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thesis entitled

THE JACK PINE RESOURCE IN MICHIGAN: AN

ASSESSMENT OF VOLUME, GROWTH, MORTALITY, AND

COARSE WOODY DEBRIS

presented by

Andrew Thomas Klein

has been accepted towards fulfillment
of the requirements for the

degree In Foresty

 

 

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THE JACK PINE RESOURCE IN MICHIGAN: AN ASSESSMENT OF VOLUNIE,
GROWTH, MORTALITY, AND COARSE WOODY DEBRIS

By

Andrew Thomas Klein

A THESIS

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

MASTER OF SCIENCE
Department of Forestry

2004

 

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ABSTRACT

THE JACK PINE RESOURCE IN MICHIGAN: AN ASSESSMENT OF VOLUNIE,
GROWTH, MORTALITY, AND COARSE WOODY DEBRIS

By

Andrew Thomas Klein

Jack pine (Pinus banksiana Lambert.) is economically and ecologically important
in the Lake States region and throughout much of Canada. The current state of the jack
pine resource was assessed in six regions in Michigan and one region in Wisconsin by
quantifying standing live and dead volume, mortality, top-kill, annual radial growth
patterns, and coarse woody debris volume in one 0.01 ha circular plot per stand. Overall,
live and dead volume was higher on state land in the western Upper Peninsula of
Michigan than in the other six surveyed regions averaging 448.5 m3/ha live volume and
68.4 m3/ha dead volume. Accumulation of coarse woody debris volume was highest in
the Ottawa National Forest (64.2 m3/ha) and the Huron-Manistee National Forest (60.1
m3/ha). Stand age had the most consistent relationship with all variables except radial
growth rates across all regions. Stands 50+ yrs old generally had higher levels of standing
volume, more mortality, and higher accumulation of coarse woody debris volume than
younger stands. Under-stocked stands had less volume, mortality, and lower amounts of
coarse woody debris volume than well-stocked or over-stocked stands. Patterns among
standing volume, mortality, radial growth rates, and site index were unclear within
regions. Among crown classes, mortality was generally higher in intermediate and
suppressed trees than dominant trees. However, more dead volume was concentrated in

dominant trees than in intermediate or suppressed trees.

To my Mom, Judy Kay Klein
(1954 — 1995)

ACKNOWLEDGEMENTS

I would like to thank Dr. Deborah G. McCullough and Dr. Larry A. Leefers for
their patience, guidance, and friendship during the course of this study. I would also like
to thank my graduate committee member, Dr. Donald 1. Dickmann. Other thanks go
towards Dr. Daniel Keathley, Chairperson of the Dept. of Forestry at Michigan State
University, who provided appreciated advice and encouragement, and to other faculty
members in the Dept. of Forestry who provided welcome encouragement, especially Dr.
Michael Walters and Dr. Karen Potter-Witter. I am grateful to field cooperators who
provided assistance with gathering compartment maps and stand inventory data used to
locate research plots. Special thanks go to Bob Heyd, Les Homan and Roger Mech with
the Michigan Department of Natural Resources, Doug Born, Larry Melstrom, Charlotte
Bofinger, Quent McNichols, Steve Katovich, and Linda Haugen with the USDA Forest
Service, and Tim Beyer with the Wisconsin Department of Natural Resources. I would
also like to thank Dr. Raymond Miller, and everyone at the Upper Peninsula Tree
Improvement Center for their assistance in measuring annual radial growth data. Finally,
I need to thank my family, who have all been there when I needed them throughout this
project. Special thanks go to my fiancee Elizabeth McDonald, my daughter Emma Klein,
and my Dad, Bill Klein. They have given me tremendous support, encouragement, and
love in the last three years, which has been greatly appreciated. Funding for this study

was provided by the USDA Forest Service PI‘IPS program.

 

 

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TABLE OF CONTENTS

LIST OF TABLES .......................................................................................................... vii
LIST OF FIGURES .......................................................................................................... ix
INTRODUCTION ............................................................................................................. 1
Thesis Objectives ......................................................................................................... 1
Thesis Organization ...................................................................................................... 2
CHAPTER 1
AN ASSESSMENT OF MORTALITY, TOP-KILL, AND STANDING LIVE AND
DEAD VOLUME IN MICHIGAN AND WISCONSIN JACK PINE STANDS ............. 4
Introduction .................................................................................................................. 4
Methods ........................................................................................................................ 8
Study Sites ............................................................................................................... 8
Stand Selection and Establishment of Plots ............................................................ 8
Stand Composition, Mortality, and Top-Kill .......................................................... 9
Live and Dead Volume ......................................................................................... 10
Statistical Analysis ................................................................................................ 11
Results ........................................................................................................................ 14
Jack Pine Volume, Mortality, and Top-Kill .......................................................... 14
Mortality, Dead Volume, and Tree Characteristics ............................................... 15
Stand Inventory Variables ..................................................................................... 16
Discussion .................................................................................................................. 22
Jack Pine Volume, Mortality, and Top-Kill .......................................................... 23
Mortality, Dead Volume, and Tree Characteristics ............................................... 26
Mortality, Live and Dead Volume, and Stand Inventory Variables ...................... 26
Summary and Conclusions .................................................................................... 28
CHAPTER 2
ANALYSIS OF ANNUAL RADIAL GROWTH RATES OF JACK PINE ACROSS
NORTHERN MICHIGAN AND WISCONSIN ............................................................. 44
Introduction ................................................................................................................ 44
Methods ...................................................................................................................... 47
Study Sites ............................................................................................................. 47
Stand Selection ...................................................................................................... 47
Tree Core Extraction ............................................................................................. 48
Annual Radial Growth and Jack Pine Budworm Defoliation ............................... 50
Statistical Analysis ................................................................................................ 51
Results ........................................................................................................................ 54
Overall Growth of Live Jack Pine ......................................................................... 54
Regional Differences ............................................................................................ 54
Stand Inventory Variables ..................................................................................... 55

 

 

 

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Effects of Jack Pine Budworm Defoliation ........................................................... 58

Discussion .................................................................................................................. 60
Total Growth of Jack Pine from 1991 — 2000 ....................................................... 61
Regional Growth Rates from 1991 — 2000 ........................................................... 62
Summary and Conclusions .................................................................................... 64

CHAPTER 3

ACCUMULATION OF COARSE WOODY DEBRIS IN MICHIGAN AND
WISCONSIN JACK PINE STANDS IN RELATION TO STAND AND SITE

VARIABLES .................................................................................................................. 67
Introduction ................................................................................................................ 67
Methods ...................................................................................................................... 70
Study Sites ............................................................................................................. 70
Stand Selection ...................................................................................................... 70
Measurement of Coarse Woody Debris ................................................................ 71
Statistical Analysis ................................................................................................ 72
Results ........................................................................................................................ 74
Abundance and Volume of Coarse Woody Debris ............................................... 74
Stand Inventory Variables and Coarse Woody Debris Accumulation .................. 75
Discussion .................................................................................................................. 77
Coarse Woody Debris Volume in Michigan and Wisconsin ................................ 77
Coarse Woody Debris in Relation to Stand Variables .......................................... 78
Ecological Importance of Coarse Woody Debris .................................................. 80
Summary and Conclusions .................................................................................... 82
CONCLUSIONS, LIMITATIONS, AND FUTURE RESEARCH ................................ 90
Conclusions ................................................................................................................ 90
Management Recommendations ........................................................................... 90
Limitations ................................................................................................................. 92
Future Research .......................................................................................................... 92

APPENDIX A ................................................................................................................. 96
Long-term Impact Plot Locations .............................................................................. 96

APPENDIX B ............................................................................................................... 110
Measurement Conversions ....................................................................................... l 10

REFERENCES CITED ................................................................................................. 1 12

vi

LIST OF TABLES

Table l-l — Description of terrain, soils, and location of regions surveyed. ................. 30

Table 1-2 — Characteristics used to stratify jack pine stands for evaluation of jack pine
live and dead volume (m3/ha), mortality and top-kill, and total and average annual radial
growth rates from 1991 - 2000 in six regions of Michigan and one region of Wisconsin.
......................................................................................................................................... 32

Table 1-3 — Number of jack pine stands and trees and characteristics of stands surveyed
in seven regions of Michigan and Wisconsin to assess standing live and dead volume
(m3/ha), mortality and top-kill, total and average annual radial growth rates of jack pine
trees, and coarse woody debris volume (m3/ha). ............................................................ 33

Table 1-4 — Comparison of mean (t SE) volume (m3/ha) of live and dead jack pine trees
per stand, mean (t SE) percentage of dead jack pine trees, and mean (t SE) percentage of
jack pine trees with dead tops in the seven surveyed regions. ....................................... 34

Table 1-5 — Comparison of the percentage of dead volume (m3/ha) and percentage of jack
pine trees that were dead in dominant, intermediate, and suppressed crown classes in the
seven surveyed regions. .................................................................................................. 35

Table 1-6 - Number of stands sampled and Spearman’s non-parametric correlations (rs)
between live volume (m3/ha), dead volume (m3/ha), and stand characteristics in each
region. ............................................................................................................................. 36

Table 1-7 — Results of linear regression analysis for jack pine live volume (m3/ha) and
dead volume (m3/ha) predicted by stand age (yrs), site index (SI) (m), and basal area
(BA) (mtha) within each region, and by stand age (yrs), site index (51) (m), basal area
(BA) (m2/ha), land ownership, and physio-region among all regions. .......................... 37

Table 1-8 — Comparison of the mean (t SE) ratio of dead volume to live volume (m3/ha)
per stand grouped by stand age (yrs), site index (m), and basal area (mzlha) in the seven
regions. ........................................................................................................................... 41

Table 2-1 — Comparison of average total growth rates (mm) from 1991 — 2000 (t SE)
between live dominant, and live intermediate and suppressed trees among all region, and
within each region. ......................................................................................................... 65

Table 2-2 — Comparison of mean average growth rates (mm) from 1991 — 2000 (t SE)

for live dominant jack pine trees by tree age (yrs), site index (In), and stand basal area
(mzlha) categories among all regions, and within regions. ............................................ 66

vii

Table 3-1 — Characteristics used to stratify jack pine stands for evaluation of coarse
woody debris volume (m3/ha) in six regions of Michigan and one region of Wisconsin. 83

Table 3-2 — Number of stands sampled and Spearman’s non-parametric correlation
coefficients (rs) between coarse woody debris volume (m3/ha) and stand characteristics
among the seven regions. ............................................................................................... 84

Table 3-3 — Volume of coarse woody debris (m3/ha) for selected forest types of North

America. Coarse woody debris volume was calculated from an equation derived by
Wagner (1968)“. ............................................................................................................. 85

viii

 

 

 

 

 

  

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Figure 1-1 - Locations of permanent plots surveyed in six regions of Michigan and one
region in Wisconsin from 2001 to 2003. ........................................................................ 42

Figure 1-2 — Mean (1 SE) percentage of dead jack pine trees in seven regions in
Michigan and Wisconsin grouped by (A) stand age, (B), site index (m), and (C) basal
area (mzlha). ................................................................................................................... 43

Figure 3-1 - Mean (i SE) volume (m3/ha) of coarse woody debris in jack pine stands in
seven regions in Michigan and Wisconsin. .................................................................... 86

Figure 3-2 - Distribution of coarse woody debris (m3/ha) by diameter class (cm) in seven
regions in Michigan and Wisconsin. .............................................................................. 87

Figure 3—3 - Distribution of coarse woody debris volume (m3/ha) by decay class in the
seven regions of Michigan and Wisconsin. Low decay refers to recently fallen pieces
with fine twigs and bark fully intact; moderately decayed pieces had little or no bark or
fine twigs; highly decayed pieces had obvious deterioration of woody tissue. ............. 88

Figure 3-4 -— Mean (1 SE) volume (m3/ha) of coarse woody debris in seven regions in
Michigan and Wisconsin grouped by (A) stand age (yrs), and (B) basal area (m2/ha). .89

 

 

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INTRODUCTION

Thesis Objectives

Baseline data was collected from jack pine (Pinus banksiana Lambert.) stands to
assess the current state of jack pine in northern Michigan and Wisconsin to establish a
framework to monitor long-term impacts of jack pine budworm (Choristoneura pinus
pinus Freeman) (JPBW), an important defoliator of jack pine. The long-term goal for
collection and analysis of this data is to validate and modify an existing jack pine
management model, the Lake States Jack Pine Budworm Decision Support System
(Conway et al. 1998), which was developed from empirical data collected in the Raco
Plains area of the Hiawatha National Forest in the eastern Upper Peninsula of Michigan
(Conway et al. 1999a; Conway et al. 1999b; McCullough et al. 1996). This study is the
first to quantify and compare stand-level impact data among several different regions in
the Lake States area.
The overall objectives of this study were to:

1. Establish a network of permanent plots across seven regions in Michigan and
Wisconsin to gather baseline data to assess the current state of jack pine and
monitor long-term impacts of J PBW defoliation.

2. Quantify jack pine mortality, top—kill, standing volume, annual radial growth
rates, and accumulation of coarse woody debris among surveyed regions of jack
pine. These variables were of interest, because they could be affected by JPBW

defoliation.

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3. Evaluate relationships between site and stand variables (tree age, stand age, site
index, and basal area), and jack pine mortality, top-kill, standing volume, annual
radial growth rates, and accumulation of coarse woody debris.

Specific hypotheses are as follows, and each is given as a research hypothesis:

H]: Jack pine mortality, top-kill, standing volume, annual radial growth rates, and

accumulation of coarse woody debris differ among the seven surveyed regions in

Michigan and Wisconsin.

H2: Jack pine mortality, standing volume, annual radial growth rates, and

accumulation of coarse woody debris are related to tree, stand, and site variables

within the seven surveyed regions in Michigan and Wisconsin.

H3: Relationships between jack pine mortality, standing volume, annual radial

growth rates, and accumulation of coarse woody debris and tree, stand, and site

variables differ among the seven surveyed regions in Michigan and Wisconsin.
Thesis Organization

This thesis is divided into three chapters. Some repetition may occur in each
chapter, particularly the introduction and methods sections. In the first chapter,
standing live volume, mortality, top-kill, and standing dead volume are quantified
and compared among regions. All impact variables, excluding top-kill, are
examined in relation to tree and stand characteristics within regions, and
relationships between live and dead volume and stand variables, land ownership,
and regional location are assessed. The second chapter describes patterns of annual
radial growth, and compares those patterns among regions. Annual radial growth

data is then examined in relation to tree and stand characteristics within regions. In

the third chapter, accumulation, size, and decay level of coarse woody debris
volume are quantified and compared among regions, and then examined in relation
to stand age and basal area. The major results for this study and areas for future
research of the impact and management of the JPBW in the Lake States are
presented in a concluding chapter. Finally, Appendix A lists the geographical and
plot center locations in all seven surveyed regions, while Appendix B lists

measurement conversions related to this study.

 

 

 

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CHAPTER 1

AN ASSESSMENT OF MORTALITY, TOP-KILL, AND STANDING LIVE AND
DEAD VOLUME IN MICHIGAN AND WISCONSIN JACK PINE STANDS

Introduction

Jack pine (Pinus banksiana Lambert) is an important resource in the Great Lakes
region of the US. and throughout much of Canada. In Michigan and Wisconsin, jack pine
forests occur on nearly 485,000 ha (1.2 million acres) (Piva 1997). Jack pine is a rapid
colonizer in early forest succession, tolerates relatively poor, sandy soils, and has
qualities desirable for the commercial pulpwood industry (Rudolph and Laidly 1990).
Jack pine forests provide habitat for game and non—game species, including the
endangered Kirtland’s Warbler (Dendroica kirtlandii), and also provide recreational
opportunities such as hunting, camping, and bird watching (Benzie 1977). More than
270,000 cords of jack pine are annually harvested for wood fiber, amounting to a
stumpage value of nearly $10.1 million (USDA-Forest Service 2002). Management
intensity in jack pine forests has escalated because of the enhanced economic value of
jack pine pulp, which sold at roughly $4/cord in 1991 and $35/cord in 2002 (McCullough
and Leefers 2000; USDA-Forest Service 2002), leading to more emphasis on
optimization of harvest rotations.

In northern Michigan and Wisconsin, jack pine forests experience multiple natural
disturbances, such as wind, heavy snow, or fire, which can injure trees or cause tree
death. At present, major fires occur at approximate 30 year intervals (Rouse 1986), while
strong wind events can be localized or widespread (Zhang et al. 1999). Return intervals

for catastrophic winds can be measured in centuries, but localized storms with winds

 

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sufficient to break or uproot trees in individual stands can occur every decade or less
(Canham et a1. 2001; Foster and Boose 1992).

Biotic disturbances, including insect outbreaks, can also affect tree mortality by
killing trees or branches, or predisposing trees to attack by secondary pests (Conway
1998). Outbreaks of jack pine budworm (Choristoneura pinus pinus Free.) (JPBW), a
prominent native defoliator, occur at six to ten year intervals, and typically persist two to
four years (McCullough 2000). Heavy defoliation can result in death of the terminal
leader (top-kill), tree mortality, and tree volume loss (Graham 1935; Gross 1992; Gross
and Meating 1994; Kulman et al. 1963). Mortality typically accumulates for two to three
years following the collapse of high density JPBW populations, and up to 16% of trees
can die following an outbreak (Conway et al. 1999a; Gross 1992; Gross and Meating
1994; McCullough et al. 1996).

