of browsing on the dynamics of vegetation species .(Section 3 ) . E l k populations a l so increase s tead i ly from t h e i r i n i t i a l p o p u l a t i o n and reach 60 animals a t about year 15; the animals then begin emigrating out of the area to maintain a maximum of 60 animals (Section 6).
8 . 3.2 "Tree Farm'' Scenario
The condi t ions for t h i s scenar io a re : ( a ) each yea r , ha rves t a l l s i t e s fo r which the height
is greater than 36 meters;
( b ) a p p l y h e r b i c i d e s t o a l l s i t e s c l e a r c u t ; and
(c) space and t h i n on every s i te , according to the ru l e s i n the baseline scenario.
The annual harvest of wood (Figure 8 . 8) shows a very h i g h i n i t i a l volume extraction followed by per iodic heavy burs t s of harvesting every 2-5 years. The h i g h i n i t i a l e x t r a c t i o n is because of t h e c l ea r cu t t i ng of mature stands i n the upper and lower p a r t s of the watershed. The per iodic bursts of harvest occur because many s i t e s reach harvestable height at the same time. The harvesting rule effect ively temporal ly synchronizes those s i tes w i t h the same growth indices .
E l k populations show the same trend as i n the baseline (Figure 8 . 9) . Deer populat ions increase a t a s lower ra te , 4 5 per year. The herbicide treatment of la rge numbers of s i t e s e f f e c t i v e l y removes much of the forage and browse t h a t was ava i lab le i n the baseline scenario.
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8.3.3 "Wildlife Farm" Scenario
The condi t ions for t h i s scenario are:
( a ) a l l s i t e s a r e i n i t i a l l y mature;
( b ) each year, harvest a l l s i t e s f o r which the height is greater than 3 m ; and
(c ) a l low natural regenerat ion on a l l c u t s i t e s .
Pa r t i c ipan t s spec i f i ed pa r t i cu la r s i t e s n o t t o be harvested throughout the simulation and a tending regime d i f fe ren t than tha t i n the basel ine.
Annual harvest of wood (Figure 8.10) again shows an i n i t i a l l a r g e e x t r a c t i o n of timber followed by effect ive. ly no volume yield. Again, i n t h e f i r s t y e a r , many mature sites were ha rves t ed . S i t e s . a re s t i l l being harvested i n succeeding years but volume y ie ld is very small because t rees a re on ly 3m i n height when c u t (Figure 4.3).
E l k again have dynamics s imi la r to those i n the basel ine. Deer populations respond almost as well a s i n the basel ine scenario and reach a populat ion s ize of about 3000 by year 30 (Figure 8 . 9 ) . Food is l i k e l y abundant because of natural regeneration, the .absence of s i t e p repa ra t ion and higher proportion of s i t e s w i t h low relat ive t imber fol iage biomass. The lower f inal populat ion suggests that t h e conceptualization of deer movement may be s u c h that they are not responding well to favourable changes i n t he i r hab i t a t . They may n o t be taking suff ic ient advantage of the improved hab i t a t t ha t is created for them by t h e s imulated forestry management regimes. T h i s suggests that the processes involved i n deer movement and re-distribution are poorly understood.
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Harvest
0 0 1 0 1 0 1 0 1 0 1 0 1 1 1 0 0 1 0 0 1 0 1 0 1 0 1 0 1 0 0 1 0 0 1 1 1 0 1 0 0 1 0 1 0 0 1 0 1 1 0 1 0 0 1 0 0 1 1 1 1 1 1 1 1 1 1 0 0 0 0 1 0 1 0 1 0 1 0 1 0 1 0 0 0 1 0 1 0 1 1 1 0 1 1 1
0 - never harvest 1 - harvest when height 3m
Figure 8.10 Input conditions for "wildlife farm" scenario.
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An a l t e r n a t i v e e x p l a n a t i o n for t h e r educed deer p o p u l a t i o n may d e r i v e from snow effects . The i n c r e a s e d food s u p p l i e s g e n e r a t e d by t h i s " w i l d l i f e farm" s c e n a r i o may be compensa ted fo r by t h e f ac t t h a t most o f t h i s food is b e i n g produced on s i tes t h a t p r o v i d e p o o r w i n t e r r a n g e . I n other w o r d s , o v e r a l l w i n t e r f o o d s u p p l i e s may a c t u a l l y b e reduced as a consequence of g r e a t e r snow dep ths on most si tes. S i n c e winter f e e d i n g is i m p o r t a n t t o b o t h s u r v i v a l a n d n a t a l i t y of deer t h e e f f e c t would be a r e d u c t i o n i n p o p u l a t i o n g r o w t h ra tes .
8 . 3 . 4 P r e d a t i o n Scenario
C o n d i t i o n s f o r t h i s s c e n a r i o a re t h e same as t h o s e f o r t h e b a s e l i n e scenar io ( S e c t i o n 8 . 3 . 1 ) e s c e p t t h a t a l l p r e d a t o r s h a v e b e e n i n c l u d e d .
E l k and deer p o p u l a t i o n s d e c r e a s e t o v e r y low l e v e l s qu ick ly and r ema in low f o r t h e d u r a t i o n of t h e s i m u l a t i o n ( F i g u r e 8.U) . Wolf numbers dec l ine as p r e y d e c l i n e ( F i 5 u r e 8.n). T h i s behav iour is e x t r e m e l y d i f f e r e n t t h a n t h a t i n a l l o t h e r scenarios a n d s t r o n g l y s u g g e s t s t h a t , g iven t he manner i n which t h e p r e d a t i o n p r o c e s s e s were c o n c e p t u a l i z e d ( S e c t i o n 7 ) t h e p o p u l a t i o n d y n a m i c s of deer and e l k a r e h i g h l y s e n s i t i v e t o p r e d a t i o n .
8.4 Model Ref inemen t s
The p r e s e n t model is v e r y c o m p l e x a n d t h e r e f o r e d i f f i c u l t t o i n t e r p r e t a n d u n d e r s t a n d w i t h o u t e x t e n s i v e gaming. We s t r o n g l y recommend a t h o r o u g h a n a l y s i s of t h e
c o n c e p t s a n d d a t a u s e d t o d e v e l o p t h e p r e s e n t m o d e l . I n i t i a l
.
Y J W
#
60
0
- 117 - PREOAT ION S C E N A R
.
Y E A R
10
I 30
a W W 0
#
v) W
0 3
3
#
I Y E A R
30
I Y E A R
30
.
Figure 8 . 1 1 &lode1 behaviour for predat ion scenario .
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l i terature reviews are of ten very helpful i n f i l l i n g many of the data and parameter uncertainties, as well as some conceptual def ic iencies .
We recommend aga ins t making refinements which add t o model complexity u n t i l the dynamics of the current vers ion are well understood. Perhaps a careful analysis of the current model w i l l show that far less detai1:s is :suff ic ient to under- s tand the interact ions between fo res t ry and wildl i fe populat ion dynamics. The refinements detailed below e i ther requi re new conceptualization of ex i s t ing pa r t s of the model, addi t ion of important components t ha t were l e f t o u t of the i n i t i a l model, or the acquisition of bet.ter data.