Silvicultural guidelines have been developed to reduce tree mortality and volume
loss caused by JPBW defoliation. Current recommendations include prioritizing over-
mature stands for harvest or salvage, maintaining shorter rotation ages on lower quality
sites than on higher quality sites, and maintaining proper stocking levels (16.1 — 25.3
mZ/ha basal area) (Benzie 1977). Other recommendations for managing the vulnerability
of jack pine stands to J PBW impact include reducing the proportion of suppressed trees
in a stand, maintaining within stand tree diversity, and decreasing the amount of stand
edge (Kouki et al. 1997; McCullough et al. 1994).

Several previous studies have addressed impacts of JPBW, including jack pine
mortality and standing volume loss. Kulman et al. (1963) and Gross (1992) reported jack

pine mortality within crown classes in Minnesota and Ontario, respectively. Gross (1992)

noted factors other than JPBW that contributed to mortality of intermediate and
suppressed trees in jack pine stands. A few studies have focused on the economic impacts
that JPBW defoliation can have on jack pine stands (Conway et al. 1999a; N yrop et al.
1983; Rose 1974). A few investigations have also looked at the growth and productivity
of jack pine in relation to soil and site characteristics. Studies in Canada found that the
growth of jack pine was more productive in soils with greater moisture-holding capacity
and with a lower percentage of glacial sands (Beland and Bergeron 1996; Hamilton and
Krause 1985). Pawluk and Ameman (1961) also found that jack pine stands growing in
soils with higher moisture content, as well as higher cation exchange capacities in the
Lake States region were more productive than stands growing in droughty soils with
higher contents of coarse sand. No previous studies, however, have evaluated potential
differences in jack pine mortality, top-kill, or standing live and dead volume among
regions.

A study was inititated in 2001 to assess the current status of the jack pine resource
and to collect baseline data to quantify long-term impacts of JPBW defoliation in six
regions of northern Michigan and one region in Wisconsin. Within each region, I
established a network of permanent plots to: (1) quantify jack pine mortality, top—kill, and
standing live and dead volume; (2) compare these variables among surveyed regions; and
(3) evaluate relationships between site and stand variables and jack pine mortality,
standing live volume, and standing dead volume. I hypothesized that jack pine mortality,
top-kill, and live and dead volume would differ among the seven regions because of
variations in management guidelines among regions, site characteristics, climatic factors,

and stand structure. Secondly, I hypothesized that mortality and live and dead volume

 

 

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Methods

Study sites

Permanent plots were established from May to August in 2001 — 2003 in six
regions of northern Michigan and one region in Wisconsin to assess the current state of
jack pine and to monitor long-term impacts of JPBW, including mortality, top-kill, and
volume loss. I selected these seven regions based upon the relative abundance of jack
pine in the area, and the historical importance of JPBW outbreaks. These regions
included state land in the north-central Lower Peninsula of Michigan (NL—State), the
Huron-Manistee National Forest in the northeastern Lower Peninsula (NL-HNF), the
Raco Plains area of the Hiawatha National Forest in the eastern Upper Peninsula of
Michigan (UP-Raco), two regions of state land in the Upper Peninsula (UP-East and UP-
West), the Ottawa National Forest in the western Upper Peninsula (UP-ONF), and state
land in west-central Wisconsin (WI-State) (Figure 1-1). Soils were generally moderately
drained to droughty, except for two regions (UP—East and WI-State), which contained
areas of poorly drained peat soils (Table 1-1). The terrain was generally level to gently
sloping, with moderately steep areas in the UP-West and UP-ONF regions, while the WI-

State region had scattered sandstone mounds (Table 1-1).

Stand selection and establishment of plots

A stratified random sampling approach was used to select jack pine stands in each
of the seven regions for sampling. Stratification was based on stand age, site index, and
basal area (Table 1-2), because of their documented relationship with tree mortality and

jack pine volume (Conway et al. 1999a, 1999b; McCullough et al. 1996), and because

 

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these variables are routinely collected and used operationally by forest managers. These
variables were acquired for all jack pine stands from each respective forest management
agency’s database. After stands were grouped by age, site index, and basal area, I
randomly selected jack pine stands from each group, based on the percentage of the total
number of stands that were assigned to each stand variable category. Number of stands
used per region ranged from 35 stands in the NL-State region to 78 stands in the UP—Raco
region. If stands had been recently harvested or were not accessible, a replacement stand

was selected from the same group.

Permanent plots were established in a total of 356 jack pine stands encompassing
6,374 ha (15,750 acres) in northern Michigan and Wisconsin from 2001 to 2003 (Table 1—
3). Stand age ranged from 10 yr in the UP-ONF region to 117 yr in the UP-Raco region.
Site index (at 50 yrs) ranged from 9.2 m (30 ft) in the UP-East region to 22.3 m (73.2 ft)
in the UP-ONF region and basal area ranged from 2.3 m2/ha (10 ftZ/ac) in the NL-State,
NL-HNF, UP-East, and WI-State regions to 50.6 mZ/ha (220 ftZ/ac) in the UP-Raco

region (Table 1-3).

Stand composition, mortality, and top-kill

One circular, 0.01 ha (0.025 acre) fixed-radius plot was randomly located in each
stand using compartment maps overlaid with a transparent grid. Grid cells were selected
at random for plot center location, and a compass and pacing was used to establish the
permanent plot center in the field. I established one survey plot per stand in all regions
except NL—State. Multiple plots per stand were established in the NL-State region in 2001
to assess within—stand variability. Within each of the NL-State stands, I established at

least two plots; three plots for stands larger than 8.5 ha (21 acres), four plots for stands

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larger than 20.7 ha (51 acres), and five plots for stands larger than 40.5 ha (100 acres).
For analysis, I used mean values, based on the number of established plots per stand at
the NL-State region. In all other regions, I chose to establish one plot per stand to ensure
that a wide range of jack pine forest could be surveyed, and jack pine stands were
generally fairly small (mean and median stand acres = 44 and 32, respectively), and tree

age and stocking tends to be fairly homogenous within stands.

Within each plot, I measured the height, diameter at breast height (DBH; 1.37 m
above ground), length of the dead terminal leader on top-killed trees, dominance class,
and crown ratio of all jack pine trees. This study was limited to analysis of jack pine trees
only, so other associated species in each plot were not measured. The percentage of jack

pine trees that were dead or top-killed was calculated for each plot.
Live and dead volume

The volume of each jack pine tree (m3) per plot was calculated using the standard

jack pine volume equation from the LS-TWIGS model:
V = 43*SIAO'2‘W5 * (1 — EXP(-l.0*O.0633760)*D))A3'398‘

where V = jack pine volume (m3), D = DBH (cm), and SI = site index (m). Live volume,
including standing live and top—killed jack pine trees, and dead volume, representing
standing dead jack pine trees, was determined. Volume of jack pine trees measured
within each plot was summed, and then expanded to a per hectare value to estimate stand
volume. In the NL-State region, where multiple plots per stand were established, jack
pine live and dead volumes were summed for all plots then divided by the number of

plots to generate a mean jack pine volume per stand.

10

Statistical analysis

Stand level estimates of mortality, top-kill, and live and dead volume were
grouped for analysis based on categories or threshold values for age, site index, and basal
area typically used for jack pine management in the Lake States (Table 1-2) (Benzie
1977), and previous studies that related these variables to JPBW impact (Conway et al.
1999a, 1999b; McCullough et al. 1996). Stands were divided into two categories based
on age (< 50 yrs, 50+ yrs), and three categories based on basal area (< 16.1 mzlha (< 70
ft2/ac), 16.1 — 25.3 mzlha (70 -— 110 ft2/ac), > 25.3 m2/ha (> 110 ft2/ac)) (Benzie 1977;
Conway 1999a; McCullough et al. 1996). Comparisons of mortality and dead volume
among basal area categories were made using data acquired from each forest manager’s
inventory database. I then calculated stand basal area values using jack pine data from
live dominant trees, which were collected from my permanent plots and compared those
values with the basal area data used for the mortality and dead volume comparisons to
check for accuracy of the manager’s inventory databases using a standard t-test (p <

0.05). Basal area values from inventory data were used in analyses.

Categories for site index were based on mean and median site index of jack pine
stands per region. Mean and median site index values ranged from 14.7 m (48.2 ft) to
15.3 m (50.2 ft) for the NL-State, NL-HNF, UP-Raco and UP-East regions (Table 1-3),
so I chose 14.9 m (49 ft) as the division between low and high quality site index for these
regions. Mean and median values for the UP-ONF and WI-State regions ranged from
16.4 m (53.8 ft) to 17.2 m (56.3 ft), so I chose 16.8 m (55 ft) as the division between low

and high quality site index for these regions. Mean and median values for the UP-West

11

region ranged from 18.0 m (59.1 ft) to 18.3 m (60 ft), so I chose 18.3 m (60 ft) as the

division between low and high quality site index (Table 1-3).

A test of normality for mortality data was significant in the NL-State and W1-
State regions using the Shapiro-Wilk procedure (Kuehl 2000). For these regions, I
analyzed associations between mortality data and stand age and site index categories
using a t-test, and basal area categories using one-way analysis of variance (ANOVA)
procedures. If the ANOVA test was significant, treatment means were separated using the
Fisher’s least square difference procedure (Kuehl 2000) at the 0.05 level of confidence
Log transformation normalized live volume data in all regions except the UP-Raco and
UP-ONF regions, and dead volume data in the NL—State region. Within these regions,
associations between live volume, dead volume, and stand age, site index, and basal area

categories were analyzed using either a t-test or ANOVA.

Log transformations of overall mortality, top-kill, and volume data (n = 356) did
not normalize data, so I used a one-way non-parametric ranked F test for regional
comparisons (p < 0.05) (Neter et al. 1996). Analysis of within-region comparisons of
mortality, and live and dead volume data which were not normalized by log
transformations, were analyzed using a one-way non-parametric ranked F test (p < 0.05)
(Neter et al. 1996). If the F-test was significant, treatment means were separated using a
non-parametric multiple comparison procedure (p < 0.05) (Zar 1984). All non-parametric
pairwise comparisons were analyzed by first ranking the data, then using a t-test.
Interactions among non-normal jack pine mortality and live and dead volume data, and
stand age, site index, and basal area categories for all regions combined (n = 356) were

analyzed using a two-way ranked F test (Neter et al. 1996).

12

 

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Lot

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p10;

3mm

lite,

 

Linear associations between jack pine live volume (m3/ha of standing live trees),
dead volume (m3/ha of standing dead trees), and stand inventory variables were evaluated
among all regions combined, and within each region, using Spearman’s nonparametric
correlation coefficient (r5). Standing live and dead volume were used as response
variables, and stand age, site index, and basal area were used as predictor variables.
Backward stepping linear regression was used to assess relationships between log
transformed live and dead volume data and stand inventory variables. Backward stepping
procedures were used in order to adjust models for the effect of potential collinearity
among predictor variables, and to most efficiently find the most powerful predictors of

live and dead volume.

Within each region, I used stand age, site index, and basal area as predictor
variables of live and dead volume data. With all regions combined, I used the same stand
inventory variables as linear predictors of live and dead volume data, and tested for
significance of land ownership (USDA Forest Service owned vs. MI Department of
Natural Resources owned), and physio-region (northern lower Michigan regions (NLMI)
vs. eastern Upper Peninsula regions (EUP) vs. western Upper Peninsula regions (WUP))
using dummy variables. Data were analyzed using SAS statistical software (SAS

Institute, Inc. 2000) at the p < 0.05 level of significance.

13

 

hut

 

 

 

Results
Jack pine volume, mortality and top-kill

Overall, volume of live jack pine averaged 220.8 1 10.64 m3/ha. On average, 20.4
i 0.96% of the jack pine trees in our plots were dead, and 5.1 i: 0.51% of the jack pine
had dead tops. Volume of dead jack pine averaged 35.0 i 3.51 m3/ha.

Overall, live volume was generally similar among regions, however the UP-West
region had a significantly higher average live volume per hectare than the UP-ONF, UP-
East, NL-HNF, WI-State, UP-Raco, and NL-State regions. Live jack pine volume was
also significantly higher in the UP-ONF region than in the WI-State, UP-Raco, and NL-
State regions (F = 17.04, P < 0.0001, d.f. = 6, 349) (Table 1-4). In the UP-West stands,
live jack pine volume averaged 448.5 1 44.83 m3/ha, approximately one and a half to
three times higher than the other six regions (Table 1—4). Live jack pine volume averaged
245.6 i: 22.73 m3/ha in the UP-ONF stands, approximately 33% to 65% higher than the
WI-State, UP-Raco, and NL-State regions (Table 1-4).

Percentage mortality was generally variable among regions, and stand variability
was also high within regions. The UP-ONF and WI-State regions had significantly more
dead jack pine trees per stand than the UP-Raco and NL-State regions (F = 4.74, P =
0.0001, d.f. = 6, 349) (Table 1-4), but other differences among regions were not
significant. On average, the UP-ONF and WI-State stands had 28.0 i 2.95% and 27.3 i
2.67% mortality, respectively, while only 13.2 i- 1.46% and 15.0 i 1.96 % of the jack
pine trees in plots were dead in the UP-Raco and NL-State regions.

Percentage top-kill was generally similar among all regions, except for the UP-

Raco region, which had a significantly higher percentage of jack pine trees with dead

14

 

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to.

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of ti.
that

liar:

class.
Class.

intern

 

tops than the UP-West, NL-HNF, WI-State, and UP-ONF regions (F = 4.84, P < 0.0001,
d.f. = 6, 349) (Table 1-4). On average, 9.9 i 1.58% of jack pine were top-killed in UP-
Raco stands, approximately two and a half to four times higher than stands in the UP-
West, NL-HNF, WI-State, and UP-ONF regions.

Trends in the amount of dead volume were similar to those of standing live
volume among regions. Volume of dead jack pine trees was significantly higher in the
UP-West region than in the UP—East, NL-HNF, UP-Raco, and NL-State regions (F =
4.79, P = 0.0001, d.f. = 6, 349) (Table 1-4). There was an average of 68.4 a 17.85 m3/ha
of dead jack pine volume in the UP-West region, nearly two to four and a half times more
than stands in the UP-East, NL-HNF, UP-Raco, and NL-State regions (Table 1-4).
Mortality, dead volume, and tree characteristics

The majority of dead jack pine trees were in the intermediate or suppressed crown
classes, while most of the dead volume was in the dominant and co-dominant crown
class. Suppressed trees accounted for only 11.2% of the dead jack pine volume, while
intermediate trees represented 37.3% of dead volume (Table 1-5).The NL-State, UP-
ONF, and UP-Raco regions were the only areas where a higher percentage of dead
volume occurred in the intermediate and suppressed crown classes than in the dominant
crown class (Table 1-5). Dead volume in the intermediate and suppressed crown classes
in these regions accounted for 64.7%, 65.1%, and 67.3% of the total dead volume,
compared with the other regions, which had only 30% to 40.5% of the total dead volume
in the intermediate and suppressed crown classes (Table 1-5).

Overall, 17.6% of the dead trees and 51.5% of the dead volume were in the

dominant or co-dominant crown class in the seven regions (Table 1-5). The NL-HNF

15

region had the highest percentage of dead jack pine trees in the dominant crown class at
24.2%, while the WI—State region had the highest percentage of dead volume in the
dominant crown class at 69.5% (Table 1-5). The NL-State region had the lowest number
of dead dominants at 6.3%, while the UP-Raco region had the least percentage of dead
volume in the dominant class at 32.7% (Table 1~5). Most of the dead jack pine were
classed as suppressed or intermediate trees. Mortality of suppressed and intermediate
trees ranged from 16.0% in the WI-State region to 62.5% at the same region.
Stand inventory variables

Mortality of jack pine trees and the ratio of dead to live volume of jack pine
seemed to be highest in stands that were 50+ yrs old among all regions. I calculated a
ratio of dead to live volume for within region comparisons because I felt that this would
standardize the proportion of dead volume relative to the proportion of live volume in
each stand. Overall, significantly more mortality occurred in stands that were 50+ yrs old
than in stands younger than 50 yrs (t = 6.81, P <.0001, d.f. = 1, 311). However, a
significant interaction occurred between stand age and site index (F = 5.05, P <.0001, d.f.
= 5, 350). Stands that were 50+ yrs old growing on higher quality sites across all regions
had higher levels of mortality than younger stands growing on higher quality sites. Stands
50 yrs old or older averaged 25.2 i 1.26% mortality, while younger stands averaged 13.0
i 1.25% mortality. Significantly more mortality occurred in stands that were 50+ yrs old
than in younger stands in the NL-HNF (t = 3.13, P = 0.0033, d.f. = 1, 40), UP-Raco (t =
3.92, P = 0.0002, d.f. = 1, 75), UP-East (t = 4.03, P = 0.0002, d.f. = 1, 41), and UP-ONF
(t = 3.22, P < 0.0001, d.f. = 1. 48) regions (Figure 1-2A). Trends were similar in the other

three regions, but not significant. Mortality in stands that were 50+ yrs old ranged from

16

 

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Slit.“

and

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20.8 i 2.68% in the UP-Raco region to 32.4 i 3.38% in the UP-ONF region, while
mortality of stands less than 50 yrs old ranged from 7.1 i 2.25% in the UP-Raco region
to 12.3 i 2.77% in the UP-ONF region (Figure 1-2A).

Overall, the ratio of dead to live volume was significantly higher in stands that
were 50+ yrs old than in younger stands (t = 6.77, P <.0001, d.f. = 1, 310). Stands
younger than 50 yrs old averaged a ratio of 8.5 _-+_- 1.90 m3/ha dead to live volume, while
stands that were 50+ yrs old averaged a ratio of 22.9 i 2.46 m3/ha dead to live volume.