8.4.1 Vegetation
There appears t o be l i t t l e e f f e c t of food l imi t a t ion on deer and e lk from the predictions of the model presented i n Section 8.3. Therefore there is no present need t o r e f i n e the conceptual s t ructure of the vegetation submodel. Futur.e refinements to the deer and e lk models t ha t produce food l i m i t i n g e f f e c t s w i l l a lso provide guidance as to what refinements are needed i n the vegetation submodel.
8.4.2 Timber
8.4.2.1 Effec ts of Browsing
The model w , i l l have grea te r p red ic t ive power when the e f f e c t s of browsing on t r ee growth and mor ta l i ty a re be t te r quant i f ied. Al ternately, equal ly viable hypotheses exis t for t h e impact of foliage removal. These r e l a t ionsh ips can be eas i ly measured w i t h simple a r t i f i c i a l d e f o l i a t i o n experiments (e.9. , Craighead, 1 9 4 0 ) .
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8.4.2.2 Direct Effects of Wildl i fe
The model present ly does not consider the direct e f f e c t s of w i ld l i f e on timber. T h i s conceptual deficiency can be removed by developing a r e l a t ionsh ip t ha t p red ic t s d i r e c t removal of stems a s a function of stem s i z e and use of a s i t e by deer and e l k , a s measured i n number of animals/unit area/unit time. The time fac tor is c r u c i a l because increasing duration of s tay i n a s i t e probably r e s u l t s i n greater physical damage t o t h e young coni fe rs on t h a t s i t e .
8.1.3 Deer - Some of the po ten t ia l model refinements suggested by
the discussion of conceptual and information gaps i n the deer submodel (Section 8.2.3) would be d i f f i c u l t t o make w i t h the present model s t ruc ture . For example, improving t h e pred ic t ion of food covered by snow would e n t a i l a vegetation submodel much more detailed than the one a t present . Given the absence of food l imi t a t ion , even w i t h probable underestimation of winter forage availabil i ty (Section 8.2.3.1.2) , t h i s pa r t of the model is not worth re f in ing a t present . However, some pa r t s of the deer model could l ikely be eas i ly improved.
8.4.3.1 Snow Intercept ion
The degree of snow in te rcept ion is r e l a t ed t o e a s i l y measured var iab les s u c h a s crown closure and crown length. Accurate relationships for predicting snow in te r - ception can l ikely be derived u s i n g var iables a l ready calculated
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i n the present model; s u c h re la t ionships would be easy to implement.
8.4.3.2 Food Preferences
The estimation of unbiased preferences i s a d i f f i c u l t task b u t , i f i t were done, could be very simply ref ined i n t h e model. A review of e x i s t i n g l i t e r a t u r e would be a prudent step because the preferences may already be documented.
8.4.3.3 Exploi ta t ion
Exploitation competit ion was not included i n the f i r s t v e r s i o n of the model and one form of t h i s process is presently included. I t has no q u a l i t a t i v e e f f e c t on model behaviour. Yet, other forms of exploitation could be simulated, u s i n g competition models from c lass ica l p reda tor - prey theory (e .g . , Griff i ths and Holling, 1 9 6 9 ) . The model may be sensi t ive to other a l ternate hypotheses about exp lo i t a t ion , t h u s p o i n t i n g t o the need for research i n t h a t area.
8.4.4 E l k
8.4.4.1 Escape Cover
-
If what elk perceive a s good escape cover can be quant i f ied , the model can be re f ined to accommodate those changes. Additional variables which elk probably use as escape cover, such as debr i s and vegetation, are simulated
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i n the present model and appropriate re la t ionships could be developed to re la te these var iables to the escape cover value of a s i t e .
8.4.4.2 Food Preferences
See Section 8.4.3.2, Deer Food Preferences. The arguments are the same.
8.4.4.3 Emigration
The var iab les which i n i t i a t e emig ra t ion a r e l i ke ly t o be d i f f i c u l t t o measure and are probably similar to those which i n i t i a t e movement between s i t e s w i t h i n a region. The present hypothesis implies that e lk are intolerant of physical crowding, irrespective of the range value for the area. The model w i l l have grea te r p red ic t ive power i f the proper mechanisms for emigration can be described.
8.4.5 Predation and H u n t i n g
8.4.5.1 Seasonal Distribution of Predation
The.predat ion ra tes i n t h e model a re no t sens i t ive to seasonal changes i n prey density (Section 8.2.5.1). The functional responses can be redefined to operate seasonal ly .
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8 .4 .5 .2 Functional and Numerical Responses of Predators t o Prey Density
A l l of the functional and numerical responses were best guess hypotheses. These hypothesesneed t o be evaluated by examination of ex is t ing da ta and a v a i l a b l e l i t e r a t u r e . T h i s is necessary i f the parameters and form of the relat ionships are to achieve a measure of c r e d i b i l i t y . However, the use of b i o l o g i c a l l y r e a l i s t i c models for predation ensures that any refinements can be made very simply.
8.4.5.3 'Wolf Predation
Predation by wolves on deer and elk received the most a t t en t ion i n the development of the predation submodel. Predation is represented by a s e t . of t i g h t l y linked hypotheses about the functional responses of wolves t o fawns? a d u l t deer , and e lk ; and numerical responses of wolves t o deer. The conceptual adequacies and inadequacies are discussed i n d e t a i l i n Section 8 . 2 . 5 . 4 . Better parameter es t imates can ce r t a in ly be derived from ex i s t ing wolf preda t ion l i t e ra ture (e .g .? Haber , 1 9 7 7 ) and used to improve t h i s par t of t h e model.
8 .4 .5 .4 Cougar Predation
Each cougar may k i l l a s many a s 50 deer per year. T h i s r a t e is significantly higher than the number of k i l l s per wolf. However i n the model cougar predation received a n i g h l y simplified treatment. Much more thought is required before a good understanding of cougar predation can be included i n the model. I n view of the assumed impact
- 123 -
cougars on deer and elk this part of the model should be refined.
8.4.5.5 Escape Cover
A major question is, how does change in the amount and availability of escape cover effect predation? The problems with the current conceptualization were outlined in Section 8 . 2 . 5 . 9 . A rationale needs to be developed to support hypotheses about which components (availability of prey, successful search rate of predators, handling time) are affected.by escape cover. Because escape cover is closely tied to various silvicultural and forest practices the development of a better understanding of the effect of escape cover is a prime candidate for model refinement.
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9 . 0 RESEARCH RECOMMENDATIONS
9 . 1 The Impor tance of I n t e r d i s c i p l i n a r y H y p o t h e s e s
The IWIFR Program spans two b r o a d d i s c i p l i n e s : f o r e s t r y a n d w i l d l i f e b i o l o g y . The i n t e r d i s c i p l i n a r y n a t u r e of t h e p r o g r a m makes r e s e a r c h p l a n n i n g a d i f f i c u l t t ask . L i n k s b e t w e e n d i s c i p l i n e s m u s t b e u n d e r s t o o d i n i n t e r d i s c i p l i n a r y r e s e a r c h p l a n n i n g a n d d a t a collected b y o n e d i s c i p l i n e s h o u l d be u s e f u l t o o t h e r d i s c i p l i n e s . R e s e a r c h e r s i n v o l v e d i n i n t e r d i s c i p l i n a r y r e s e a r c h m u s t b r o a d e n t h e i r o u t l o o k t o t h e " w h o l e s y s t e m " l e v e l from t h e more c o n v e n t i o n a l " s u b s y s t e m " or " s i n g l e d i s c i p l i n e " l e v e l .
B u t e s t a b l i s h i n g h y p o t h e s e s t h a t c o n s i d e r a l l r e l e v a n t d i s c i p l i n e s is d i f f i c u l t w i t h o u t a n o r g a n i z a t i o n a l f o r m a t . T h e s i m u l a t i o n model d e v e l o p e d i n a n AEAM workshop p r o v i d e s t h a t f o r m a t i n terms o f a set o f l i n k e d h y p o t h e s e s abou t sys t em behav iour . The mode l deve loped i n t he IWIFR re seach p l ann ing workshop embod ies a se t o f h y p o t h e s e s a b o u t t h e i n t e r a c t i o n s among f o r e s t v e g e t a t i o n , d e e r , e l k , p r e d a t o r s a n d man. T h i s sec t ion e x p l i c i t l y i d e n t i f i e s t h o s e h y p o t h e s e s w h i c h should be g i v e n f u r t h e r a t t e n t i o n . We h a v e a t t e m p t e d t o i n c l u d e o n l y t h o s e h y p o t h e s e s w h o s e t e s t i n g w i l l p r o v i d e v a l u a b l e c o n t r i b u t i o n s t o t h e o b j e c t i v e s o f t h e IWIFR p r o j e c t . T h e s e h y p o t h e s e s h a v e b e e n c h o s e n o n t h e basis o f t h e i r i m p a c t , b o t h o b s e r v e d a n d a n t i c i p a t e d , o n t h e m o d e l ' s b e h a v i o u r . T h e more s e n s i t i v e t h e m o d e l ' s p r e d i c t i o n s a r e t o c h a n g e s i n a p a r t i c u l a r h y p o t h e s i s , . t h e more i m p o r t a n t it is t h a t t h e h y p o t h e s e s b e t e s t e d .
I t is c r i t i c a l l y i m p o r t a n t t o r e c o g n i z e t h a t r e s e a r c h on any of t h e h y p o t h e s e s w i l l bene f i t eno rmous . ly f rom an i n t e r d i s c i p l i n a r y a p p r o a c h . I n p a r t i c u l a r , t h e c a r e f u l d e s i g n
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of an experimental forest management plan to provide an arena for evaluat ing deer , e lk and predator responses to a va r i e ty of management act ions would cons t i t u t e an invaluable tool for the IWIFR program. Designing such a plan would only be worthwhile i f i n p u t s from a l l r e l e v a n t d i s c i p l i n e s were encouraged. Allocation of a small watershed i n which a l l the f ie ld research were carr ied out would help to ensure interdiscipl inary coordinat ion and understanding.
9 .2 Vegetation
The vegetation submodel is r i ch w i t h parameters. Most of these numbers were estimated under the pressure of time. I t would be prudent to review these parameters .to reveal large inaccuracies .
9 . 2 . 1 Competition
There is no compet i t ion among v e g e t a t i o n s p e c i e s .
T h i s hypothesis is probably invalid. However, competitive in t e rac t ions among plants should only be expl ic i t ly considered insofar a s they are influenced by deer and elk feeding. The e f f e c t s of browsing pressures on plant population dynamics deserves much more at tent ion than it was given i n the workshop.
9 .2 .2 Foraqe Ava i l ab i l i t y
1 0 % of t he s tand ing crop of a l l v e g e t a t i o n i s a v a i l a b l e a s f o r a g e t o d e e r and e l k . T h i s hypothesis should be careful ly reconsidered to evaluate the extent to which p lan t type, browsing history and standing crop affect forage a v a i l a b i l i t y .
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9 . 3 Timber
9 .3 .1 B r o w s i n g E f f e c t s
The r e l a t i o n s h i p b e t w e e n t r e e m o r t a l i t y and animal
browsing i s s t r i c t l y l i n e a r . T h i s is c e r t a i n l y n o t t r u e for g r a z i n g e f f e c t s o n c o n i f e r s f r o m o t h e r h e r b i v o r e s ( e . g . , f o r e s t i n s e c t s ) .
Tree mor ta l i ty f rom animal browsing i s independent
o f t r e e s i z e . The t i g h t c o u p l i n g b e t w e e n r e g e n e r a t i o n s t a n d d y n a m i c s a n d w i l d l i f e g r a z i n g i n d i c a t e s t h a t t h i s h y p o t h e s i s shou ld be tes ted. T h i s a n d t h e a b o v e h y p o t h e s i s a re v e r y c l o s e l y l i n k e d a n d c a n b e t e s t e d t o g e t h e r i n t h e same f i e l d p r o j e c t , g i v e n a n a p p r o p r i a t e e x p e r i m e n t a l d e s i g n .
Animal browsing does not permanent ly chenge those c h a r a c t e r i s t i c s o f a stand which a r e i m p o r t a n t t o w i l d l i f e
( c rown c losure , average he igh t , crown r a t i o , e t c . ) . An e x p e r i m e n t a l a p p r o a c h t o t e s t i n g t h i s h y p o t h e s i s is beyond t h e t e r r p o r z l s c o p e o f t h e IWIFR program, bu t can be examined by c o n s t r u c t i n g a more a p p r o p r i a t e a n d r e a l i s t i c c o n c e p t u a l i - z a t i o n of s t a n d d y n a m i c s .
9.3.2 Direct E f fec t s of Wi ld l i fe
W i l d l i f e d o e s n o t d i r e c t l y a f f e c t t r e e a a d stand growth.
Trampl ing may cause h i g h stem m o r t a l i t y . A s i m p l e f i e l d e x p e r i m e n t c o u l d b e d e s i g n e d t o measure t h e stem loss under a r a n q e of d e e r a n d e l k use l e v e l s a n d t r e e s i z e s .
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9.3.3 C o m p e t i t i o n From O t h e r V e g e t a t i o n
Timber dynamics a re i ndependen t o f unders tory vege ta t ion .
T h i s assumes no compe t i t i on be tween commercial wood s p e c i e s a n d o t h e r v e g e t a t i o n , a n a s s u m p t i o n which may be i n v a l i d i n some s i t u a t i o n s . Some p a r t i c i p a n t s a t the workshop recalled cases i n w h i c h r e g e n e r a t i o n of commercial timbe; s p e c i e s was u n s u c c e s s f u l because of heavy growth of o t h e r p l a n t s . T h i s h y p o t h e s i s c a n e a s i l y be tes ted i n a f i e l d p r o j e c t by measur ing t ree growth r a t e s u n d e r v a r i o u s biomasses of o t h e r v e g e t a t i o n .