Among all regions, stand age was consistently the most powerful predictor of live
and dead volume. Both live volume (rs = 0.51, P <.001) and dead volume (rs = 0.43, P
<.001) were significantly correlated with stand age (Table 1-6). Results from the linear
regression model indicated that stand age was a significant predictor of live volume (r2 =
0.45, P <.0001) and dead volume (r2 = 0.26, P <.0001) among all regions (n = 356)
(Table 1-7). The effect of land ownership was also significant in predicting live volume
(r2 = 0.46, P <.0001), and the effect of physio-region was significant in predicting dead
volume (r2 = 0.28, P <.0001) (Table 1-7).

Within regions, stand age was also consistently the most important factor in
predicting live and dead volume. Stands that were 50+ yrs old had a higher ratio of dead
to live volume (Table 1-8), ranging from an average ratio of 9.4 i 3.74 m3/ha dead to live
volume in the NL-State region to 36.5 3.- 6.90 m3/ha dead to live volume in the UP-ONF
region. Comparisons between the ratio of dead to live volume and stand age were
significant in the NL—HNF (t = 2.39, P = 0.0213, d.f. = 1, 42), UP-Raco (t = 3.23, P =
0.0019, d.f. = l, 72), UP-East (t = 6.07, P <.0001 d.f. = 1, 46), and UP—West (t = 2.50, P =

0.0183, d.f. = 1, 30) regions (Table 1-8).

17

 

an

“f.
\‘0f
slg'
llli.‘

“67:.

 

All regions except the NL-State region had significant correlations between live
and dead volume, and stand age (Table 1-6). In the linear regression models, stand age
was a significant predictor of live volume in all regions except the UP-West region,
where there was no linear model. Stand age was also a significant predictor of dead
volume in all regions except the NL-State and UP-West regions, where there were no
significant linear models (Table 1-7). However, stand age Was significantly correlated
with site index in the UP-ONF region (rS = 0.41, P = 0.003), indicating that older stands
were growing on higher quality sites in this region.

Within regions, site index appeared to be an inconsistent factor for comparisons
of jack pine mortality and the ratio of dead to live volume. However, when all stands
were combined, mortality in stands on higher quality sites (23.0 i 1.44%) was
significantly higher than in stands on lower quality sites (18.1 i 1.27%) (t = 2.44, P =
0.0151, d.f. = 1, 351). A marginal interaction occurred between site index and basal area
(F = 3.82, P = 0.0515, d.f. = 5, 350), indicating that more mortality potentially
accumulates in over-stocked, higher quality stands when all regions were combined.
Mortality was significantly greater in higher quality stands than in lower quality stands
only in the UP-Raco region (t = 2.10, P = 0.0386, d.f. = 1, 76) (Figure l-2B). This trend
was the same for all other regions except for the UP-West region, where there was
virtually no difference (Figure 1-ZB).

Comparisons between the ratio of dead to live volume and site index categories
were consistently insignificant within regions (Table 1—8). Only the NL-HNF (rS = 0.34, P
= 0.017), UP-Raco (rs = 0.30, P = 0.007), and UP-ONF (r5 = 0.43, P = 0.002) regions had

significant correlations between live volume and site index, and the low rs values suggest

18

 

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high variability among stands within the regions. No significant relationships occurred
between dead volume and site index within regions (Table 1-6), and linear regression
models within regions also indicated that site index was a significant predictor of live
volume only in the NL-HNF region (r2 = 0.35, P = 0.0001), and was not a significant
predictor of dead volume within any regions (Table 1-7). However, results of Spearman’s
correlation analysis indicated that both live volume (rS = 0.42, P <.001) and dead volume
(rs = 0.25, P <.001) were significantly correlated with site index when all regions were
combined (Table 1-6). Linear regression models using all regions combined also
indicated that site index was consistently a significant predictor of both live and dead
volume (Table 1-7).

Differences between basal area data calculated from permanent plots for live
dominant jack pine trees and inventory database basal area data provided by cooperating
agencies were significant only in the NL-HNF (t = 2.24, P = 0.0275, d.f. = 1, 98) and UP-
West (t = 4.43, P <.0001, d.f. = 1, 96) regions. Within regions, permanent plot basal area
data averaged 0.3 mzlha, 0.5 m2/ha, and 2.2 m2/ha lower than inventory database basal
area data in the UP-ONF, UP-Raco, and NL-State regions, while permanent plot basal
area data averaged 0.4 mz/ha, 2.6 mzlha, 4.2 mzlha, and 8.3 mz/ha higher than inventory
database basal area data in the WI-State, UP-East, NL-HNF, and UP-West regions.
However, when all regions were combined, a Pearson’s test of linear correlation resulted
in a low r-value (r = 0.35), suggesting high variability and a lack of a linear relationship
between permanent plot basal area data and inventory database basal area data used for

stand category analysis.

19

 

 

 

 

m0

0I0

Generally, jack pine stands that were well-stocked (basal area of 16.1 -- 25.3
mZ/ha) or over-stocked (basal area > 25.3 mz/ha) had more mortality and a higher ratio of
dead to live volume than stands that were under-stocked (basal area < 16.1 mzlha),
however, some variability among regions occurred. Overall, mortality was significantly
higher in well to over-stocked stands than in under—stocked stands (F = 25.47, P <.0001,
d.f. = 2, 353). Stands that were well-stocked or over-stocked averaged 25.6 : l.44% and
28.3 i 2.97% mortality, respectively, while under-stocked stands averaged 13.4 i 1.22%
mortality. Mortality of jack pine was significantly higher in stands that were well-stocked
or over-stocked than in stands that were under-stocked in the NL-HNF (F = 5.09, P =
0.0100, d.f. = 2, 47), UP-Raco (F = 10.85, P < 0.0001, d.f. = 2, 75), UP-ONF (F = 4.43, P
= 0.0173, d.f. = 2, 47), and WI-State (F = 6.22, P = 0.0044, d.f. = 2, 41) regions (Figure
l—2C).

Overall, the ratio of dead to live volume was significantly higher in well to over-
stocked stands than in under-stocked stands (F = 19.83, P <.0001, d.f. = 2, 353). Stands
that were well—stocked or over-stocked averaged a ratio of 21.0 i 2.71 m3/ha and 22.1 i
5.14 m3/ha dead to live volume, respectively, while under-stocked stands averaged a ratio
of 12.4 i 2.36 m3/ha dead to live volume. When all regions were combined, both live
volume (r, = 0.47, P <.001) and dead volume (rs = 0.43, P <.001) were significantly
correlated with basal area (Table 1-6), probably because of the significant relationship
between basal area and stand age (r s = 0.49, P <.001) and site index (rs = 0.35, P <.001).
Significantly higher ratios of dead to live volume occurred in well-stocked stands than in
under-stocked stands in the NL—State (F = 4.75, P = 0.0156, d.f. = 2, 32), NL-HNF (F =

5.65, P = 0.0063, d.f. = 2,47), and UP-Raco (F = 5.91, P = 0.0042, d.f. = 2, 75) regions

20

(Table 1-8). This trend was the same for all other regions except the UP-East region,
which averaged an approximate ratio of 10 m3/ha of dead to live volume for under, well,
and over-stocked stands. The UP-ONF region had a significantly lower ratio of dead to
live volume in over-stocked stands than in well-stocked stands (F = 3.80, P = 0.0295, d.f.
= 2, 47) (Table 1-8). All regions except the NL-HNF and UP-West regions had
significant correlations between live volume and basal area, and all regions except the
UP-ONF region had significant correlations between dead volume and basal area (Table
1-6), probably a result of the significant correlations between basal area and stand age

and site index.

21

Discussion

Overall, live volume of jack pine seemed to be higher than previous Lake States
studies have found (Rudolph and Laidly 1990), but relatively similar to studies in Canada
(Gross 1992). Mortality and top-kill of jack pine in Michigan and Wisconsin more
closely resemble what other Lake States studies have reported (Conway et al. 1999a;
McCullough et al. 1996. Rudolph and Laidly (1990) reported that un-managed stands of
jack pine in all age classes in the Lake States region averaged approximately 136.5 m3/ha
live volume. Estimates of live volume from this study were probably higher because the
highly productive jack pine regions in the western Upper Peninsula of Michigan were
included in the analysis. Gross (1992) found that jack pine stands in Ontario averaged
approximately 202.3 m3/ha standing volume. However, one of the four stands had a
relatively high percentage (71%) of associated species, while this study accounted for
jack pine volume only.

In the 30,000 ha Raco Plains area of the Hiawatha National Forest in Michigan,
McCullough et al. (1996) and Conway et al. (1999a) found that one to two years
following defoliation by JPBW, mortality of jack pine averaged 8% and 16%,
respectively, while Kulman et al. (1963) reported roughly 30% mortality of jack pine in
Minnesota. Mortality results from this study were similar to these previous studies,
indicating that mortality of jack pine varies within and among stands, depending upon
stand age, and whether or not a severe disturbance, such as defoliation by JPBW, has
recently occurred. Results from studies of top-kill in Saskatchewan (Hall et al. 1998), and

in the Raco Plains area of the Hiawatha National Forest (McCullough et al. 1996)

22

indicated relatively higher levels of top-kill than what our study suggests, probably
because of the amount of dead jack pine trees that were likely top-killed.
Jack pine volume, mortality, and top-kill

In most regions, jack pine was relatively similar, however, some variability did
occur among regions. Possible reasons for overall similarities among some regions could
be because of the general homogeneity of age and density among jack pines stands, or
because of relatively similar site conditions (Table 1—1). Because jack pine is a prolific
pioneer species, regeneration of stands is generally even-aged, and because jack pine can
grow on very droughty sites where other, more competitive species may have more
difficulty establishing, so stands can be relatively low in species diversity (Rudolf 1958).
Jack pine stands in regions that were most similar in terms of live volume, dead volume,
and mortality generally grew in similar site conditions; droughty to moderately drained
sands with very little moisture holding capacity that are of lower site quality than the
other regions (Johnson 1990; Werlein 1998; Whitney 1992). Standing live volume of jack
pine was especially high in the UP-West region. In this region, jack pine typically grows
on much higher quality sites than in most other regions, except the UP-ONF region,
which has generally similar growing conditions (Schwenner 1991). It has been well
documented that jack pine can grow faster and to larger sizes on better quality sites than
on lower quality sites (Rudolf 1958; Rudolph and Laidly 1990). Mean and median site
index values for jack pine in the UP-West region were generally 1.0 to 3.5 m higher than
all other regions, where average live volume estimates were significantly less.

The high percentage of dead trees in the UP-ONF and WI-State regions could be

related to several factors, including stand age and basal area, the frequency and severity

23

of JPBW outbreaks within each region, the frequency of other disturbances, or differing
management guidelines. Stands in the UP-ONF region were generally old and fairly well
to over-stocked, while stands in the WI-State region were generally young and under-
stocked. So, the question arises as to why these two seemingly different regions have
such high, equal amounts of mortality. Several of the old stands in the UP-ONF region
were located in designated ‘buffer’ riparian areas, where harvesting was not allowed
(Larry Melstrom, personal communication). Jack pine, being a short-lived species, can
quickly accumulate mortality beyond ages 50 to 60 yrs, depending upon site conditions
(Benzie 1977). The high levels of mortality in relatively young stands in the WI-State
region were probably a result of natural thinning processes occurring from ages 35 yrs to
45 yrs. The relatively higher percentage of top-kill in the UP-East, NL-State, and UP-
Raco regions is likely related to the frequency and severity of JPBW outbreaks that have
occurred (Heym et al. 1993; M1 Dept. of Natural Resources 1980 — 1994). High levels of
dead standing jack pine volume in the UP-West and UP-ONF are likely related to
generally higher levels of live volume and mortality in the regions, as well as generally
higher frequencies of older aged, heavier stocked stands.

Genetic variation between populations of jack pine across geographical regions
has been well documented (Hyun 1976; Gauthier et al. 1992). Variation in the genetics of
different populations can affect the susceptibility of individuals to mortality caused by
biotic and abiotic stresses which occur across the landscape. Genetic variation can
potentially affect stand volume growth, as well as variations in the production of
serotinous and non-serotinous cones. Jack pine stands where non-serotinous cones are

produced more frequently may have higher percentages of intermediate or suppressed

24

trees, which can succumb to mortality from insect defoliation or other natural thinning
processes (Kenkel et al. 1989).

Differences in management guidelines among regions can also affect the amount
of live and dead volume, and the percentage of dead trees which occur in a stand. Results
indicated that older aged, heavier stocked stands seem to be most vulnerable to individual
tree mortality, suggesting that rotation ages and compliance with stocking guidelines
should be among the most important management rules to follow to maintain the highest
levels of economic viability for jack pine. Results from the linear regression analysis
further indicate that land ownership, i.e. different management, may affect the structure
of jack pine stands among regions. Rotation ages may be different, based upon market
values of jack pine in different areas. Jack pine stands used for pulp vs. stands used for
dimension lumber vs. stands that are whole-tree harvested could be managed with
different intermediate or late stand treatment methods, thus reflecting the potential
variation among regions and ownerships. This suggests that human-caused disturbance,
i.e. harvesting for wood products, could be just as an important factor as naturally-caused
disturbances, such as JPBW outbreaks, in explaining the current jack pine status in
Michigan. Linear regression analysis also indicated that a regional effect may exist in
explaining the amount of dead volume in jack pine stands. This could be explained by
many of the factors I just suggested which affect the structure of jack pine stands;
frequency of JPBW outbreaks, severity of randomly occurring abiotic disturbance

(weather events, etc.), or genetic variation.

25

Mortality, dead volume, and tree characteristics

The occurrence of jack pine mortality in different crown levels can be important
because the majority of economic impacts occur when dominant, merchantable trees die.
The largest percentage of trees that died in all regions were either in the suppressed or
intermediate crown levels of the stand. Yet, the greatest percentage of standing volume
that was dead occurred in the dominant class. Kulman et a1. (1963) found that mortality
of intermediate and suppressed trees following successive years of JPBW defoliation in
Minnesota ranged from 25% to 70%, while mortality of dominant and co-dominant trees
ranged from an average of 12% to 17%. Gross (1992) found that dominant and co-
dominant jack pine trees averaged less than 1% mortality after a JPBW outbreak in
Ontario, while intermediate and suppressed trees ranged from an average of 9% to 60%
mortality. My results were generally similar with these studies, except the percentage of
mortality in the dominant and co-dominant crown classes were higher than the results
reported by Gross (1992). This implies that impacts from within stand competition or
natural disturbances such as defoliation by JPBW, can act as natural thinning agents in
over-stocked stands by freeing up resources to surviving individuals by disposing of less
vigorous suppressed trees. In regions where the dominant class is more heavily affected
by tree mortality and volume loss, emphasis should be placed on salvage or pre-salvage
operations so that the economic value of vulnerable trees can be saved (Conway 1999a).
Mortality, live and dead volume, and stand inventory variables

There are a few reasons why there were such confounding differences between
basal area data that I calculated from live dominant jack pine trees from permanent plots

and basal area data received from cooperating forest manager’s databases. The

26

differences were likely due to the fact that my plot-level data was taken from jack pine
trees only, while most stands were not complete monocultures of jack pine, e.g.
plantations, and forest manager’s likely include data on other companion species in
stands while updating their stand inventory databases. On average, basal area data
calculated from my plots were generally higher in four of the seven regions. These results
could reflect the potential that the stand inventory data I received from managers may not
have reflected the density of the stand during while I was collecting data.

Jack pine mortality and average dead to live volume ratio seemed to be closely
related to stand age and basal area among all regions. However, because basal area was
closely associated with stand age, it should be interpreted as a less important indicator of
mortality and dead volume. The generally strong correlation between basal area and stand
age suggested that well—stocked to over-stocked stands were over-aged. From earlier
discussion, more mortality and dead volume should occur in older stands. Linear
regression results within regions further describe the importance of stand age on volume
loss resulting from tree death, suggesting that jack pine stands should be harvested at
optimum rotation periods to lessen economic losses by damaging disturbances, such as
defoliation by JPBW. Many studies have noted higher levels of jack pine mortality and
dead volume in older stands (Conway et al. 1999a; McCullough et al. 1996; Volney
1998). Most of the regions surveyed had extensively higher amounts of mortality in older
stands, except the NL-State and WI-State regions, which had relatively high percentages
of dead jack pine in younger stands. As an explanation, higher levels of mortality within
these regions occurred in the intermediate and suppressed crown classes in well or over-

stocked stands. Mortality in younger stands could have been a result of natural thinning,

27

thus allowing a subsequent rapid increase in the growth and productivity potential of
dominant, vigorous trees.

McCullough et al. (1996) and Conway et al. (1999a) found that mortality and
volume loss was higher in higher quality stands in the Raco Plains area of the Hiawatha
National Forest in Michigan. They suggested that trees growing on higher quality sites
may have lower root-to-shoot ratios and would potentially be less tolerant of defoliation
by JPBW than trees growing on lower quality sites. Even though the results showed that
mortality was generally higher on higher quality sites among all regions, that comparison
was significant only in the UP-Raco region. Four regions (NL-State, UP-East, UP-West,
WI-State) had proportionally more dead volume on higher quality sites, while the other
three regions (NL-HNF, UP-Raco, UP-ONF) had a higher proportion of dead volume on
lower quality sites.