9 . 4 Deer
9.4 ..1 Snow - The e f f e c t o f s n o w f a l l on food s u p p l y and energy
c o s t s f o r deer i s i n d e p e n d e n t o f t h e a c t u a l sequence of
s n o w f a l l e v e n t s d u r i n g w i n t e r . T h i s h y p o t h e s i s may be best e v a l u a t e d i n a theore t ica l framework s i n c e f i e l d e x p e r i m e n t a t i o n would be v e r y d i f f i c u l t a n d l i k e l y o n l y c o r r e l a t i v e . U s i n g t h e model t o examine r e sponses t o c h a n g e s i n t h e t e m p o r a l " s t ruc tu re" of w i n t e r s h o u l d p r o v i d e i n s i g h t s i n t o how d e t a i l e d a n u n d e r s t a n d i n g o f t he i n t e r a c t i o n s b e t w e e n s n o w f a l l p a t t e r n s and deer s u r v i v a l is n e c e s s a r y .
For a l l t r e e s g r e a t e r t h a n 2m t a l l , t h e r e i s a d i r e c t
z e i a t i o n s b i p j e t w e e n crown c l o s u r e and snow i n t e r c e p t i o n ,
w i t h c o m p l e t e i n t e r c e p t i o n o c c u r i n g a t 100% crown c l o s u r e .
T h i s is l i k e l y n o t t r u e ; h o w e v e r , i t p r o v i d e s a n u l l h y p o t h e s i s a g a i n s t w h i c h t h e i n t e r a c t i o n s b e t w e e n t ree h e i g h t , c r o w n closure and snow i n t e r c e p t i o n c a n be e v a l u a t e d . S u c h i n t e r - act ions l e n d t h e m s e l v e s e a s i l y t o f i e l d measurements in managed
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s t a n d s a n d may p r o v i d e v a l u a b l e i n s i g h t s i n t o t h e c h a r a c t e r i z a t i o n o f winter r ange .
The r e l a t i o n s h i p b e t w e e n snow depth and t h e p r o p o r t i o n
o f f o o d a v a i l a b l e t o d e e r i s s t r i c t l y l i n e a r . The assumpt ion implicit i n t h i s h y p o t h e s i s , t h a t t h e f o o d - h e i g h t d i s t r i b u t i o n f o r a l l p l a n t s is u n i f o r m , d e s e r v e s a t t e n t i o n . I f t h i s a s s u m p t i o n is s e r i o u s l y i n v a l i d f o r i m p o r t a n t w i n t e r food s p e c i e s i t w i l l s e v e r e l y o v e r e s t i m a t e t h e d e t r i m e n t a l impac t o f snowfa l l on deer s u r v i v a l . I n f o r m a t i o n o n t h i s 2 r e s u n a b l y . c a n b e f o u n d i n t h e l i t e r a t u r e a n d f i e l d a n a l y s e s may be unwarranted - t h e reso lu t ion r e q u i r e d is n o t g r e a t .
9 . 4 . 2 Movement
Deer s e l e c t w i n t e r r a n g e h a b i t a t s a t t h e b e g i n n i n g
o f w i n t e r and do n o t m o d i f y t h e i r d i s t r i b u t i o n i n r e s p o n s e t o t h e a c t u a l s n o w f a l l p a t t e r n s t h a t w i n t e r . O b s e r v a t i o n s of h a b i t a t f i d e l i t y d u r i n g w i n t e r w o u l d p r o v i d e u s e f u l i n f o r - m a t i o n o n t h e v a l i d i t y of t h i s a s s u m p t i o n . I t is poss ib le t h a t t h e costs o f r e d i s t r i b u t i o n when s n o w f a l l is u n u s u a l l y heavy may o u t w e i g h t h e b e n e f i t s o f m o v i n g t o more s u i t a b l e w i n t e r r a n g e . If t h i s is n o t t r u e t h e deer i n t h e model may be more s e n s i t i v e ( i n t e rns o f e f f e c t s o n s u r v i v a l ) t o v a r i a t i o n s i n w i n t e r climate t h e n w o u l d b e e x p e c t e d i n r e a l i t y .
The ccmponents used t o c h a r a c t e r i z e t h e v a l u e o f a s i t e a s deer h a b i t a t a r e s u f f i c i e n t t o a c c u r a t e l y r e f l e c t
t h e u t i l i t y o f t h a t s i t e a s w in te r range , e scape ccver h a b i t a t ,
and f e e d i n g h a b i t a t . T h i s h y p o t h e s i s n e e d s more d j s c u s s i o n . I t is d i f f i c u l t t o c o n c e i v e of s i m p l e f i e l d e x p e r i m e n t s t o e f f e c t i v e l y i d e n t i f y t h e c r i t i c a l components of deer h a b i t a t . A c o n c e r t e d e f f o r t s h o u l d b e made t o c a r e f u l l y i d e n t i f y a
l i s t of components which a r e most l i k e l y t o be i m p o r t a n t .
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From such a l i s t , pred ic t ions of deer dis t r ibut ions i n a par t icu lar a rea a t dif ferent t imes of year could be compared to the ac tua l seasonal pa t te rns i n that area.
An a r e a of 3 2 0 h e c t a r e s i s a r e a s o n a b l e a p p r o x i m a t i o n of t h e r a n g e of movement of a n i n d i v i d u a l d e e r i n a p a r t i c u l a r
s e a s o n . T h i s hypothesis is r e l a t ed t o t he one above. Again, observations of w i t h i n season movement pa t t e rns would provide useful information for the testing of t h i s hypothesis.
A grea t dea l of emphasis was placed a t the workshop on the importance of spa t ia l he te rogenei ty to deer surv iva l . S i tua t ions such as the juxtaposition of good winter range w i t h a winter food supp ly were thought t o be c r i t i c a l t o d e e r . Clearly, t h i s question is one of the c e n t r a l issues of the IWIFR program. A grea t dea l of careful thought and discussion m u s t be devoted to developing ways of evaluating j u s t how sens i t i ve deer a re to the s t ruc ture of the meso-environment which surrounds them. Presumably, the more mobile (both i n terms of capaci ty and wil l ingness to move) the animals are, the less important local disturbances become. Studies of deer movements i n response to changes i n habitat should probably form the focus of research effort concerned w i t h deer. Studies of deer d i s t r ibu t ion and abundance c a r r i e d o u t . i n conjunction w i t h experimental forest harvesting and second growth management p rac t i ces would be espec ia l ly usefu l .
9 .4 .3 Feeding
Both the annual biomass to seasonal kcal conversion fac tors and the re la t ive preference values used i n the model should be ca re fu l ly reviewed to ensure that they are reasonable.
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Research aimed at es tabl ishing the actual deer preferences for various food types m i g h t be worthwhile, although the e f for t requi red to genera te accura te resu l t s may outweigh the benefi ts . Educated guesses a t preferences derived from t h e l i t e r a t u r e and perhaps some crude measures of e l e c t i v i t y ( Iv lev , 1 9 6 1 ) should be s u f f i c i e n t . I t is important to recognize that only large differences i n preference are worth considering. Two species which exhibi t only a 20% d i f fe rence i n preference m i g h t well be considered a single food type from the deer 's point of view.
There i s no i n t e r f e r e n c e c o m p e t i t i o n f o r f o o d among
deer an6 e x p l o i t a t i o n e f f e c t s a r e o n l y i m p o r t a n t a t very h i g h
d e e r d e n s i t i e s r e l a t i v e t o t h e i r f o o d s u p p l y . These two assumptions imply t h a t . the deer are efficient, cooperative foragers and have important implications to both deer and t h e i r food supply when deer populations become very large. The absence of these effects presumably accounts to some extent for the extremely large deer populations observed i n all model scenarios without predation.
9 . 4 . 4 S u r v i v a l a n d R e p r o d u c t i o n
A l l m o r t a l i t y e x c e p t t h a t due t o p r e d a t i o n and hun t ing occurs dur ing win ter and i s i n f l u e n c e d s o l e l y b y a w in te r
cxergy budget .
Reproduct ion ( b i r t h o f f a w n s ) o c c u r s a t t he beg inn ing o f summer and i s i n f l u e n c e d s o l e l y b y w i n t e r and spring energy
i n t a k e .
These two hypotheses were considered quite reasonable by most pa r t i c ipan t s . However, the extreme sensit ivity of the model t o changes i n the parameters of the re la t ionships
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d e r i v e d from t h e s e h y p o t h e s e s s u g g e s t s t h a t a c a r e f u l r e v i e w of both would be w a r r a n t e d .
Winter mortality and predation mortality are not compensatory. T h i s h y p o t h e s i s i m p l i e s t h a t t h e w i n t e r s u r v i v a l r a t e s of deer r e m a i n i n g a f t e r p r e d a t i o n a n d h u n t i n g s e i n d e p e n d e n t o f p r e d a t i o n a n d h u n t i n g m o r t a l i t y . T h i s h y p o t h e s i s is i n v a l i d i f p r e d a t o r s take t h e weaker members o f a p r e y p o p u l a t i o n . H i g h e r p r e d a t i o n ra tes s h o u l d decrease t h e number of weaker a n i m a l s e n t e r i n g t h e w i n t e r a n d c o n s e q u e n t l y i n c r e a s e w i n t e r s u r v i v a l .
9.5.1 Effects of Snow
The metabolic costs of a population moving through snow are related only to the depth of snow and the population
size. I n f a c t small e l k u s e t r a i l s g e n e r a t e d b y l a r g e r e l k
and t he metabolic costs t o t h e p o p u l a t i o n are t h e r e f o r e n o t s i m p l y m l t i p l i c a t i v e . Also, t h e t y p e .of snow is p r o b a b l y i m p o r t a n t . Metabolic costs of walking on snow t h a t h a s a t h i c k ice l a y e r are p r o b a b l y lower t h a n w a l k i n g on snow wi thout such a l a y e r . T h e i m p o r t a n c e of f i e l d - t e s t i n g t h i s h y p o t h e s i s c a n be estimated by gaming w i t h t h e p r e s e n t model. The metabolic cost m u l t i p l i e r for snow ( F i g u r e 6.3) c a n be a p p l i e d o n l y t o a d u l t a g e classes, or c a n be scaled up or down t o simulate t h e e f f e c t s of d i f f e r e n t snow types.
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9.5.2 Movement
T h e a r g u m e n t s p e r t a i n i n g t o deer movement ( S e c t i o n 9 .4 .2 )
a p p l y t o e l k as well . Expe r imen t s t o a c c u r a t e l y d e f i n e t h e e n v i r o n m e n t a l c r i t e r i a e l k u s e i n c h o o s i n g h a b i t a t w o u l d be d i f f i c u l t t o c o n c e i v e a n d d e s i g n , l e t a l o n e u n d e r t a k e . P e r t u r b a t i o n s t u d i e s offer p e r h a p s t h e best method of d i s c e r n i n g t h e i m p o r t a n t c r i t e r i a e l k u s e . S t a n d s of v a r i o u s t y p e s c o u l d be a l te red i n s p e c i f i c a n d w e l l - d e f i n e d ways and changes in t h e u s e of those s t a n d s by e l k measured.
E l k u s e of a n a r e a w i t h s n o w i s o n l y p r o p o r t i o n a l t o
t h e a v a i l a b l e f o r a g e i n t h e a r e a . T h e h i g h e r m e t a b o l i c c o s t s of a o v i n g t h r o u g h s n o w a r e n o t " t r a d e d o f f " a g a i n s t f o r a g e
v a l u e . E l k p r o b a b l y u t i l i z e a s i t e on t h e basis o f i ts n e t e n e r g y v a l u e . T h e y l i k e l y do n o t use a s i te w i t h snow s i m p l y because i t h a s a h i g h f o r a g e v a l u e b u t " c o m p a r e " t h e p o t e n t i a l e n e r g y g a i n s t o be made by g r a z i n g o n t h e a v a i l a b l e f o r a g e w i t h t h e metabolic costs o f .mov ing t h rough t he snow in t ha t s i t e .
Forage under snow i s c o m p l e t e l y u n a v a i l a b l e t o e l k .
T h i s i s p r o b a b l y n o t t r u e . E l k may d i g u n d e r t h e snow for forage, t h e r e b y r e d u c i n g p o t e n t i a l food s t r e s s d u r i n g t h e w i n t e r . M e t a b o l i c costs t o e l k from s u c h a c t i v i t y are l i k e l y increased , however (Walters e t a l . , 1 9 7 5 ) .
9 . 5 . 3 Escape Cover
Slk w i l l n o t u s e s i t e s w i t h n o a c c e s s t o a d e q u a t e
c o v e r . T h i s may be t r u e under c o n d i t i o n s of adequate f o r a g e a v a i l a b i l i t y b u t may n o t be t r u e i f f o r a g e becomes l i m i t i n g . Under food s t r e s s e l k may t r a d e o f f t h e r i s k s of b e i n g k i l l e d by
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predators w i t h the r i sks of s t a rva t ion and w i l l feed i n areas without good escape cover.
E l k perce ive escape cover o n l y i n t e r m s o f d e n s i t y and
h e i g h t o f t i m b e r . Other components of habitat are probably also used. Debris and other vegetation may be used by e l k , e spec ia l ly t h e smaller animals. I t is probably impossible to der ive a good d e f i n i t i o n of escape cover i n a f ie ld s tudy . Simply observing where e lk spend time i s not adequate because e l k s e l e c t h a b i t a t u s i n g o t h e r c r i t e r i a . Also, escape cover cannot be defined i n terms of v i s i b i l i t y t o humans, a s Thomas e t a l . ( 1 9 7 9 ) have done, but i n terms of probabi l i ty of a t tack by predators , a d i f f i c u l t q u a n t i t y t o measure. An a l t e rna te approach would be t o t e s t model behaviour using d i f f e r e n t d e f i n i t i o n s of escape cover ( i . e . , combination of t imber a t t r ibu tes , debr i s , and vegeta t ion) .
9 . 5 . 4 Forage
F o o d p r e f e r e n c e s r e f l e c t f o o d requ i remen t s . T h i s
hypothesis assumes that the forage species selected by e lk ref lect physiological needs. Therefore , e lk would go hungry and suffer decreased survivorship and f ecund i ty i f r e s t r i c t ed to unpreferred browse. An a l ternate hypothesis is t h a t e l k have "psychological" preferences and su f fe r no adverse effects i f forced t o feed on " less preferred" forage types.
T h i s can probably be tes ted by a review of t h e l i t e r a t u r e or by a s imple f ie ld s t u d y i n w h i c h the phys io logica l s ta tus of e lk were monitor'ed under d i f f e r e n t d ie t s .