The variation in impact on different sites could be attributed to moisture or
nutrient holding capacities of the soils in different regions, or to the percentage of dead
dominant or suppressed trees in older or relatively higher quality stands. The variability
of the amount of dead trees and proportion of dead volume among regions could also be
related to the occurrence of salvage or pre-salvage operations, which remove recently
killed, merchantable trees. My results indicated an inconsistent pattern of loss of
dominant trees in higher quality stands, which suggests that further research should be
done specifically looking at mortality in relation to site characteristics in different areas.
Summary and conclusions

This study is the first to collect baseline data to describe the current status of the

jack pine resource in Michigan and Wisconsin for monitoring long-term impacts of

28

JPBW. Within stands, age seems to be the most important factor to predict mortality of
jack pine, yet tree death occurs most frequently among the suppressed and intermediate
crown classes. Stands experiencing high mortality in the dominant crown class should be
prioritized for harvest. Interestingly, only a few regions varied significantly from the rest,
with respect to live and dead volume, and mortality and top-kill. These results will be
used to modify a current decision support model (Conway et al. 1998), so that it can be

applicable to forest managers across the surveyed regions.

29

 

 

 

 

 

 

 

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leg

 

Table 1-2. Characteristics used to stratify jack pine stands for evaluation of jack

pine live and dead volume (ms/ha), mortality and top-kill, and total and average

annual radial growth rates from 1991 - 2000 in six regions of Michigan and one
region of Wisconsin.

 

 

 

 

Age (years) Site Index (m)1 CE:EE$Z::)2 "$2:ij
Young (< 50) Low Under 69
Well 16
Over 0
High Under 25
Well 24
Over 5
Old (50+) Low Under 39
Well 50
Over 12
High Under 28
Well 56
Over 32
TOTAL 356

 

1Site index was stratified differently among regions: the Ottawa National Forest in the
west Upper Peninsula and state land in west-central Wisconsin (low SI 5 16.8 m <
high SI), state land in the west-central Upper Peninsula (low SI 5 18.3 m < high SI),
other four regions (low SI 5 14.9 m < high SI).

2Basal area categories represent stands considered to be: Under-stocked = (< 16.1

m2/ha); Well-stocked = (16.1 - 25.3 mZ/ha); Over-stocked = (> 25.3 m2/ha).

32

Table 1-3. Number of jack pine stands and trees and characteristics of stands
surveyed in seven regions of Michigan and Wisconsin to assess standing live
and dead volume (ms/ha), mortality and top-kill, total and average annual radial

growth rates of jack pine trees, and coarse woody debris volume (ms/ha).
Regions surveyed included state land in northern lower Michigan (NL-State), the

Huron-Manistee National Forest (NL-HNF), the Raco Plains area of the Hiawa-
tha National Forest (UP-Raco), state land in the eastern Upper Peninsula of

Michigan (UP-East), state land in the western Upper Peninsula (UP-West), the
Ottawa National Forest (UP-ONF), and state land in Wisconsin (WI-State)

(SEM = standard error of the mean).
Region NL-STate NL-HNF UP-Raco UP-East UP-West UP-ONF Wl-State

 

 

 

 

No. stands 35 50 78 50 49 50 44

No. trees 1020 499 826 561 559 488 518
Age (years)

Mean 54.7 55.7 48.5 53.9 58.0 57.1 43.1
SEM 2.58 2.33 2.43 2.84 1.93 2.26 2.26

Median 54 57 57 60 60 64 38

Min 23 16 13 20 32 10 20

Max 79 87 1 17 101 86 96 71

Site Index
(m)
Mean 14.7 15.0 14.9 14.8 18.2 17.2 16.4
SEM 0.32 0.25 0. 14 0.26 0.28 0.26 0.24
Median 15.0 15.3 15.3 15.3 18.3 16.8 16.8
Mln 10.7 10.7 12.5 9.2 12.2 14.6 12.2
Max 18.3 19.5 18.0 18.6 21.4 22.3 19.8
Basal Area
(mzlha)

Mean 15.3 14.7 18.2 17.0 18.6 19.6 14.5
SEM 1.49 1.05 1.13 1.12 0.79 1.20 1.36
Median 16.1 13.8 16.9 16.1 18 18.4 15.5

Min 2.3 2.3 19.0 2.3 9.2 3.5 2.3
Max 39.1 34.5 50.6 32.2 29.9 34.5 34.5

 

33

Table 1-4. Comparison of mean (1 SE) volume (ma/ha) of live and dead jack

pine trees per stand, mean (1 SE) percentage of dead jack pine trees, and

mean (1 SE) percentage of jack pine trees with dead tops in the seven

surveyed regions. Regions included state land in northern lower Michigan
(NL-State), the Huron-Manistee National Forest (NL-HNF), the Raco Plains

area of the Hiawatha National Forest (UP-Raco), state land in the eastern

Upper Peninsula of Michigan (UP-East), state land in the western Upper

Peninsula (UP-West), the Ottawa National Forest (UP-ONF), and state land in
west-central Wisconsin (WI-State). Letters indicate significant differences

among regions (p < 0.05).

Live Volume (ma/ha) Mortality (%)

Top-Kill (%)

Dead Volume (ma/ha)

 

Region
NL-State 144.8 1 12.95 c 13.2 1 1.46 b
NL-HNF 201.6 1 22.16 be 18.1 1 2.31 ab
UP-Raco 150.6 1 17.08 c 15.0 1 1.96 b
UP-East 209.5 1 22.02 be 20.8 1 2.75 ab
UP-West 448.5 1 44.83 a 22.1 1 2.59 ab
UP-ONF 245.6 1 22.73 b 28.0 1 2.95 a
Wl-State 191.3 1 23.46 c 27.3 1 2.67 a

34

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3511D9b
991158a
5211D3ab
381132b
231098b
301079b

15.0 1 6.00 be
20.1 1 5.04 be
20.0 1 3.69 c
29.3 1 6.27 be
68.4 1 17.85 a
62.6 1 9.48 ab
32.5 1 9.31 abc

Table 15 Comparison of the percentage of dead volume (ms/ha) and
percentage of jack pine trees that were dead in dominant, intermediate, and
suppressed crown classes in the seven surveyed regions. Surveyed regions
included state land in northern lower Michigan (NL-State), the Huron-
Manistee National Forest (NL-HNF), the Raco Plains area of the Hiawatha
National Forest (UP-Raco), state land in the eastern Upper Peninsula of
Michigan (UP-East), state land in the western Upper Peninsula (UP-West),
the Ottawa National Forest (UP-ONF), and state land in west-central
Wisconsin in-State).

 

Dominant Intermediate Suppressed
Region Dead Volume Mortality Dead Volume Mortality Dead Volume Mortality

NL-State 35.3 6.3 48.2 41.5 16.5 52.1
NL-HNF 59.5 24.2 36.9 52.6 3.6 23.2
UP-Raco 32.7 17.7 41.2 38.5 26.1 43.1
UP-East 70.1 20.7 28.2 52.3 1.7 27.0
UP-West 59.5 20.0 38.0 35.7 2.5 44.3
UP-ONF 34.9 15.6 40.5 43.0 24.6 41.4
WI-State 69.5 21.5 30.2 62.5 0.3 16.0

ALL 51.5 17.6 37.3 46.3 11.2 36.0

 

35

 

 

 

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Figure 1-2. Mean (:l: SE) percentage of dead jack pine trees in seven regions
in Michigan and Wisconsin grouped by (A) stand age, (B) site index (m), and

(C) basal area (m2/ha). Different letters indicate significant differences among
groups within regions (p < 0.05).

43

CHAPTER 2

ANALYSIS OF ANNUAL RADIAL GROWTH RATES OF JACK PINE ACROSS
NORTHERN MICHIGAN AND WISCONSIN

Introduction

Annual radial growth rings have long been used to evaluate effects of
environmental and climatic factors on tree growth (Hainze and Benjamin 1984; Jeong
and Rao 1996; Larsen and MacDonald 1995; Watson and Luckman 2002), and to predict
growth and yield of economically important species (Boyer 1987; Johnson et al. 1981).
Tree ring analysis has been used to evaluate effects of defoliating insects on radial
growth, such as western spruce budworm (Choristoneura occidentalis Freeman) (Weber
and Schweingruber 1995), spruce budworm (Choristoneurafitmiferana Clements) (Piene
1989; Shore and Alfaro 1986), and Douglas-fir tussock moth (Orgyia pseudotsugata
McDunnough) (Brubaker 1978). Outbreak years can generally be identified by a
pronounced decrease in radial growth due to heavy defoliation.

Jack pine (Pinus banksiana Lambert) is an important species in the Lake States
region of the US. and throughout much of Canada. It is a fast growing, shade intolerant
species which can grow on relatively poor soils, and is important for the commercial
pulpwood industry (Rudolph and Laidly 1990). In Michigan and Wisconsin, jack pine
forests occur on nearly 485,000 ha (1.2 million acres) (Piva 1997). More than 270,000
cords of jack pine are annually harvested for wood fiber, amounting to a stumpage value
of nearly $10.1 million (USDA-PS timber price list 2002). Management intensity in jack
pine forests has escalated because of the enhanced value of jack pine pulp (from $4/cord
in 1991 to $35/cord in 2002) (McCullough and Leefers 2000; USDA-PS timber price list

2002), leading to emphasis on optimization of harvest rotations.

44

Every year, jack pine forests in the Lake States region experience multiple natural
disturbances, which can affect patterns of annual radial growth in jack pine, including
drought stress and other weather events. Jack pine budworm (JPBW) is among the most
important biotic disturbances in jack pine ecosystems. Outbreaks occur every 6 - 10
years, typically lasting two to four years (McCullough 2000). During a JPBW outbreak,
heavy defoliation can result in radial growth reduction, death of the terminal leader (top-
kill), and tree mortality (Gross 1992; Kulman et a1. 1963).

Because of the economic importance and demand for jack pine in Michigan and
Wisconsin (Piva 1997), it is important to quantify annual growth patterns in jack pine.
Advances in annual radial growth research can aid forest managers in decision making
processes, so that proper stand attributes, including stand density and age, can be
identified for the most efficient growth of economically viable trees. Important stand-
level disturbances that greatly affect annual growth patterns can also be recognized and
stands can then be managed properly to lessen annual growth losses.

A large-scale project was initiated in 2001 to assess the current status of the jack
pine resource and to quantify long-term impacts of JPBW defoliation in six regions of
Michigan and one region of Wisconsin. Objectives of this study were to (1) quantify
annual radial growth of jack pine in a network of recently established permanent plots,
(2) assess relationships between radial growth and crown class and stand variables, and
(3) evaluate radial growth patterns in jack pine among regions related to tree and stand
level disturbance. I hypothesized that patterns of annual radial growth for jack pine would
differ among the seven regions, because of variation in JPBW outbreaks, and climatic

patterns. Within a given region, I hypothesized that radial growth patterns would be

45

negatively related to tree age and stocking level, and positively related to site quality and

dominance class.

46

Methods

Study sites

Permanent plots were established from May to August in 2001 — 2003 in six
regions of northern Michigan and one region in Wisconsin to assess the current state of
jack pine and to monitor long-term impacts of JPBW and annual radial growth rates of
jack pine. These seven regions were selected based upon the relative abundance of jack
pine in the area, and the frequency of JPBW outbreaks. These regions included state land
in the north-central Lower Peninsula of Michigan (NL-State), the Huron-Manistee .
National Forest in the northeastern Lower Peninsula (NL-I-INF), the Raco Plains area of
the Hiawatha National Forest in the eastern Upper Peninsula of Michigan (UP-Raco), two
regions of state land in the Upper Peninsula (UP-East and UP-West), the Ottawa National
Forest in the western Upper Peninsula (UP-ONF), and state land in west-central
Wisconsin (WI-State) (Figure 1-1). Soils were generally moderately drained to droughty,
except for two regions (UP-East and WI-State), which contained areas of poorly drained
peat soils (Table 1-1). The terrain was generally level to gently sloping, with moderately
steep areas in the UP-West and UP-ONF regions. The WI-State region had scattered

sandstone mounds (Table l- 1 ).

Stand selection

A stratified random sampling approach was used to select jack pine stands in each
of the seven regions for sampling. Stratification was based on stand age, site index, and
basal area (Table 1-2), because of their documented relationship with tree mortality, jack

pine volume, and annual radial growth (Conway et al. 1999a, 1999b; McCullough et al.

47

1996), and because these variables are routinely collected and used operationally by
forest managers. These variables were acquired from each respective forest management
agency’s database. After stands were grouped by age, site index, and basal area, we
randomly selected jack pine stands from each group, based on the percentage of the total
number of stands that were assigned to each stand variable category. Number of stands
used per region ranged from 35 stands in the NL-State region 78 stands in the UP-Raco
region. If stands had been recently harvested or were not accessible, 3 replacement stand

was selected from the same group.

Permanent plots were established in a total of 356 jack pine stands encompassing
6,374 ha (15,750 acres) in northern Michigan and Wisconsin from 2001 to 2003 (Table 1-
3). Stand age ranged from 10 yr in the UP-ONF region to 117 yr in the UP-Raco region.
Site index ranged from 9.2 m (30 ft) in the UP-East region to 22.3 m (73.2 ft) in the UP-
ONF region and basal area ranged from 2.3 mzlha (10 ft2/ac) in the NL-State, NL-HNF,
UP-East, and WI-State regions to 50.6 m2/ha (220 ft2/ac) in the UP-Raco region (Table 1-

3).
Tree core extraction

One circular, 0.01 ha (0.025 acre) fixed-radius survey plot was randomly located
in each stand using compartment maps overlaid with a transparent grid. Grid cells were
selected at random for plot center location, and a compass and pacing was used to locate
the permanent plot center in the field. I established one survey plot per stand in all
regions except NL-State. Multiple plots per stand were established in the NL-State region
in 2001 to assess within-stand variability. Within each of the NL-State region stands, I

established at least two plots; three plots for stands larger than 8.5 ha (21 acres), four

48

plots for stands larger than 20.7 ha (51 acres), and five plots for stands larger than 40.5 ha
(100 acres). For analysis, I used mean values, based on the number of established plots
per stand at the NL-State region. In all other regions, I chose to establish one plot per
stand to ensure that a wide range of jack pine forest could be surveyed, and jack pine
stands were generally fairly small (mean and median stand acres = 44 and 32,
respectively). The age of jack pine trees and stocking also tends to be fairly homogenous

within stands.

Each standing jack pine tree within each plot was identified as live, dead, or top-
killed. Tree height, diameter at breast height (DBH; 1.37 m above ground), dominance
class, and crown ratio were recorded on all jack pine trees in each plot. This study was
limited to analysis of jack pine trees only, so other associated species in each plot were
not measured. From two to six jack pine trees were randomly selected in each plot from a
stratified combination of live, dead, or top-killed trees within jack pine crown classes
(dominant/co-dominant, intermediate, or suppressed). The extraction of cores from a
combination of trees depended upon whether or not those trees were present in the plot,
and what condition the trees were in when cores were being extracted. For example, to.
extract a core from dominant live, dead, and top-killed trees, one of each of those trees
would need to be present in a survey plot at the same time. Plus, if the tree was dead, its
condition would have to be such that an adequate core could be extracted to achieve an

accurate measurement of annual n'n g width.

One increment core from each tree was extracted at diameter at breast height
using an increment borer. Following extraction, cores were placed in a straw, and labeled

with the compartment, stand, and tree numbers from which they were extracted. In the

49

laboratory, cores were mounted and sanded. Annual ring width (to nearest 0.01 mm) was
measured with an optical digitizing scanner and WINDENDRO image analysis software
(Regent Instruments, Inc., Quebec, Que). Because light or missing rings can occur in
jack pine that have been affected by JPBW defoliation or other natural stresses (Kulman
et al. 1963; O’ Neil 1963), caution and precision was used when identifying annual ring

sequences of jack pine cores after digitally scanning them into WINDENDRO.

I collected a total of 1,147 cores from live trees (836 cores), dead trees (168
cores), and top-killed trees (143 cores) that were either in the dominant/codominant,
intermediate, or suppressed crown classes. Because the sample size was so un-balanced, I
chose to statistically compare only the live trees among all regions. Sample sizes were
also comparatively small for live intermediate (156 cores) and suppressed trees (21

cores), so data from those two crown classes were combined for statistical analysis.

Previous jack pine studies have used stem analysis to examine growth patterns
and volume losses resulting from JPBW defoliation (Conway et al. 1999b; Kulman et al.
1963; Gross 1992). Increment cores were chosen because this study spanned a large
geographical area, and non-destructive methods were chosen for tree core data collection.
By using non-destructive increment cores, previously sampled trees can be re-visited, and
future radial growth patterns can be compared with these results.

Annual radial growth and jack pine budworm defoliation

I plotted annual radial growth rates from 1991 — 2000 from a subset of tree cores
which were collected from 55+ year old live dominant trees. From 1991 — 1994,
widespread defoliation from JPBW occurred in all seven surveyed regions (Heym et al.

1993; MI Dept. of Natural Resources 1991 - 1994; WI Dept. of Natural Resources 1992

50

- 1994). The period 1991 — 2000 was chosen because the most recent regional outbreak

of JPBW occurred during this time period.

Statistical analysis

Mean values of average and total annual radial growth rates from the years 1991 —
2000 were grouped for analysis based on categories or threshold values for age, site
index, and basal area typically used for jack pine management in the Lake States (Table
1—2) (Benzie 1977), and previous studies that related these variables to JPBW impact
(Conway et al. 1999b; McCullough et al. 1996). For analysis, tree were divided into three
categories based on tree age (20 - 39 yrs, 40 - 59 yrs, 60+ yrs), and three categories based
on stand basal area (< 16.1 mzlha (< 70 ftzlac), 16.1 — 25.3 mz/ha (70 — 110 ft2/ac), > 25.3
m2/ha (> 110 ftZ/ac)) (Benzie 1977; McCullough et al. 1996). Comparisons of mean
average annual radial growth rates from 1991 — 2000 among basal area categories were
made using data acquired from each forest manager’s inventory database. I then
calculated stand basal area values using jack pine data from live dominant trees, which
were collected from my permanent plots and compared those values with the basal area
data used for annual radial growth rate comparisons to check for accuracy of the
manager’s inventory databases using a standard t-test (p < 0.05). Basal area values from

inventory data were used for analyses.