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9 .5 .5 E m i g r a t i o n
E l k e m i g r a t e a s a r e s u l t of p e r c e i v e d e l k d e n s i t i e s
a n d n o t a s a r e s u l t of r e d u c e d r a n g e v a l u e s . E l k d i s p e r s a l is p r e s e n t l y a s s u m e d t o b e d e p e n d e n t o n l y o n p o p u l a t i o n s i z e . T h i s i m p l i e s t h a t a p o p u l a t i o n w i l l s t a r v e a t low d e n s i t i e s r a t h e r t h a n e m i g r a t e f r o m a low p r o d u c t i v i t y w a t e r s h e d . C o n v e r s e l y , a t h i g h d e n s i t i e s , e l k w i l l l e a v e v e r y p r o d u c t i v e r a n g e s . An a l t e r n a t e h y p o t h e s i s is t h a t e m i g r a t i o n is d e t e r m i n e d by p o p u l a t i o n v i g o r , as m e a s u r e d b y w e i g h t , r e l a t i v e f o r a g e i n t a k e , or some o t h e r i n d i c a t o r .
T h e s e h y p o t h e s e s w o u l d b e d i f f i c u l t t o t e s t well i n t h e f i e l d b e c a u s e i t would e n t a i l a l a r g e scale e x p e r i m e n t . Some i n d i c a t i o n o f w h a t t r i g g e r s e m i g r a t i o n i n e l k could be d e r v i e d , t h o u g h , by t r a c k i n g a n i m a l s w i t h v a r y i n g p h y s i o l o g i c a l s t a t e s . P r e s u m a b l y , i f t h e f o r m e r h y p o t h e s i s is n o t i n v a l i d , movement s h o u l d b e i n d e p e n d e n t o f a n i m a l v i g o r ; i f t h e l a t t e r h y p o t h e s i s is n o t i n v a l i d , movement w i l l be dependent on a n i m a l v i g o r .
9 . 6 P r e d a t i o n a n d H u n t i n g
The e f f e c t s of p r e d a t i o n and h u n t i n g i n t h e m o d e l a p p e a r t o be so s i g n i f i c a n t t h a t t h e y m a s k t h e e f f e c t s o f f o r e s t management p r a c t i c e s on w i l d l i f e p o p u l a t i o n s . T h i s m o d e l r e s u l t c o r r e s p o n d s well w i t h t h e o b s e r v a t i o n s o f some p a r t i c i p a n t s o f d r a m a t i c d e c l i n e s i n d e e r p o p u l a t i o n s on V a n c o u v e r I s l a n d w i t h a c c o m p a n i e d i n f l u x e s a n d i n c r e a s e s i n wolves. Given t h e dramatic e f f e c t o f p r e d a t i o n on w i l d l i f e p o p u l a t i o n s , b o t h s i m u l a t e d a n d r e a l , close i n v e s t i g a t i o n of p r e d a t i o n on dee r and e l k is w a r r a n t e d .
I - 135 -
9 . 6 . 1 Func t i . ona1 Respodses \
Fawn m o r t a l i t y f kom bear predat ion increases as fawn d e n s i t y d e c r e a s e s .
E l k m o r t a l i t y f r o n c o u g a r p r e d a t i o n i n c r e a s e s a s e l k
d e n s i t y d e c r e a s e s .
Deer m o r t a l i t y f r o m cougar predat ion increases a s deer d e n s i t y d e c r e a s e s and becomes constant when d e e r d e n s i t y becomes s u f f i c i e n t l y l o w .
Deer m o r t a l i t y f r o m w o l f p r e d a t i o n i n c r e a s e s t o a aaxi .~um a s d e e r d e n s i t i e s i n c r e a s e f r o m v e r y l o w l e v e l s and
decreases w i t h f u r t h e r i n c r e a s e s i n d e e r d e n s i t y .
W o l v e s s w i t c h t o e l k a s p r e y when d e e r d e n s i t i e s
d e c r e a s e t o v e r y l o w l e v e l s .
T h e s e h y p o t h e s e s h a v e v e r y d i f f e r e n t i m p l i c a t i o n s f o r t h e p o p u l a t i o n d y n a m i c s o f d e e r a n d e l k . T h e y i m p l y t h a t , a l o n e , b e a r s h a v e t h e p o t e n t i a l t o d r i v e d e e r p o p u l a t i o n s e x t i n c t , c o u g a r s h a v e t h e p o t e n t i a l t o d r i v e e l k p o p u l a t i o n s e x t i n c t , w h i l e w o l v e s can d r i v e d e e r p o p u l a t i o n s t o v e r y low l e v e l s a n d m a i n t a i n t h e m a t low l e v e l s .
T h e f o r m o f t h e b e a r f u n c t i o n a l r e s p o n s e a n d t h e c o u g a r f u n c t i o n a l r e s p o n s e i m p l i e s t h a t t h e y h a v e n o h a n d l i n g time ( t i n e t a k e n t o h u n t , c a p t u r e , e a t , a n d d i g e s t a p r e y ) when h u n t i n g for t h e s e p r e y ( H o l l i n g , 1959), a n i n v a l i d a s sumpt ion . Also, t h e p a r a m e t e r estimates f o r t h e f u n c t i o n a l r e s p o n s e s , s u c h a s maximum consumpt ion r a t e s , were " b e s t g u e s s " estimates. The f u n c t i o n a l r e s p o n s e s o f t h e p r e d a t o r s s h o u l d be examined c lose ly .
- 136 -
The functional responses of bear and cougar probably have a form similar to that hypothesized for wolves. A l l
three predator species are generalized. They have a var ie ty of spec ies as po ten t ia l p rey , and take advantage of a pa r t i cu la r prey item when i t becomes more abundant. Exact determination of the functional response is therefore not pract ical because a l te rna te p rey , as well as deer and e l k , would have t o be iden t i f i ed and censused. However, i t would be usefu l t o estimate the parameters of t h e functional response (Section 8 .2 .5 .9 )
under a range of prey densities. They can be derived by visual observat ions of wolves, bear, and cougar preying on deer and elk (e.g. , Haber, 1 9 7 7 ) . The r e s u l t s may be tempered by the confounding effect of escape cover but w i l l cer ta inly provide a better understanding of t he e f f ec t s of predation.
9 . 6 . 2 Numerical Responses
Bear and cougar popula t ions are independent of deer
and e l k p o p u l a t i o n s .
Wolf popula t ions are independent of e l k p o p u l a t i o n s .
hiolves have a numer ica l r e sponse t o deer populations.
Numerical responses are d i f f i c u l t to es t imate and their es t imat ion may be outside the scope of t h i s program. Predator d e n s i t y estimates on Vancouver Island, coupled w i t h a knowledge of the functional responses, would give a good p r e d i c t i v e a b i l i t y of t h e p o t e n t i a l e f f e c t s of predators on deer and elk populations.
- 137 -
A review of the appropr ia te l i t e ra ture would probably give i n s i g h t into numerical responses. For example, Haber ( 1 9 7 6 ) has found that the numerical response of wolves i n the a r c t i c is closely related to changes i n the soc ia l s t ruc ture and t e r r i t o r y s i z e under different prey densi t ies . Information of t h i s type may be usefu l to the I W I F R program.