Two categories for site index were chosen, based on mean and median site index
of jack pine stands in each region. Mean and median site index values ranged from 14.7
m (48.2 ft) to 15.3 m (50.2 ft) for the NL-State, NL-HNF, UP-Raco and UP-East regions
(Table 1-3). I chose 14.9 m (49 ft) as the division between low and high quality site index

for these regions. Mean and median values for the UP-ONF and WI-State regions ranged

51

from 16.4 m (53.8 ft) to 17.2 m (56.3 ft), so I chose 16.8 m (55 ft) as the division between
low and high quality site index for these regions. Mean and median values for the UP-
West region ranged from 18.0 m (59.1 ft) to 18.3 m (60 ft), so I chose 18.3 m (60 ft) as

the division between low and high quality site index (Table 1-3).

Results of the Shapiro-Wilk procedure (Kuehl 2000) indicated that all sets of data
were normal. I used one-way analysis of variance (AN OVA) to assess differences in total
annual radial growth of live dominant trees and live intermediate + suppressed trees
among regions, and between the live dominant and live intermediate + suppressed crown
classes among all regions combined. Average annual radial growth for live dominant jack
pine trees among categories of tree age, site index, and stand basal area were also
analyzed using one-way ANOVA. When the ANOVA results were significant, treatment
means were separated using the Fisher’s least square difference procedure (p < 0.05)
(Kuehl 2000). Interactions between average annual radial growth and tree age, site index,
and basal area categories among all regions (n = 356) were tested using a two-way
ANOVA. Pairwise comparisons between average annual radial growth of live dominant

jack pine trees and site index categories were analyzed using a t-test.

For analysis of annual radial growth rates and JPBW defoliation, I compared
average radial growth rates of live dominant jack pine trees during outbreak years for
each region (NL-State, NL-HNF, UP-Raco, UP-East, and UP-ONF = 1991 — 1993; UP-
West = 1991 - 1994; WI-State = 1992 - 1994), including three years following the final
year of outbreak against the remainder of years until the year 2000 (recovery years). A t-
test was used to analyze statistical significance between average growth rates of outbreak

and growth loss years and growth recovery years.

52

Linear associations between average annual radial growth of live dominant jack
pine trees and stand inventory variables were evaluated using Pearson’s correlation
coefficient. Backward stepping multiple regression was used to assess relationships
between average annual radial growth of live dominant trees and tree age, site index, and
stand basal area for all regions combined (n = 659), and within regions (NL-State; n =
118, NL-HNF; n = 76, UP-Raco; n = 100, UP-East; n = 105, UP-West; n = 79, UP-ONF;
n = 90, WI-State; n = 91). Backward stepping procedures were used in order to adjust
models for the effect of potential collinearity among predictor variables, and to most
efficiently find the most powerful predictors of average annual radial growth. Data were
analyzed using SAS statistical software (SAS Institute, Inc. 2000) at the p < 0.05 level of

significance.

53

Results

Overall growth of live jack pine

Overall, live jack pine trees in the dominant class, and growing in well-stocked
and over-stocked stands, added significantly higher amounts of radial growth than trees
that were growing in the suppressed crown class in under-stocked stands. However,
results did show trends, though insignificant, in decreased annual radial growth as tree
age increased. Among all regions, live dominant jack pine trees grew significantly more
from 1991 —- 2000 than live trees in the intermediate and suppressed crown classes (t =
7.96, P <.0001, d.f. = l, 796) (Table 2-1). Live dominant trees averaged 27.4 i 0.42 mm
of total growth from 1991 — 2000, while live trees in the intermediate and suppressed
classes averaged 20.2 t 0.63 mm of growth during the same 10-yr period.
Regional differences

Live dominant jack pine trees grew significantly more from 1991 -— 2000 in the
UP-West region than the other six regions (F = 16.45, P <.0001, d.f. = 6, 652). Live
dominant trees in the NL-State region grew the least, averaging only 22.0 i 0.90 mm of
growth per tree in the 10-yr period (Table 2-1). Total radial growth averaged between
25.8 mm and 31.8 mm per tree in the other five surveyed regions. Live trees in the
intermediate and suppressed crown classes also grew significantly more in the UP-ONF
and UP-West regions than in the UP-Raco and NL-State regions (F = 4.00, P = 0.0009,
d.f. = 6, 170) (Table 2-1). Intermediate and suppressed trees in the UP-ONF and UP-West
regions averaged 26.4 i 2.54 mm and 26.3 1 2.76 mm, respectively, of growth from 1991

— 2000, while growth of live trees in the intermediate and suppressed crown class

54

averaged from 17.8 i 0.90 mm in the NL-State region to 22.8 i- 2.22 mm in the WI—State
region during the 10-year period (Table 2—1).
Stand inventory variables

Among all regions, annual average radial growth rates of live dominant jack pine
trees seemed to be marginally related to tree age and site index. Generally, variability of
growth rates seemed to be high within and among stands. Among all regions combined,
no significant differences occurred among average annual growth rates of live dominant
trees from 1991 - 2000 among age classes (F = 1.45, P = 0.2354, d.f. = 2, 618) or
between site index classes (t = 1.84, P = 0.0662, d.f. = 1, 638) (Table 2-2). Average
annual growth rates of dominant trees among all regions were significantly correlated
with tree age (r = -0.08, P = .0490) and site index (r = 0.31, P <.0001). However, the low
r-values suggested high variability and a lack of a significant linear relationship. When all
regions were combined, the linear regression model indicated that tree age and site index
were significant predictors of average annual growth of live dominant jack pine during
the 10-yr period (F = 29.36, P <.0001, r2 = 0.13), but the low r2 value again suggests high
variability and a lack of a strong linear model.

Generally, average radial growth rates among age classes within regions were
quite variable. There were no significant differences between average annual radial
growth rates of live dominant trees from 1991 — 2000 among age classes within all
regions except in the UP—Raco region, where trees aged 40 — 59 yrs old had significantly
higher average growth rates than trees that were 20 — 39 yrs old and trees that were 60+
yrs old (F = 7.24, P = 0.0014, d.f. = 2, 72) (Table 2-2). Significant correlations occurred

between average radial growth rates and tree age in the NL-State (r = -0.22, P = 0.0186),

55

UP-East (r = -0.24, P = 0.0141), and UP—West (r = -0.27, P = 0.0165) regions. There were
no correlations between tree age and average radial growth in the NL-HNF, UP-Raco,
UP-ONF, and WI-State regions. Linear regression analysis indicated that tree age was a
significant predictor of average annual growth rates in the NL-State (F = 3.26, P =
0.0242, r2 = 0.05), UP-East (F = 2.80, P = 0.0441, r2 = 0.06), and UP-West (F = 3.07, P =
0.0328, r2 = 0.08) regions. However, the low r-square values suggested a high variability
of annual growth patterns within these regions, indicating that these are potentially non-
linear functions.

Within regions, average radial growth rates from 1991 — 2000 were generally
greater on higher quality sites than on lower quality sites, except in the UP-East region.
This comparison was significant only in the UP-ONF region (t = 3.33, P = 0.0013, d.f. =
1, 80) (Table 2-2). There was a significant correlation between average annual growth
rates and site index in the UP-Raco (r = 0.40, P = 0.0005) and UP-ONF (r = 0.29, P =
0.0070) regions. Linear regression analysis indicated that the UP-Raco region was the
only region where site index was a significant predictor of annual radial growth patterns
during the 10-yr period (F = 8.38, P <.0001, r2 = 0.23), however, the low r2 value again
suggests high variability and the possibility that it was a non-linear model.

Differences between basal area data calculated from permanent plots for live
dominant jack pine trees and inventory database basal area data provided by cooperating
agencies were significant only in the NL-HNF (t = 2.24, P = 0.0275, d.f. = 1, 98) and UP-
West (t = 4.43, P <.0001, d.f. = 1, 96) regions. Within regions, permanent plot basal area
data averaged 0.3 m2/ha, 0.5 m2/ha, and 2.2 mZ/ha lower than inventory database basal

area data in the UP-ONF, UP-Raco, and NL-State regions, while permanent plot basal

56

area data averaged 0.4 mz/ha, 2.6 m2/ha, 4.2 m2/ha, and 8.3 mzlha higher than inventory
database basal area data in the WI-State, UP-East, NL-HNF, and UP-West regions.
However, when all regions were combined, a Pearson’s test of linear correlation resulted
in a low r-value (r = 0.35), suggesting high variability and a lack of a linear relationship
between permanent plot basal area data and inventory database basal area data used for
stand category analysis.

Patterns between stand basal area and annual average growth rates from 1991 —
2000 among all regions were inconsistent. Among all regions combined, live dominant
trees growing in over—stocked stands with basal area greater than 25.3 mzlha had
significantly higher growth rates than trees growing in under-stocked and well-stocked
stands with basal area S 25.3 mzlha (F = 8.89 , P = 0.0002, d.f. = 2, 658) (Table 2-2).
However, significant interactions occurred between stand basal area and tree age (F =
17.69, P <.0001, d.f. = 5, 614), and between stand basal area and site index (F = 51.26, P
<.0001, d.f. = 5, 614) when all regions were combined. Average radial growth patterns of
trees between 20 and 39 yrs old increased with stocking levels until stands reached a
density of approximately 25 mzlha, then leveled off. However, trees older than 40 yrs
continued to increase in annual growth as stocking levels increased, probably a result of
heavier stocked stands growing on higher quality sites. Growth of dominant trees in well-
stocked stands decreased as site quality increased, while annual growth of trees in under-
stocked and over—stocked stands increased with site quality.

Among all regions, average annual growth patterns were significantly correlated
with stand basal area (r = 0.22, P <.0001), likely due to the correlation between stand

basal area and site index (r = 0.31, P <.0001). Linear regression analysis indicated that

57

stand basal area was a significant predictor of average annual radial growth patterns of
live dominant jack pine trees (F = 29.36, P <.0001, r2 = 0.13), however, the indications
from correlation results imply that tree age and site index were more important predictors
of annual radial growth of jack pine than stand basal area.

Within all regions except the NL-HNF and UP-West regions, live dominant trees
in over-stocked stands with basal area greater than 25.3 mZ/ha generally had greater
average annual radial growth rates from 1991 — 2000 than dominant trees growing in
well-stocked and under—stocked stands with basal area S 25.3 mzlha, a potential result of
the significant correlation between stand basal area and site index, except in the WI-State
region where there was no correlation between the two stand variables. The UP-ONF (F
= 3.55, P = 0.0328, d.f. = 2, 88) and WI-State (F = 3.47, P = 0.0354, d.f. = 2, 89) regions
were the only areas where this comparison was significant. There was a significant
correlation between average radial growth patterns and stand basal area in the UP-Raco (r
= 0.43, P = 0.0002) and UP-ONF (r = 0.28, P = 0.0075) regions. Linear regression
analysis indicated that in the UP-Raco region, stand basal area, along with site index, was
a significant predictor of average annual growth rates of live dominant jack pine trees (F
= 8.38, P <.0001, r2 = 0.23).

Efiects of jack pine budworm defoliation

Results did not show any clear or consistent annual losses of radial growth of
dominant jack pine trees that were 55+ yrs old within all seven regions. Results of t-tests
between average annual radial growth during outbreak and radial growth loss years and
recovery years were not significant within all regions. This is likely due to inter and intra-

stand variability of defoliation that occurs during a J PBW outbreak (Volney 1992; Wallin

58

and Raffa 1998). I was also unable to gather specific defoliation data for jack pine trees
that were cored in most regions, so it was unclear whether or not sample trees had been

significantly affected by defoliation.

59

Discussion

I wasn’t expecting to find that older-aged trees had relatively higher growth rates
than younger-aged trees in the UP-Raco, UP-East, UP-ONF, and WI-State regions, and
that trees in well-stocked or over-stocked stands also had higher annual radial growth
rates than trees in under-stocked stands in all regions except the NL-HNF region. There
are a few explanations behind these unpredicted results. Higher average growth rates in
older-aged trees in the UP-Raco and WI—State regions could have been a result of
measured tree cores that were extracted from older trees growing on higher quality sites.
Correlation results indicated that there was a significant linear association between tree
age and site index in these two regions, indicating that older trees growing on higher
quality sites could have relatively higher growth rates than younger trees in these regions.
Relatively higher growth rates of dominant trees in heavier stocked stands could also be
explained by the correlation results, which suggested that higher quality sites in all
regions except the WI-State region contained denser stands of jack pine, and that these
denser stands may have had better growth rates than under-stocked stands which occurred
on lower quality sites.

Because of the large regional area covered and the fact that non-destructive
sampling methods were used, tree core extraction was necessary instead of stem analysis.
I also collected a very large sample size (N = 1,147) of tree cores, so a relatively rapid
method of ring width measuring was necessary (used a digital scanner and computer
software exclusively to measure ring widths of all cores). Consequently, ring widths of
some cores may have been over-estimated because of the possible occurrence of light or

missing rings following defoliation by JPBW (Conway et al. 1999b; Kulman et al. 1963;

60

O’Neil 1963), especially for jack pine trees growing in the intermediate and suppressed
crown classes (Kozlowski 1971). Gross (1992) also noted that the use of tree cores to
identify estimates of defoliation by JPBW can be negatively biased because growth
impact along the bole of the tree can be variable, i.e. growth rings at 1.37 m height may
not fully illustrate the impact to annual ring width patterns resulting from insect
defoliation.
Total growth of jack pine from 1991 — 2000

Results indicated that growth rates of live jack pine trees from 1991 — 2000 were
generally similar among most regions. Live dominant trees had higher growth rates in the
UP-West region than in the other six surveyed regions. It has been well documented that
jack pine can be relatively productive on better quality sites with higher moisture
retention and nutrient-holding capacities than on lower quality sites with excessive
moisture loss and nutrient leaching (Rudolf 1958; Rudolph and Laidly 1990). As
indicated by the stand inventory data I received from regional managers, jack pine
typically grew on relatively higher quality sites in the UP-West region than in most other
regions, except the UP-ONF area, which had generally similar growing conditions. Mean
and median site index values for jack pine in the UP-West region were generally 1.0 to
3.5 m higher than all other regions, where 1991 — 2000 growth rates were generally less.

There are a few reasons why growth rates of jack pine were generally similar in
many of the regions. Dominant trees in the NL~State, NL-HNF, UP-Raco, and UP-East
regions were generally growing in stands with similar site characteristics (Johnson 1990;
Werlein 1998; Whitney 1992). These sites contained generally droughty to moderately

drained sands with very little moisture holding capacity that are of lower site quality than

61

the UP-West and UP-ONF regions (Table l-l), where annual tree growth was generally
much higher.

As expected, overall growth of live dominant jack pine was higher than the
growth of live jack pine in the intermediate and suppressed crown classes. Jack pine is a
highly intolerant species and needs full sunlight in order to maintain adequate annual
growth rates (Rudolph and Laidly 1990). Trees that are over-topped with a lack of
sunlight or are growing with heavy crown competition, such as those occurring in the
intermediate or suppressed crown level, generally have more difficulty capturing
necessary light or mineral resources to gain sufficient annual growth (Kenkel et al. 1989).
These results suggest that the effects of recurring disturbances in jack pine ecosystems
such as JPBW or drought can act as natural thinning agents by stressing undesirable
suppressed or intermediate trees. Heavy and persistent stress could then make
intermediate and suppressed trees vulnerable to mortality, thus freeing up resources for
merchantable trees growing in the dominant crown class (Conway 1998; Gross 1992).
Regional growth rates from 1991 — 2000

There are a few reasons why there were such high amounts of variation between
the basal area data that I calculated from live dominant jack pine trees from permanent
plots and basal area data received from cooperating forest manager’s databases. The
differences were likely due to the fact that my plot-level data was taken from jack pine
trees only, while most stands were not complete monocultures of jack pine, e. g.
plantations, and forest manager’s likely included data on other companion species in
stands while updating their stand inventory databases. On average, basal area data

calculated from my plots were generally higher in four of the seven regions. These results

62

could reflect the potential that the stand inventory data I received from managers may not
have reflected the density of the stand during this survey.

Within regions, relationships between annual radial growth patterns and stand
inventory variables were inconsistent. Results of average radial growth rates for older-
aged trees were higher than what previous studies have found. Brooks et al. (1998) found
that 70+ yr old live jack pine trees in northern Saskatchewan and Manitoba grew at
average rates of 1.0 mm per year, approximately 2.5 mm less than what my results of 70+
yr old dominant jack pine (n = 66) indicated. However, jack pine in the Great Lakes
region generally have longer growing seasons and higher annual precipitation rates
(Rudolph and Laidly 1990), which can contribute to higher annual radial growth
increments.

As previously noted, jack pine trees growing on higher quality sites typically
show higher growth rates than trees growing on lower quality sites (Rudolph and Laidly
1990). This is reflective of the growth of jack pine in all regions except the NL—State and
UP-East regions, which had equal or lesser rates of annual growth on high quality sites
than on low quality sites.

I was surprised to find that dominant jack pine trees in well-stocked or over-
stocked stands generally grew an average of 0.1 to 0.9 mm more per year from 1991 —
2000 than trees growing in under-stocked stands in most regions. This could be explained
by the possible over-estimates of annual ring widths as explained earlier because of our
sampling procedure, or by a few biological factors. Recent studies have found high
mortality rates of intermediate and suppressed jack pine trees in well-stocked and over-

stocked stands (Klein et al. un-published data). It has also been recognized that if jack

63

pine stocking levels get too high, stagnation and excessive intra-stand mortality of
suppressed, low vigor trees can occur (Benzie 1977; Rudolph and Laidly 1990). When
this occurs, valuable light, water, and nutrient resources are released for the remaining,
dominant trees. Therefore, radial increments could increase following this natural
thinning stage in stands (Kenkel et al. 1989). Finally, higher growth rates of trees in
heavier stocked stands could be explained by the previously explained relationship
between stand basal area and site index within most of the regions.

Summary and conclusions

Some apparent inconsistencies in the results could have potentially been avoided
by using different procedures. Previous research has noted that missing or light rings
occur in annual growth rings of jack pine (Kulman et al. 1963; O’ Neil 1963). Methods
attempting to identify growth losses caused by JPBW defoliation among all regions could
have also been modified or corrected by standardizing growth years by identifying one
annual growth ring which was affected by one year of growth loss (i.e. identifying a
widespread drought year, etc.). Results may also have been more consistent if annual
growth patterns would have been analyzed with a binocular dissecting microscope to
account for light or missing rings in a subset of tree cores.

This study is part of a larger research project to describe the current state of the
jack pine resource in Michigan and Wisconsin. Regional growth patterns of jack pine
have been quantified, and have compared the effects of within stand, crown level
competition on the annual growth of trees. This baseline data could be used to build more
specific future studies on the regional variation of annual radial growth rates of this

economically important sub-boreal species.

64

Table 2-1. Comparison of average total growth rates (mm) from 1991 - 2000
(:1; SE) between live dominant, and live intermediate and suppressed trees
among all regions, and within each region. Regions included state land in
northern lower Michigan (NL-State), the Huron-Manistee National Forest (NL-
HNF), the Raco Plains area of the Hiawatha National Forest (UP-Raco), state
land in the eastern Upper Peninsula of Michigan (UP-East), state land in

the western Upper Peninsula (UP-West), the Ottawa National Forest (UP-
ONF), and state land in west-central Wisconsin (WI-State). Different

letters indicate significant differences among regions within crown class
categories (Fisher's LSQ (p < 0.05).

Live Intermediate

 

 

 

 

Region lee Dominant & Suppressed
NL-State 22.0 :1: 0.90 d 18.4 :1: 2.64 c
n=118 n=82
NL-HNF 26.7 :1: 1.20 c 21.8 :t: 1.66 abc
n=76 n=21
UP-Flaco 25.8 x 0.88 c 29.9 1 2.33 bc
n=100 n=30
UP-East 26.7 :1: 1.17 c 20.8 a: 1.57 abc
n=105 ”=7
UP-West 35.0 :1: 1.28 a 44.3 :1: 5.30 a
n=79 n=16
UP-ONF 31.8 a; 0.86 b 26.2 a: 2.87 a
"=90 ”=8
Wl-State 26.7 :t 1.04 c 22.9 a: 2.23 ab
n=91 n=1 1
TOTAL‘ 27.4 :1: 0.42 a 28.4 :1: 1.48 b
n=659 n=177

 

TDifferent letters indicate significant differences between crown class
categories (Fisher's LSD) (p < 0.05).

65

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000005 00:00.50; :_ 0:0. 00000 0:0 0:65:00 .000: 0003 05 :_ 000:0". .0:o=0z 03000 05 ”0:200. 0:0E0 20:00:20 0000000 003 605 0:0P

 

 

 

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66

CHAPTER 3
ACCUMULATION OF COARSE WOODY DEBRIS IN MICHIGAN AND
WISCONSIN JACK PINE STANDS IN RELATION TO STAND AND SITE
VARIABLES
Introduction
Coarse woody debris (CWD) is an important component of forest ecosystem
dynamics. It functions as a source and sink of nutrients (Harmon et al. 1986; Jurgensen et
al. 1987; Krankina et al. 1999; Laiho and Prescott 1999), provides habitat for vertebrate
and invertebrate organisms (Bowman et al. 1999; Carey and Johnson 1995; Edmonds and
Eglitis 1989; Graham 1925; Loeb 1999), serves as a seedbed for understory herbs and
tree seedlings (Harmon et al. 1986; Thompson 1980), enhances soil organic matter, and
regulates soil temperature levels (Marra and Edmonds 1994 and 1998; McFee and Stone
1966). Susceptibility of forests to catastrophic wildfires, however, can be greatly affected
by the accumulation and composition of CWD (Loomis 1977; Tinker and Knight 2001).
Jack pine (Pinus banksiana Lambert) ecosystems are ecologically and

economically important in the Great Lakes region of the US. and throughout much of
Canada. In Michigan and Wisconsin, jack pine forests occur on nearly 485,000 ha (1.2
million acres) (Piva 1997). Jack pine is a rapid colonizer in early forest succession,
tolerates relatively poor, sandy soils, and provides habitat for game and non-game
species, including the endangered Kirtland’s Warbler (Dendroica kirtlandii) (Benzie
1977). More than 270,000 cords of jack pine are annually harvested for wood fiber,
amounting to a stumpage value of nearly $10.1 million (USDA-Forest Service 2002).
Management intensity in jack pine forests has escalated because of the enhanced

economic value of jack pine pulp, which sold at roughly $4/cord in 1991 and $35/cord in

67

2002 (McCullough and Leefers 2000; USDA-Forest Service 2002), leading to more
emphasis on shortening harvest rotations. Effects of management activities on CWD
accumulation in jack pine stands, however, have not been previously addressed.

Jack pine forests in northern Michigan and Wisconsin experience multiple natural
disturbances, such as wind, ice, and heavy snow that can affect the accumulation of
CWD. Strong wind events occur stochastically and may be localized or occur across large
areas (Zhang et al. 1999). While return intervals for catastrophic winds in north-
temperate forests can be measured in centuries, storms with winds sufficient to cause
damage to canopy trees in individual stands occur at frequencies measured in decades or
less (Canham et al. 2001; Foster and Boose 1992). Strong winds can snap the boles of
jack pine, or uproot trees, thus adding significant amounts of large diameter CWD to
stands. Susceptibility of jack pine stands to damage from windstorms is affected by stand
age and structure, slope, and soil type and depth (Attiwill 1994).

Biotic disturbances, including insect outbreaks, can also affect CWD
accumulation and distribution in jack pine stands by killing trees or branches, or
predisposing trees to attack and mortality caused by secondary pests. Outbreaks of jack
pine budworm (Choristoneura pinus pinus Free.) (JPBW), a prominent native defoliator,
occur at six to ten year intervals, and typically persist two to four years (McCullough
2000). Heavy defoliation can result in radial growth reduction, death of the terminal
leader (top-kill), and tree mortality (Graham 1935; Gross 1992; Kulman et al. 1963).
Mortality typically accumulates for two to three years following JPBW population
collapse, and roughly 16% of trees can die following an outbreak (Conway et al. 1999a,

1999b; Gross and Meating 1994; McCullough et al. 1996).

68

Coarse woody debris has received relatively little attention in jack pine stands,
particularly in the sub-boreal region which includes Michigan, Wisconsin, and
Minnesota. Previous studies addressed decomposition rates and changes in chemical
composition of jack pine CWD compared with other sub-boreal species in Minnesota
(Alban and Pastor 1993) and assessed the contribution of CWD to fuel densities in
Michigan and Minnesota (Brown 1966). Pedlar et al. (2002) described the structure of
CWD in jack pine and other boreal forest types in northwestern Ontario, Canada.
Potential associations between CWD accumulation in managed sub-boreal jack pine
forests in relation to site or stand characteristics have not been previously evaluated.

A study was initiated in 2001 to assess the current jack pine resource and to
quantify long-term impacts of JPBW defoliation in six regions of northern Michigan and
one region of Wisconsin. Objectives of this study were to: (l) quantify accumulation,
size, and decay level of CWD in a network of permanent plots recently established to
monitor impacts of JPBW defoliation, and (2) evaluate relationships between site and
stand variables and the volume of CWD in the seven regions. Specifically, I hypothesized
that accumulation of CWD would differ among the seven regions, because of variation in
frequency and severity of disturbance, and management guidelines. Within a given
region, I hypothesized that accumulation of CWD would be positively related to stand

age and stocking level.

69

Methods

Study sites

I established permanent plots from May to August from 2001 -— 2003 in six
regions of northern Michigan and one region in Wisconsin to assess the current state of
jack pine, including CWD accumulation, and to monitor long-term impacts of JPBW.
These seven regions were selected based upon the relative abundance of jack pine in the
area and the frequency of JPBW outbreaks. These regions included state land in the
north-central Lower Peninsula of Michigan (NL-State), the Huron-Manistee National
Forest in the northeastern Lower Peninsula (NL-HNF), the Raco Plains area of the
Hiawatha National Forest in the eastern Upper Peninsula of Michigan (UP-Raco), two
regions of state land in the Upper Peninsula (UP-East and UP-West), the Ottawa National
Forest in the western Upper Peninsula (UP-ONF), and state land in west-central
Wisconsin (WI-State) (Figure 1-1). Soils were generally moderately drained to droughty,
except for two regions (UP-East and WI-State), which contained areas of poorly drained
peat soils (Table 1-1). The terrain was generally level to gently sloping, with moderately
steep areas in the UP-West and UP-ONF regions. The WI-State region had scattered

sandstone mounds (Table 1-1).

Stand selection

A stratified random sampling approach was used to select jack pine stands in each
of the seven regions. Stratification was based on stand age and basal area (Table 3-1),
because of their documented relationship with tree mortality and jack pine volume

(Conway et al. 1999a, 1999b; McCullough et al. 1996), and because these variables are

70

routinely collected and used operationally by forest managers. These variables were
acquired for all jack pine stands from each respective forest management agency’s
database. After stands were grouped by age and basal area, I randomly selected jack pine
stands from each group, based on the percentage of the total number of stands that were
assigned to each stand category. Number of stands per region ranged from 35 stands in
the NL-State region to 78 stands in the UP-Raco region. If stands had been recently
harvested or were not accessible, I randomly selected a replacement stand from the same
group.

Permanent plots were established from 2001 to 2003 in a total of 356 jack pine
stands that encompassed 6,374 ha (15,750 acres) in northern Michigan and Wisconsin
(Table 1-3). Stand age ranged from 10 yr in the UP-ONF region to 117 yr in the UP-Raco
region. Site index ranged from 9.2 m (30 ft) in the UP-East region to 22.3 m (73.2 ft) in
the UP-ONF region, and stand basal area ranged from 2.3 m2/ha (10 ft2/ac) in the NL-
State, NL-HNF, UP-East, and WI—State regions to 50.6 mZ/ha (220 ftzlac) in the UP-Raco

region (Table 1-3).

Measurement of coarse woody debris

One circular, 0.01 ha (0.025 acre) fixed-radius plot was randomly located in each
stand using compartment maps overlaid with a transparent grid. Grid cells were selected
at random for plot center location, and a compass and pacing was used to establish the
permanent plot center in the field. Within each plot, variables measured included jack
pine tree height, diameter at breast height (DBH; 1.37 m above ground), and dominance
class. Area of CWD, including stems and branches or logs 2 7.6 cm (3.0 in) in diameter

on the ground or leaning at less than or equal to 45° from the ground, was quantified

71

along three evenly spaced linear transects (5.6 m by 1 m) in each circular plot (FIA
Monitoring Manual, USDA-Forest Service 2001). An unbiased estimator of the volume
of CWD per unit area was calculated using summed transect data for each stand and the

equation:
v = ([12/80de

where V is volume in m3/ha; L is transect length in m; and d,- refers to the diameter of the
debris in cm (Van Wagner 1968). Average volume of CWD in m3/ha by region was then

estimated.

A decay level of each piece of CWD was modified from Sollins (1982). Coarse
woody debris was classified as light decay: recently down with fine twigs, bark fully
intact; moderate decay: little or no bark, and presence of older aged twigs or branches, no

fine twigs; and high decay: no bark or twigs, and significant woody deterioration.
Statistical analysis

Stand level estimates of CWD volume were grouped for analysis based on
categories or threshold values for age and basal area typically used for jack pine
management in the Lake States (Table 3-1) (Benzie 1977), and previous studies that
related these variables to JPBW impact (Conway et al. 1999a, 1999b; McCullough et al.
1996). Stands were divided into two categories based on age (< 50 yrs, 50+ yrs), and
three categories based on basal area (< 16.1 mz/ha (< 70 ft2/ac), 16.1 - 25.3 mzlha (7O —
110 ftzlac), > 25.3 mzlha (> 110 ftz/ac)) (Benzie 1977; Conway 1999a; McCullough
1996). Comparisons of CWD volume among basal area categories were made using data

acquired from each forest manager’s inventory database. Basal area values were then

72

calculated using jack pine data from live dominant trees, which were collected from my
permanent plots and compared with the basal area data used for CWD volume
comparisons to check for accuracy of the manager’s inventory databases using a standard

t-test (p < 0.05). Basal area values from stand inventory data were used for analyses.

Normality of variables was tested with the Shapiro-Wilk test (Kuehl 2000). Log
transformations did not normalize CWD data, so I used a non-parametric ranked F test to
assess differences in CWD volume among regions and among categories of basal area
across all regions and within regions (Neter et al. 1996). If the F test was significant,
treatment means were separated using a non-parametric multiple comparison procedure
(p < 0.05) (Zar 1984). Interactions among CWD volume and stand age and basal area
categories within regions were tested using a two-way ranked F test (Neter et al. 1996).
Pairwise comparisons between age categories across all regions and within each region
were analyzed using a non-parametric t-test. Linear associations between volume of
CWD and stand age and basal area were estimated across all regions, and within regions,
using Spearman’s nonparametric correlation coefficient (rs). Data were analyzed using

SAS statistical software (SAS Institute, Inc. 2000) at p < 0.05 level of significance.

73

Results
Abundance and volume of coarse woody debris

I encountered a total of 449 pieces (44,900 pieces/ha) of CWD in 128 of 356 of
the jack pine stands we surveyed in the seven regions. Stands with CWD were
significantly older (57.2 i- 1.21 years) than stands where no CWD occurred along plot
transects (48.2 t 1.41 years) (t = 4.78, P < 0.0001, df = 1, 354). Stands with CWD also
had significantly higher stocking levels (17.6 i 0.64 mzlha basal area) than stands where
no CWD occurred along transects (14.2 i 0.67 mzlha basal area) (t = 3.54, P = 0.0005, df
= l, 354). Overall, volume of CWD in the 356 jack pine stands averaged 38.1 i 3.36
m3/ha. Over 50% of the CWD pieces were in 7.6 — 11.4 cm in diameter, which included
mostly twigs and small branches (Figure 3-2). Only 3% of the pieces were in the 2 21.8
cm diameter class, which included fallen trees and large limbs (Figure 3-2). Overall,
nearly 70% of the CWD was lightly to moderately decayed (Figure 3-3).

The UP-ONF region had significantly more pieces of CWD (198 1 32.80
pieces/ha) than the UP-Raco, UP-East, and UP-West regions (F = 4.54, P = 0.0002, df =
6, 349). The UP-Raco region had the fewest number of CWD pieces, averaging only 63 i
13.49 pieces/ha, and had the lowest percentage of stands with CWD at 36%, while the
UP-ONF region had the highest percentage of stands with CWD at 66%. Volumes of
CWD in the UP-ONF (64.2 .4; 12.80 m3/ha) and NL-HNF (60.1 i 10.14 m3/ha) regions
were significantly higher than in the UP-Raco (21.2 i 4.81 m3/ha) and UP-East (22.5 i
5.75 m3/ha) regions (F = 4.73, P = 0.0001, df = 6, 349) (Figure 3-4). Overall, the

percentage of older stands (50+ yrs) with the highest average CWD volume (2 50 m3/ha),

74

ranged from 17% and 22% at the UP-East and UP-Raco regions, to 44% and 66% at the
UP-ONF and HL-HNF regions.

More than 60% of the CWD was in the smallest diameter class in four regions
(NL-State, UP-Raco, UP-ONF & WI-State). Based on personal observation, these pieces
were likely a result of branch breakage from high winds or heavy snow or ice. The NL-
HNF and UP-West regions had greater proportions of CWD that were 2 15 .5 cm (Figure
3-2). Based on observations, these larger pieces of CWD were likely a result of bole snap,
wind-throw, or leftover snags (standing dead trees) following a clearcut harvest. Among
all regions, the UP—Raco and UP-ONF regions had relatively higher proportions of lightly
decayed CWD, while most of the CWD in the NL-State, NL-HNF, UP-East, UP-West,
and WI-State regions was moderately to heavily decayed (Figure 3—3).

Stand inventory variables and C WD accumulation

Basal area data calculated from permanent plots for live dominant jack pine trees
was significantly different from inventory database basal area data provided by
cooperating agencies only in the NL—HNF (t = 2.24, P = 0.0275, d.f. = l, 98) and UP-
West (I = 4.43, P <.0001, d.f. = l, 96) regions. Within regions, plot basal area data
averaged 0.3 mz/ha, 0.5 m2/ha, and 2.2 mzlha lower than stand inventory basal area data
in the UP-ONF, UP-Raco, and NL-State regions, while plot basal area data averaged 0.4
mz/ha, 2.6 mZ/ha, 4.2 mzlha, and 8.3 m2/ha higher than stand inventory basal area data in
the WI-State, UP—East, NL-HNF, and UP-West regions. When all regions were
combined, a Pearson’s test of linear correlation resulted in a low r-value (r = 0.35, P
<.001) suggesting high variability, and likely a non-linear relationship between plot basal

area data and stand inventory basal area data used for stand category analysis.