9.6.3 Escape Cover
The presence of escape cover makes a propor t ion of
t h e prey populat ion " immune" from predat ion.
Escape cover may af fec t p reda t ion by increasing handling time, decreasing the rate of successful search, or may a f f e c t any combination of parameters. The s e n s i t i v i t y of various assumptions about what consti tutes escape cover and the e f f ec t s of escape cover on the functional response should be tes ted w i t h the present model. The assumptions t o which the model is most s ens i t i ve can then be tes ted for i n the f ie ld . Exploration w i t h the model is a necessary prerequisite because of the l ikely d i f f i c u l t y i n conducting field experiments on escape cover (Section 9 . 5 . 2 ) .
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1 0 . 0 LITERATURE CITED
Charnov, E.L. 1973. Optimal f o r a g i n g : some t h e o r e t i c a l e x p l o r a t i o n s . Ph.D. T h e s i s , U n i v e r s i t y of Washington.
95 PP-
C r a i g h e a d , F.C. 1940. Some e f f e c t s of a r t i f i c i a l d e f o l i a t i o n o n p i n e a n d l a r c h . J. For. 38: 858-888.
G r i f f i t h s , K . J . and C.S. Ho l l ing . 1969 . A c o m p e t i t i o n s u b m o d e l f o r p a r a s i t e s a n d p r e d a t o r s . C a n . E n t . 101: 785-818.
Habe r , G.C. 1977 . Soc io -eco log ica l dynamics of wolves and . p r e y i n a s u b a r c t i c e c o s y s t e m . Ph.D. T h e s i s , U n i v e r s i t y of B r i t i s h C o l u m b i a .
H o l l i n g , C.S. 1959. Some c h a r a c t e r i s t i c s of simple t y p e s of p r e d a t i o n a n d p r a r a s i t i s m . C a n . E n t . 9 1 : 3 8 5 - 3 9 8 .
H o l l i n g , C . S . , ed . 1978 . Adap t ive Env i ronmen ta l Asses smen t and Management. John Wiley &I S o n s , N e w Yrok. 377 pp.
Horn, H.S. 1 9 7 1 . The Adapt ive Geometry of Trees. Monogr. in Pop. Biol. No. 3, Princeton University Press.
144 pp.
I v l e v , V.S. 1 9 6 1 . E x p e r i m e n t a l E c o l o g y o f t h e F e e d i n g of F i s h e s . Yale U n i v e r s i t y Press , N e w Haven. 302 pp.
McConnell , B.R., and J . G . Smi th . 1970. Response of under- s t o r y v e g e t a t i o n t o p o n d e r o s a p i n e t h i n n i n g s . J . Range Manage. 23: 208-212.
- 139 - M i t c h e l l , K.J. 1 9 7 2 . S u p p r e s s i o n a n d d e a t h . I n : T.G.
Honer , ed . P roceed ings of a Tree Growth S imula t ion Workshop. F o r e s t Management I n s t i t u t e , Ottawa. I n t e r n a l R e p t . , FMR-25. pp. 71-78.
M i t c h e l l , K.J. 1975 . Dynamics and s imula t ed y i e ld of D o u g l a s f i r . F o r . Sci. Monogr. No. 17 .
Noy-Meir, I. 1 9 7 5 . S t a b i l i t y of g r a z i n g s y s t e m s : a n a p p l i c a t i o n o f p r e d a t o r - p r e y g r a p h s . J. Ecol. 63: 459-481.
Shephe rd , R . , J. Harr i s , A. Van S i c k l e , L . F i d d i c k , L. McMullen. 1 9 7 7 . S t a t u s of w e s t e r n s p r u c e budworm o n D o u g l a s F i r i n B r i t i s h C o l u m b i a . C a n . F o r . S e r v . F o r . Pest Rept . Pac . For. R e s . C e n t r e . Victor ia , B.C.
Solomon, M.E. 1949. The n a t u r a l con t ro l of animal p o p u l a t i o n s . Anim. Ecol. 18: 1-35.
S t a g e , A.R. 1973. Prognosis model for s t a n d d e v e l o p m e n t . U.S. Dept. Agr. For. S e r v . Res. Pap. INT-137. 32 pp.
Thomas, J.W., H. Black , R . J . S c h e r z i n g e r , a n d R . J . P e d e r s e n . 1979. Deer and E l k . I n : J.W. T h o m a s , e d . , W i l d l i f e H a b i t a t s i n Managed Forests . U.S. Dept. Agr. For . Ser. Agr. Handbook No. 553, pp. 104-127.
Walters, C . J . , R. H i l b o r n , R.M. Peterman. 1975. Computer s i m u l a t i o n o f b a r r e n - g r o u n d c a r i b o u d y n a m i c s . Ecol. Model. 1: 303-315.
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L i s t of ParticiFnts
Name
Peter Ackhurst
-
Fred Bunnell
Wayne Combs
Rick Davies
Don Eastman
Rick Ellis
Robert Everitt
A1 ton Hares tad
Doug Janz
Bob Jones
>like Jones
Jerry Kennah
Affiliation Telephone Number
Ministry of Forests - 668-2570 Van., 355 Burrard Street, Vancouver, B . C . Faculty of Forestry, 228-5724 University of British Columbia
B.C. Forest Products Box 130 Crofton, B.C. VOR 1RO
Minis try of Environment, 758-3951 Fish & Wildlife, Kanairno
Minis try of Environment, 387-5910 Fish & Wildlife, Victoria
Ministry of Forests, R.B. 387-3144 1450 Government Street , Victoria, B.C.
ESSA Ltd. 678 West Broadwy , Vancouver, B.C.
872-0691
B . C . Provincial Xuseum, 387-3649 Victoria, B.C.
Minis try of Environment, 758-3951 Fish & Wildlife, Kanairno
Minis try of Forzs ts , S .B . , 387-3918 1450 Government Street , Victoria, B . C . ESSA Ltd. 678 Nest Broadwzy , Vancouver, B.C.
Ministry of Forests, Van., 355 Burrard S t r z s t , Vancouver, B.C.
872-0691
- 141
Name
Vlad Korelus 7
s teve Lorimer
R . XcLaughl in
Pete NcNamee
Ken Ni tchell
Doug Xorrison
Steven Northway
Fred Xuszdorfer
Brian Nyberg
K i m Scoullar
Michael Staley
HoIcard S tauf fer
Affiliation
Pacific Forest Products, 8067 East Saanich Road, Saanichton, B . C . VOS 1NO Crown Zellerbach, Box 609 Iadysmi th , B . C . YacMillan Bloedel 65 Front Street, Nanaimo, B.C.
ESSA Ltd., 678 West Broadway Vancouver, B.C. V5Z 1G6
Ministry of Forests - R.B. 1450 Government Street, Victoria, B . C . Minis try of Environment, Fish & Wildlife, Nanaimo
MacVi 1 lan Bloedel 65 Front Street, Nanaimo, B. C .
Telephone Number
652-4023
i
245-221 1
872-0691
758-3951
Ministry of Forests - Van., 668-2891 355 Burrard Street, Vancouver, B.C.
Ministry of Forests - Van., 668-2570 355 Burrard Street, Vancouver, B.C.
S O 6 - 5775 Toronto Road 224-1158 Vancouver, B.C.
ESSA Ltd . 678 West Broadway, Vancouver, B.C. V5Z 1G6
Ninistry of Forests - R . 3 .
872-0691
853 Byni Street, Victoria, B.C.
" 142 -
- Name Affiliation Telephone Number
Susan Stevenson 101,Burden Street, 564-5695 Prince George, B.C.
David Tait ESSA Ltd./U.B.C. 228- 5724 Faculty of Foresfry University of Rrltlsh Cdunbia
Marika H. Townshend Minis try of Environment, Fish & Wildlife 2569 Kenworth Rord, Nanaimo, B.C.
Bernie h'aatainen MacYillan Bloedel, 65 Front Street, Nanaimo, B.C.
758-3951
753-1 112
- 143 -
APPENDIX - CoMMENTS OF MXXSHOP PARTICIPANTS ON THE DRAFT REPOEYT
Veqetaticn S u h d e l ,
Arboreal Lichens, p. 18 , Sec. 3.4 Lichens need l i g h t and after thinning,with more l igh t , l ichen growth shculd be greater.
Foraqe Available for Brawsinq, p.21, Sec. 3.5 Forage species physical availability is probably 75% - 90%.
Fertilizatim, p.21, Sec. 3 . 7
The response to fer t i l izat im is dependant on forest density. If the forest is thinned, the assumption holds. If the forest is unthinned, the assumption is false, as the tree cancpy w i l l
cut the forage. ' be greatly increased. i n density w i t h fertilization, shading
Effects of Silvicultural Practices, p.88, Sec. 8.2.1.3 Spzies ccmposition w i l l change w i t h silvicultural practices, as will nutrient levels and palatability. Nanaged stands cannot be equated to natural stands which w i l l tend to have a higher live crown ratio.
Alternate Representation of Vegetaticn, p.88, Sec. 8.2.1.4 I t is very d i f f i c u l t to simplify as there are, i n reality, scores of habitats which result i n significant changes in vegetation. Vegetation also is dependant on overstory density due to tolerance to shading of sane species. Micro and macro climate must be considered i n vegetation groupings. There is no more consistency of value as f o d or of response to management wi th in physiognanic categories than between these categories. These relationships are camplex. Too much aggre- gation takes the result too far f r m the real world.
Veaetatim, p.118, Sec. 8.4.1 On the contrary, focd has to be limiting.
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Curpetition, p.125, Sec. 9.2.1 Also, the effect of forest develqmnt m forage prcductim and availability must be cmsidered.
Timber Submcdel
Chanqes i n Grawth, p.25, Sec. 4.1.1.2 If repeated for years, heavy brawsing w i l l substantially inf hence stand develapment and yield.
Heiqht, p.27, Sec. 4.2 Very dense understory certainly affects tree grcrwth.
Grawth, p.70, Sec. 8.2.2.1.2 Brwsing, via stem deformatim, can cause value losses i n the bottan of a tree, but the relationship is basically a grawth retardatim situatim. Heavily browsed trees often grow dramatically Once the leaders get beyond reach. Permanent damage to stem form is unlikely unless we measure limbyness as a result of lower density due to browsing.
Direct Effects of Wildlife p.90, Sec. 8.2.2.2 Effects are usually randan affecting single stems, not the entire stand. L m priority. The usual densities of deer and elk aren't great enough to cause trampling losses.
Effects of Silvicultural Practices, p. 92, Sec. 8.2.2.3 Spacing and thinning may change nutrient cycling thereby changing the quality of vegetation.
Influence of Other Veqetation on Timber, p.92, Sec. 8.2.2.5 Th i s happens a t an early age, when seedlings and canpeting vegetation are a t the same root depth. Not cn forest lands. Foresters w i l l get rid of brush quickly i f herbicides are available.
- 145 - Canpetition f r m Other Vegetat im, p.127, Sec. 9.3.3
Juvenile spaced stands w i t h heavy understory respond very s l w l y to spacing as the understory is more capable of rapidly spreading to occupy the site and use the. iadditimal water and nutr ients . .
Deer Suhncdel
Sncw Reaching the Canopy, p.33 , Sec. 5.1 Accumulation and ablat icn prccesses are important because they can change the amcunt of food available t o ungulates.
Snow Reaching the Ground, p.35, Sec. 5.1.2 Fig. 5.1 is not true; even when c r m closure is 1, branches eventually bend, sncw s l ides o f f and reaches the grand. A crown cw hold cnly a ce r t a in amount of sncw (mass) before it either slides d m or breaks the tree. I t depends cn the quality of the sncw too.
Food Cwered by Snw, p.35, Sec. 5.1.3 Improvements could be made by expressing the re la t imship as nm-linear curves. Thus threshold depths could ke identified. We used a uniform dis t r ibu t ion because the programmer thcught it too d i f f i c u l t t o use nm-linear relaticnships. They do move during winter , but we d m ' t know what t r iggers movements .
Snow In t e rcep t im, p.93, Sec. 8.2.3.1.1 Wind also strongly affects s n w through f a l l and depth patterns. Snw qua l i t y is important too. I t is important to recognize that winter range must have sncw interception.
-
Mwement, p.94, Sec. 8.2.3.2 I f movements are to be made more sens i t ive to snow then the snow mcdel must be run cn a dai ly basis .
- 146 - Feedinq, p.96, Sec. 8.2.3.3
Depending m availability, preferences change markedly.
Survival and Reproductim, p.97, Sec. 8.2.3.4 Deer c d i t i m entering winter range is dependant on food quality cn sumner range. Reproductive success is also dependant cn surmer range quality.
- Snow, p.127, Sec. 9.4.1 T ~ E effect of s n d a l l m feed may be fairly easily tested in the field. Sequence and processes of accumulation and ablaticn can determine the rate at which f ccd becanes buried and the duraticn of the burial.
Survival and Reprductim, p.Ul, Sec. 9.4.4 Or, winter conditims may weaken deer and result i n even greater predatian rates.
E l k Submcdel
Escape Cover, p. 97, Sec. 8.2.4.1 1
Research shows clearly a "marked distance fran cover/feeding use" relatimship. After abcut 600 f t . fran cover, l i t t l e use is made of forage. Vis ib i l i ty is a starting point - it works for escape fran humans.
E f f e c t s of Sncw, p.131, Sec. 9.5.1 Small elk may have easier t ra i ls but they end up w i t h focd that has keen lef t over by the large elk. I t may be of poorer quality than that obtained by the large elk.
Emigraticn, p.I.34, Sec. 9.5.5 Canpetitim for available food and l m r e d foal quality cn c r a d d ranges are certainly reasms for m m e n t by other members of the genus Cervus.
- 147 - Predation and Hunting Suhodel
Functional Responses, p.135, Sec. 9.6.1
Presumably the more fawns, the greater likelihood of a bear finding sane.
Numerical Responses, p. 136, Sec. 9.6.2 Cougar density is probably dependant on elk populations because they are strict carnivores. Bear are cmmivorous and only opportunistic carnivores.
If either a numerical or functional response is to be described, one must also estimate deer densities.