75

Overall, stands 2 50 years old had significantly higher average CWD volume
(51.6 i 0.62 m3/ha) than younger stands (17.3 i 0.90 m3/ha) (t = 5.56, P <.0001, df = 1,
354). Well-stocked (45.7 i 1.03 m3/ha) to over-stocked stands (47.0 i 2.67 m3/ha) with
basal area 2 16.1 mzlha (7O ft2/ac) also had significantly higher amounts of CWD than
under-stocked stands (28.5 i 1.72 m3/ha) when all regions were combined (F = 3.95, P =
0.0201, df = 2, 353). However, there was a significant interaction between stand age and
basal area (F = 8.22, P <.0001, df = 5, 350), suggesting a possible relationship between
the two variables. When all regions were combined, stand age (p < .0001, rS = 0.27) and
basal area (p = 0.007, rs = 0.18) were significantly correlated with CWD volume in jack
pine stands (n = 356) (Table 3-3). However, the small rs values suggest high levels of
variability among stands and are likely non-linear functions.

The NL-HNF and UP-Raco regions had significantly higher CWD volume in
stands 2 50 yrs old than in younger stands < 50 yrs old (NL-HNF: t = 4.03, P = 0.0002, df
= 1,48; UP-Raco: t = 3.66, P = 0.0005, df = 1, 76). However, a significant interaction
occurred between age and basal area in the NL-HNF region (F = 4.97, P = 0.0047, df = 5,
44). This trend was consistent in other regions, but not statistically significant (Figure 3-
4A). All regions had more CWD volume in well or over-stocked stands (basal area 2 16.1
mz/ha (70 ftzlac)), than in under-stocked stands (basal area < 16.1 m2/ha), but differences
between well-stocked and under-stocked stands were significant only in the UP-Raco
region (F = 6.29, P = 0.0030, df = 2, 75) (Figure 3-4B). Only three regions (NL-HNF,
UP-West, WI-State) had significant correlations between age and CWD volume (Table 3-
3). In the Raco Plains region, basal area was significantly correlated with CWD volume

(p = 0.004, r, = 0.33) (Table 3-3).

76

Discussion
Coarse woody debris volume in Michigan and Wisconsin

Jack pine stands in Michigan and Wisconsin had an average CWD volume of 38.1
m3/ha, which is relatively low compared to other coniferous forest types (Table 3-3).
Several studies have found higher CWD levels in coniferous stands. For example, Butts
and McComb (2000) found that managed stands of Douglas-fir (Pseudotsuga menziesii
Mirb.) in the Pacific Northwest averaged 314.3 m3/ha of CWD, while Clark et al. (1998)
measured an average of 100 m3/ha of CWD in fire-initiated lodgepole pine (Pinus
contorta Dougl.) stands in the Canadian boreal forest. In managed southern yellow pine,
Hess and Zimmerman (2001) recorded an average of 41.2 m3/ha of CWD volume per
stand. Two studies have noted lesser amounts of CWD volume in coniferous ecosystems;
black spruce (Picea mariana Mill.) (Pedlar et al. 2002) and ponderosa pine (Pinus
ponderosa Dougl.)/ Douglas-fir (Robertson and Bowser 1999), which averaged 17.8
m3/ha and 15.9 m3/ha of CWD volume, respectively.

A possible explanation for the relatively lower volumes of CWD in jack pine
ecosystems compared with other forest types could be the differences in maximum
productivity between regions. Tree species in the Pacific Northwest region, such as
Douglas-fir or Sitka spruce (Picea sitchensis Bong.) have much larger growth potentials
than jack pine in the Lake States (Harlow et al. 1996), so when trees of their size die,
much higher volumes of CWD are then produced.

Jack pine regions in Michigan and Wisconsin had different stand and density
structures, along with variation in site characteristics. These regional variations could

have affected the differences in the volume of CWD that we found. The variation of

77

CWD volume could also reflect differences in productivity levels, i.e. the more standing
volume of jack pine an area is capable of growing, the greater potential that a higher
volume of CWD could be left following a disturbance. The frequency and severity of
disturbance may also contribute to variation in CWD volume. Canham et al. (2001)
reported that localized disturbance events such as damaging thunderstorms can occur as
frequently as less than every 10 years. Jack pine is relatively susceptible to wind damage
(Everham and Brokaw 1996), and has generally weak wood structure, making it
susceptible to bole snap during high wind events (Webb 1989). These results give support
to the hypothesis that there is variation in the structure and condition of jack pine stands
across the Lake States region and how they may be managed.
Coarse woody debris in relation to stand variables

There are a few reasons why there were such high amounts of variation between
the basal area data that I calculated from live dominant jack pine trees from permanent
plots and basal area data received from cooperating forest manager’s databases. The
differences were likely due to the fact that my plot-level data was taken from jack pine
trees only, while most stands were not complete monocultures of jack pine, e. g.
plantations, and forest manager’s likely included data on other companion species in
stands while updating their stand inventory databases. On average, basal area data
calculated from my plots were generally higher in four of the seven regions. These results
could reflect the potential that the stand inventory data I received from managers may not
have reflected the density of the stand during this survey.

I hypothesized that the age and stocking level of jack pine stands would positively

affect the accumulation of CWD volume. Our results show that older jack pine stands

78

contributed the highest levels of CWD volume. Similarly, in managed Norway spruce
(Picea abies L. Karst.) and Scots pine (Pinus sylvestris L.) forests in southern Finland,
Siitonen et al. (2000) concluded that the oldest stands (129 — 198 yrs) had significantly
higher average CWD volumes than relatively younger stands (95 — 118 yrs). Because of
the significant correlation between stand age and basal area, we felt that basal area did
not have as important of an effect on CWD volume as stand age.

Further evidence suggests that forest management and stand-initiating disturbance
in the Lakes States region may play important roles in explaining variability of CWD
accumulation among regions. Many of the old stands at the UP-ONF region were in
designated riparian “buffer” zones where some windfall or stem breakage likely occurred,
consequently adding larger diameter CWD (Mellstrom, USDA Forest Service, personal
communication). In the NL-HNF region, a large percentage of the older aged jack pine
stands were damaged or killed by fire in the 1940’s through the 1960’s and not salvaged,
because of a lack of a jack pine market during that time period (McNichols, USDA Forest
Service, personal communication). Mortality from fires, or from other disturbance events,
may have added large diameter CWD in these stands, which could explain the relatively
high CWD levels in the 50+ yr age class in this region.

The management intensity of jack pine stands may also play an important role in
the size structure of CWD. Whole-tree harvesting or felling and bucking to a minimum
diameter of 7.6 cm (3.0 in) DIB (diameter inside bark) have been used as the primary
harvesting techniques among all regions (Beyer, Born, McNichols, Mellstrom, personal
communication). This can result in very little to no large diameter slash left on-site.

Duvall and Gri gal (1999) concluded that the main structural component of CWD in

79

managed red pines stands in the Lakes States was smaller diameter logging slash.
However, their results of logging slash apply mainly to younger stands that have
regenerated following harvest. Logging slash is present in much fewer, if any, quantities
in older jack pine stands, where the majority of CWD was measured in this study. Thus,
logging may not be as important as first thought in adding sufficient amounts of CWD to
jack pine stands. Benzie' (1977) noted that jack pine stands can stagnate under certain
conditions, and heavy competition among smaller diameter individuals can result in high
levels of mortality, thus potentially adding higher amounts of smaller diameter CWD to
stands. The fact that jack pine does not generally grow to be very large sizes (Rudolph
and Laidly 1990) could then be an explanation of why there is generally little amounts of
large diameter CWD in these jack pine regions. A better explanation may be natural
disturbances, such as heavy snow, wind, or hail, which may damage jack pine trees by
breaking off branches or dead terminal leaders from top-killed trees, which could account
for the relatively high levels of smaller diameter CWD in older stands.

Within regions, older aged stands that were well-stocked or over-stocked,
consistently had more CWD volume. Jack pine is a short-lived species, and quickly
deteriorates beyond a threshold age, generally 50 to 60 yrs, depending upon site
conditions (Benzie 1977; Rudolph and Laidly 1990). Consequently, an increase in CWD
volume in old stands should be expected. Attiwill (1994) also noted that older aged jack
pine is more susceptible to branch or bole damage from wind, ice, hail, or heavy snow.
Ecological importance of coarse woody debris

The role that the size and structure of CWD plays as a fire and wildlife habitat

component in jack pine stands is unclear. However, jack pine is known as a pyrophilic

80

species (Rudolph and Laidly 1990), and lightning and human-caused ignition can add
variation to the historic average fire return interval reported by Zhang et al. (1999). I
propose that the persistence of large diameter CWD in older stands, perhaps caused by
wind-throw or stem breakage, is an important component for fuel loads in jack pine.
Alban and Pastor (1993) found that jack pine bolts 1.2 m in length with an average
diameter of 14.7 cm in Minnesota had the slowest decay rates compared with quaking
aspen (Populus tremuloides Michx.), white spruce (Picea gluaca (Moench) V088), and
red pine (Pinus resinosa Ait.) bolts of similar size. Jack pine boles decreased in density
slower than the other species, thus potentially remaining as fuel for relatively longer
periods of time. However, jack pine slash left following harvest practices which is in
contact with mineral soil may decay at faster rates (Harmon et al. 1986). My results were
similar to that study in that nearly 50% of the CWD pieces > 15.1 cm in diameter were in
the low decay stage, while only 32% of the large diameter pieces were highly decayed.
The specific uses and habitat that jack pine CWD provides for wildlife species has
not previously been addressed. Many insect species use all decay stages of CWD during
their life cycles (Edmonds and Eglitis 1989; Graham 1925), and several species of
salamanders and ground dwelling rodents (Bowman et al. 1999; Hayes and Cross 1987)
use CWD as shelter. I made several observations of red squirrels (Tamiasciurus
hudsonicus Erxleben) and black bears (Ursus americanus Pallas) that had apparently
used downed logs for their respective feeding habits in several jack pine stands. Loeb
(1999) found that larger quantities of CWD in managed longleaf pine (Pinus palustris

Mill.) stands in South Carolina provided important habitat for cotton mice (Peromyscus

81

gossypinus) These results suggest that higher CWD volumes in managed jack pine forests
could provide quality habitat for both small and large mammals.
Summary and conclusions

The results described here are part of a larger study focusing on the current state
of the jack pine resource across Michigan and Wisconsin. This research is the first to
quantitatively evaluate CWD in jack pine stands. Future research should focus on the
structure and function of CWD within jack pine regions to understand what factors cause
accumulation of CWD volume, and to further understand what ecological role that CWD

has in jack pine ecosystems.

82

Table 3-1. Characteristics used to stratify jack pine stands for evaluation

of coarse woody debris volume (ms/ha) in six regions of Michigan and

one region of Wisconsin.

 

 

 

 

Age (years) Basal Azrea 1 Number of
Class (m Iha) Stands
Young (< 50) Under 94
Well 40
Over 5
Old (50+) Under 67
Well 106
Over 44
TOTAL 355

 

1Basal area categories represent stands considered to be:
Under-stocked = (< 16.1 m2/ha); Well-stocked = (16.1 - 25.3
mZ/ha); Over-stocked = (> 25.3 m2/ha).

83

Table 3-2. Number of stands sampled and Spearman's non-parametric

correlation coefficients (rs) between coarse woody debris volume (ms/ha) and

stand characteristics among the seven regions. Regions surveyed included
state land in northern lower Michigan (NL-State), the Huron-Manistee National
Forest (NL-HNF), the Raco Plains area of the Hiawatha National Forest (UP-
Raco), state land in the eastern Upper Peninsula of Michigan (UP-East), state
land in the western Upper Peninsula (UP-West), the Ottawa National Forest
(UP-ONF), and state land in west-central Wisconsin (WI-State). Significant

correlations are in bold and p-values are in parentheses (P < 0.05).

 

Correlation with coarse woody debris (m3/ha) (rs)

 

Region N Age (yrs.) Basal Area (ma/ha)
NL-State 35 0.12 (0.480) -0.08 (0.666)
NL-H NF 50 0.49 (0.003) 0.23 (0.102)
UP-Flaco 78 0.20 (0.077) 0.33 (0.004)
UP-East 50 0.18 (0.214) 0.11 (0.452)
UP-West 49 0.31 (0.028) 0.18 (0.203)
UP-ONF 50 0.17 (0.238) 0.08 (0.568)
Wl-State 44 0.31 (0.040) 0.06 (0.669)

ALL 356 0.27 (<.001) 0.18 (0.007)

 

84

 

.0.00000.>> 000 000.02.). 0. 0000.0 00.0 0.00.. .0. 000000. 00.29 0>>0 0.00:. ..00.w

 

0.0 m. u 0.00.0.0 £20.20. 00. ..0 .0 SEE: 0.00m 000000.00:
. 0000 .
00.0022 000 0.50 0 30 000000.).
000. ..0 .0 00.00 0.20 000000000:
0.0 0. 0 0.0.00.0 0.20.0.0. 0000 ..0 .0 .2000 0.00. 000000.).
.00 0. n 0.00.0.0 0.20.0.0. 000. ..0 .0 00:00... 0.00.. 000000003
8.02 e: 005.0 =0 000. .0 .0 0:00 0.8. 88:35
000.. ..0 .0 .:0>0..:.0 0.; 000000.).
0.0 0. u 0.00.0.0 05020.0. .000 0. 3 0000002

00:..0E0..N 0:0 000...

0.0 0. u 0.00.0.0 05:20.0. 0000 ..0 .0 .2000 0.: 000000.).

000. .
hmwgom UCN comtwflcm m mF OmmeNEr—D

x.E-0.0=000 002.0002 00.000
... 00.0000 002.0002 00.000
... 00.0000 002.0002 00.000

.08 00.0 0.0000000... 00x.0.-_00.00 000000
x_E 2.0 2.. 0.02. .0022002 0.80

20000.00 050.000 0 0:0
.020 2000000.. 0 . _ 0 0 0
000.00

0% 2. 228 855-098 828

00>. 00.0 2.0..0> 00.0 0.00.000 000000.).

000.00 0.00.0 00x.:.-.00.00 000000

... 00.0300

00.0 0090050 00.00. 0.0.0022 >200”.

 

00>..00 0E:.0> 0000000.

00080.00 000000.“. 02.0 000.2 03000000.).

00>... 00.0“. 0200....

«.000 C .00002. >0 00>..00 02.0000 00 0.0.. 00.0.3200 002. 00.29 00000

>000; 00.000 .00..0E< 0002 .0 000>. .006. 00.00.00 .0. 00.00.. 2.000 >000; 00.000 .0 0:.20> .00 0.00...

85

 

Coarse Woody Debris (ma/ha)
.L
O

   

 

 

 

 

 

, I l

NL-State NL-HNF UP- UP-East UP- UP-ONF Wl-State
Raco West

0 l

 

Figure 3-1. Mean (:l: SE) volume (ma/ha) of coarse woody debris in jack
pine stands» in seven regions in Michigan and Wisconsin. Regions surveyed
included state land in northern lower Michigan (NL-State), the Huron-
Manistee National Forest (NL-HNF), the Raco Plains area of the Hiawatha
National Forest (UP-Raco), state land in the eastern Upper Pensinsula of
Michigan (UP-East), state land in the western Upper Peninsula (UP-West),
the Ottawa National Forest (UP-ONF), and state land in west-central
Wisconsin (WI-State). Different letters indicate significant differences
among regions (p < 0.05).

86

 

 

I70414cm
90 ‘“ Elt1.5-15.2 cm i
80 -— I15.3-21.6 cm ———————————————————————
70 + I221] cm L

___-__._.___-._..-___-___._-._-.___4

 

 

_ — _ _— _. —_ _ _ _ — — __ .. —_ _ —- _ _. - — _ 1

 

    
  
    

50 . ~ -

__ . .._.. - .. __.

,ii \‘ 7. ‘ f7 .
~ 0 ~; 0 : a \-
|§ . i‘ § ' . i §

NL- NL- UP- UP- UP- UP- Wl-
State HNF Raco East West ONF State

 

 

 

   

Percentage of Coarse Woody Debris
.3:
O
t

Figure 3-2. Distribution of coarse woody debris (ma/ha) by diameter class
(cm) in seven regions in Michigan and Wisconsin. Regions surveyed
included state land in northern lower Michigan (NL-State), the Huron-
Manistee National Forest (NL-HNF), the Raco Plains area of the Hiawatha
National Forest (U P-Fiaco), state land in the eastern Upper Peninsula of
Michigan (UP-East), state land in the western Upper Peninsula (UP-West),
the Ottawa National Forest (UP-ONF), and state land in west-central
Wisconsin (WI-State).

87

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

0 60 ElLow

E IModerate

8 50 0 ——————————————————————— EHigh

>.

040‘“‘““‘ iiigfi _ " "'—‘ ’P

3 iii:

"

9 30 "*4 liii'f; ‘ 'j. "‘ a 11:5; 0 3523* —— ' 0

M i 55?? 235.3:

*5 20 - 0 - — —

0

8’

E 10 _- - - — —

0 .. ._ _

3 21:22; T323

a: O ‘ I I
NL- NL-HNF UP- UP-East UP- UP- Wl-
State Raco West ONF State

Figure 3-3. Distribution of coarse woody debris volume (ma/ha) by decay
class in the seven regions of Michigan and Wisconsin. Low decay refers to
recently fallen pieces with fine twigs and bark fully intact; moderately
decayed pieces had little or no bark or fine twigs; highly decayed pieces
had obvious deterioration of woody tissue. Surveyed regions included
state land in northern lower Michigan (NL-State), the Huron-Manistee
National Forest (NL-HNF), the Raco Plains area of the Hiawatha National
Forest (UP-Raco), state land in the eastern Upper Peninsula of Michigan
(UP-East), state land in the western Upper Peninsula (UP-West), the
Ottawa National Forest (UP-ONF), and state land in west-central
Wisconsin (WI-State).

88

(A) Stand Age (yrs.)

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

150
u, l< 50 years
5 125 “ [350+ years
8 100 a
e if i
8 «,5 75
E 5 5.
‘é’ " r-
o 25 « I I F
o . g
0 ~ L.— _
2 '< 161 m2/ha
(B) Basal Area (m lha) - g
150 0101-253 m2/ha _ '
.2 125 _ a > 25.3 mzlha '-
.0
8 100 .
5’ ’5‘ 75
0 E
g ”E 50
g 25 «
L.
2 o- ~
0 NL- NL- UP- UP- UP- UP- wu-

State HNF Raco East West ONF State

Figure 3-4. Mean (3: SE) volume (ma/ha) of coarse woody debris in seven
regions in Michigan and Wisconsin grouped by (A) stand age (yrs), and (B)

basal area (mz/ha). Regions surveyed included state land in northern lower
Michigan (NL-State), the Huron-Manistee National Forest (NL-HNF), the
Raco Plains area of the Hiawatha National Forest (UP-Raco), state land in
the eastern Upper Peninsula of Michigan (UP-East), state land in the
western Upper Peninsula (UP-West), the Ottawa National Forest (UP-
ONF), and state land in west-central Wisconsin (WI-State). Different letters
indicate significant differences among groups within regions (p < 0.05).

89

CONCLUSIONS, LIMITATIONS, AND FUTURE RESEARCH

Conclusions

Overall, standing volume and growth of jack pine was higher in the UP-West and
UP-ONF regions than the other five regions. The NL—State, NL-HNF, UP-Raco, and UP-
East regions generally had similar levels of standing jack pine volume and annual growth
rates. Among all regions, CWD volume was higher in the UP-ONF and NL-HNF regions
than the other five regions, but trends were more variable. Jack pine mortality was
consistently higher in the intermediate and suppressed crown classes than in the dominant
crown class, while the percentage of standing dead volume was higher in the dominant
crown class than in the intermediate or suppressed classes.

Overall, stand age was most consistently related to mortality, dead volume, and
accumulation of CWD volume. Stands that were under-stocked consistently had less
mortality and dead volume, and had lower amounts of CWD volume, while well-stocked
or over-stocked stands generally had higher levels of mortality, dead volume, and CWD
volume. However, basal area was generally correlated with stand age, so results of
differences among basal area categories should be interpreted with caution.

Management recommendations

One of the main objectives of this study was to collect baseline data about the
current status of the structure of jack pine stands in northern Michigan and Wisconsin. A
reason for collecting these data among several regions of jack pine was to validate the
Jack Pine Budworm Decision Support System (JPBW DSS), a GIS-based extension

which was developed from empirical data collected in the Raco Plains area of the

90

Hiawatha National Forest, one of the surveyed regions. Impact data were collected and
analyzed from other regions, so that relationships between stand inventory variables and
tree mortality, standing dead volume, and annual radial growth among different regions
could be assessed to determine if the J PBW DSS could be applied to other managed jack
pine regions. Overall results of this research indicated that the JPBW DSS could be used
for management of jack pine in other regions other the UP-Raco region, where the model
was developed. Those regions included the NL-State, NL-HNF, and the UP-East regions,
where growing conditions for jack pine (i.e. site index and soil characteristics) seem to be
relatively similar. However, updates or changes may be needed for the J PBW DSS for it
to be validated for use in managing jack pine stands in the UP-West, UP-ONF, or WI-
State regions, where site conditions seem to be different from the other regions.

Other management implications resulting from this study included maintenance of
short rotation ages of jack pine for management in areas where the structure and growth
potential of stands seems to deteriorate beyond a threshold age (generally 50 — 60 yrs).
However, regions with the highest ratio of dead volume to live volume were in areas that
had site characteristics which grew relatively productive jack pine stands. Harvest
rotations may be longer in these regions, but my results tend to contradict that longer
rotations of jack pine are economically viable on higher quality sites. Site index generally
showed inconsistent trends in determining levels of mortality and standing dead volume.
Research previously conducted in the UP-Raco region found that higher quality stands
had more mortality and standing dead volume. Even thOugh my results showed
significantly higher mortality on higher quality sites than on lower quality sites in the UP—

Raco region, none of the other regions showed statistical significance for that

91

comparison. However, trends among all other regions were counter-intuitive to how
management guidelines for jack pine are instituted (Benzie 1977), suggesting that current
guidelines in some regions may need to be re-evaluated. Because stand basal area was
consistently correlated with stand and tree age, and the fact that age consistently had
more powerful relationships with impact variables, implications should be interpreted
with caution. Higher mortality in heavier stocked stands could be interpreted as a result
of natural self-thinning in stands, but because correlations indicated that most heavily
stocked stands were older, it could be concluded that the age of the stands was a more
important factor than stand stocking levels.
Limitations

One of the most highly limiting factors for this study was the availability of time
and budget to either survey more stands within each region, or to survey other regions of
jack pine. The range of jack pine extends into northern areas of both Wisconsin and
Minnesota. Extending our survey into other jack pine areas would have provided
important information on the current state of jack pine in other Lake States areas, and
would have also provided results to other forest manager’s on the availability and validity
for the use of the J PBW DSS model. Further, I was also not able to obtain tree-specific
information about defoliation by JPBW in all regions, which would have been valuable
for my attempts to identify growth losses in merchantable trees resulting from defoliation
by JPBW among regions.

Future Research
Future research should focus on the potential relationships between jack pine

mortality and site index. My results indicated an inconsistent relationship between

92

mortality, dead volume, and site index among regions. However, because of the trends
among regions that more mortality may occur on higher quality sites suggests that jack
pine trees growing on these sites may be more susceptible to mortality by JPBW
defoliation or other disturbances.

Further studies should also focus on exploring more specific growth patterns of
jack pine by using stem analysis techniques in different regions to identify annual volume
losses from impacts on growth by JPBW defoliation. Other studies should also focus on
the ecological importance of CWD in jack pine stands by quantifying characteristics of
downed wood and collecting empirical data about habitat use and importance of CWD

for wildlife species in managed jack pine ecosystems.

93

APPENDICES

94

APPENDIX A

95

Table A-1. Locations and global positioning system (GPS) coordinate waypoints

APPENDIX A

Long-term Impact Plot Locations

of permanent plot centers with identification of compartment numbers, stand

numbers, and plot numbers within the seven surveyed regions in Michigan and

 

 

Wisconsin.
Region GPS Coordinates Compartment Stand Plot
Latitude Longitude
Lower Peninsula -
Michigan

NL-State 44° 44' 07.0" N 84° 15' 01.6" W 9 4 1
44° 44' 03.2" N 84° 15' 02.8" W 9 4 2

44° 45' 59.3" N 84° 15' 03.7" W 9 20 1

44° 45' 58.0" N 84° 15' 01.0" W 9 2O 2

44° 45' 54.9" N 84° 15' 04.7" W 9 20 3

-- -- 9 27 --

44° 44' 29.8" N 84° 14' 55.6" W 9 46 1

44° 44' 42.6" N 84° 15' 03.1" W 9 46 2

44° 44' 46.0" N 84° 15' 01.7“ W 9 46 3

44° 44' 53.8" N 84° 14' 53.1" W 9 46 4

44° 44' 41.0" N 84° 14' 32.0" W 9 46 5

44° 16' 06.8" N 85° 19' 56.5“ W 110 25 1

44° 16' 01.4" N 85° 19' 59.9" W 110 25 2

44° 16' 53.2" N 85° 19' 16.9" W 110 89 1

44° 16' 49.5" N 84° 19' 20.3" W 110 89 2

44°16'48.1"N 85°19'13.7"W 110 89 3

44° 22' 39.5" N 85° 10' 40.7" W 115 78 1

44° 22' 41.0" N 85° 40' 42.2" W 115 78 2

44° 34' 20.4" N 85° 04' 59.1“ W 135 20 1

44° 34' 21.5" N 85° 04' 53.3" W 135 20 2

44° 42' 41.0" N 85° 15' 44.2" W 161 3 1

44° 42' 47.5" N 85° 15' 47.8" W 161 3 2

44° 42' 45.4" N 85° 15' 36.9" W 161 3 3

44° 43' 27.5" N 85° 13' 48.9" W 162 27 1

44° 43' 23.9" N 85° 13' 42.5" W 162 27 2

44° 43' 24.9" N 85° 13' 39.3" W 162 27 3

44° 43' 08.3" N 85° 15' 36.1" W 162 42 1

44° 42' 58.9" N 85° 15' 36.1" W 162 42 2

44° 43' 01.8" N 85° 15' 54.0" W 162 47 1

44° 43' 34.6" N 85° 16' 20.7" W 162 55 1

44° 43' 29.0" N 85° 16' 19.3" W 162 55 2

44° 43' 40.5“ N 85° 16' 09.6" W 162 55 3

44° 43' 45.2" N 85° 13' 53.1” W 164 58 1

44° 43' 45.3“ N 85° 13' 50.6" W 164 58 2

44° 43' 48.1" N 85° 14' 56.9" W 164 69 1

44° 44' 02.1" N 85° 15' 08.6" W 164 69 2

 

96

Table A-1 (cont)

 

Region GPS Coordinates Compartment Stand Plot
Latitude Longitude
NL-State 44° 42' 42.8" N 84° 48' 40.1 " W 179 8 1
44° 42' 47.8" N 84° 48' 44.9" W 179 8 2
44° 41' 37.4" N 84° 49' 56.3" W 180 7 1
44° 41' 38.9" N 84° 49' 47.2" W 180 7 2
44° 41' 43.7" N 84° 49' 47.6" W 180 7 3
44° 41' 28.4" N 84° 49' 59.7" W 180 7 4
44° 41' 55.8" N 84° 48' 53.8" W 180 14 1
44° 41' 49.3" N 84° 48' 53.8" W 180 14 2
44° 41'45.1"N 84° 48'45.1"W 180 14 3
44° 41' 09.1 " N 84° 49' 60.0" W 180 20 1
44° 41' 11.4" N 84° 49' 54.2" W 180 20 2
44° 41' 10.5" N 84° 49' 22.1" W 180 21 1
44° 41' 08.9" N 84° 49' 16.3" W 180 21 2
44° 28' 46.8" N 84° 12' 16.6" W 197 37 3
44° 28' 22.0" N 84° 12' 25.9" W 197 65 1
44° 28' 08.0" N 84° 12' 21.1" W 197 65 2
44° 28' 15.0" N 84° 10' 07.0" W 197 126 1
44° 28' 09.5" N 84° 10' 16.2" W 197 126 2
44° 28' 06.2" N 84° 10' 18.2" W 197 126 3
44° 28' 48.9" N 84° 12' 07.4" W 198 37 1
44° 28' 50.7" N 84° 12' 10.8" W 198 37 2
44° 34' 59.5" N 84° 38' 22.5" W 231 2 1
44° 34' 58.1 " N 84° 38' 26.9" W 231 2 2
44° 34' 58.2" N 84° 38' 32.5" W 231 2 3
44° 34' 53.7" N 84° 38' 40.9" W 231 2 4
44° 34' 30.9" N 84° 37' 10.7" W 231 12 1
44° 34' 18.3" N 84° 37' 20.4" W 231 12 2
44° 34' 20.9" N 84° 37' 15.9" W 231 12 3
44° 34' 21.9" N 84° 37' 36.0" W 231 12 4
44° 48' 33.8" N 84° 39' 18.8" W 233 7 1
44° 38' 30.3" N 84° 39' 09.2" W 233 7 2
44° 37' 30.4" N 84° 39' 05.1 " W 233 27 1
44° 37' 27.3" N 84° 39' 16.6" W 233 27 2
44° 37' 23.6" N 84° 39' 13.1" W 233 27 3
44° 41' 10.2“ N 84° 29' 03.6" W 280 30 1
44° 41' 11.5" N 84° 28' 59.2" W 280 30 2
44° 41' 13.5" N 84° 28' 57.2" W 280 30 3
44° 41' 08.0" N 84° 28' 52.2" W 280 30 4
44° 46' 36.0" N 84° 22' 35.2" W 288 55 1
44° 46' 41.7" N 84° 22' 29.8" W 288 55 2
44° 46' 45.5" N 84° 22' 29.1 " W 288 55 3
44° 46' 37.4" N 84° 22' 25.9" W 288 55 4
44° 47' 24.1 " N 84° 24' 49.3" W 290 32 1
44° 47' 24.5" N 84° 24' 43.5" W 290 32 2
44° 47' 32.0" N 84° 24' 45.5" W 290 32 3
44° 49' 57.4" N 84° 24' 53.5" W 291 37 1
44° 49' 49.9" N 84° 24' 54.1" W 291 37 2

 

97

Table A-1 (cont)

 

 

Region GPS Coordinates Compartment Stand Plot
Latitude Lonmde
NL-State 44° 49' 42.9" N 84° 24' 45.8" W 291 37 3
44° 35' 48.3" N 84° 33' 28.6" W 297 2 1
44° 35' 52.5" N 84° 33' 29.4" W 297 2 2
44° 34' 37.9" N 84° 33' 51.2" W 297 22 1
44° 34' 40.9" N 84° 33' 45.7" W 297 22 2
44° 34' 42.0" N 84° 33' 42.9" W 297 22 3
44° 34' 28.1" N 84° 32' 31.7" W 297 28 1
44° 34' 25.0" N 84° 32' 28.9" W 297 28 2
44° 34' 27.6" N 84° 32' 15.2" W 297 28 3
44° 34' 04.7" N 84° 32' 52.6" W 297 43 1
44° 34' 08.5" N 84° 32' 46.1" W 297 43 2
44° 34' 05.2" N 84° 32' 57.2" W 297 43 3
NL-HNF 44° 38' 08.0" N 84° 35' 15.4" W 31 11 1
44° 39' 07.6" N 84° 26' 24.4" W 61 5 2
44° 39' 07.6" N 84° 25' 36.3" W 66 3 3
44° 39' 25.1" N 84° 24' 10.5" W 67 4 4
44° 38' 01.8" N 84° 23' 27.7" W 63 17 5
44° 39' 28.7" N 84° 21' 20.4" W 83 38 6
44° 38' 21.6" N 84° 19' 13.0" W 110 61 7
44" 39' 08.1" N 84° 18' 00.2" W 110 77 8
44° 44' 12.0" N 84° 17' 40.5" W 110 52 9
44° 40' 16.4" N 84° 17' 08.9" W 111 17 10
44° 38' 31.8" N 84° 17' 26.9" W 113 29 11
44° 38' 13.9" N 84° 16' 32.4" W 115 4 12
44° 38' 48.3" N 84° 31' 21.7" W 40 2 13
44° 38' 55.8" N 84° 29' 33.2" W 41 84 14
44°35'11.2"N 84°15'07.1"W 118 26 15
44° 39' 52.8" N 84° 14' 54.8" W 134 4 16
44° 39' 42.8" N 84° 12' 43.4" W 139 1 17
44° 38' 58.5" N 84° 10' 48.0" W 166 27 18
44° 40' 22.2" N 84° 06' 55.5" W 167 1 19
44° 40' 25.4" N 84° 07' 27.7" W 167 2 20
44° 39' 30.1" N 84° 06' 37.8" W 169 20 21
44° 38' 44.3" N 84° 06' 12.3" W 170 5 22
44° 39' 03.0" N 84° 04' 26.0" W 229 43 23
44° 38' 57.0" N 84° 05' 15.0" W 229 25 24
44° 39' 00.8" N 84° 02' 21.6" W 231 18 25
44° 39' 01.7" N 84° 01' 22.7" W 228 17 26
44° 38' 11.6" N 84° 01' 05.4" W 228 37 27
44° 37' 50.1" N 84° 01' 10.5" W 227 54 28
44° 38' 00.7" N 84° 16' 18.4" W 115 8 29
44° 39' 40.1" N 84° 06' 56.9" W 169 33 30
44° 36' 05.6" N 83° 52' 08.9" W 752 8 31
44° 35' 29.2" N 83° 50' 44.3" W 753 13 32
44° 32' 08.9" N 83° 49' 02.3" W 804 10 33
44° 29' 46.9" N 83° 48' 34.8" W 324 2 34
44° 27' 53.9" N 83° 48' 30.0" W 357 8 35

 

98

Table A-1 (cont)

 

 

Region GPS Coordinates Compartment Stand Plot
Latitude Longitude
NL-HNF 44° 28' 22.5" N 83° 50' 35.8" W 323 12 36
44° 29' 57.7" N 83° 43' 48.9" W 308 5 37
44° 29' 26.2" N 83° 44' 32.8'I W 309 12 38
44° 28' 53.9" N 83° 42' 17.2" W 329 13 39
44° 28' 28.8" N 83° 41' 16.3" W 329 8 40
44° 21' 53.9" N 83° 40' 16.6" W 440 4 41
44° 25' 09.5" N 83° 21' 28.9" W 375 11 42
44° 24' 58.2" N 83° 21' 42.7" W 375 24 43
44° 23' 12.9" N 83° 39' 52.5" W 429 7 44
44° 25' 03.7" N 83° 38' 48.5" W 364 11 45
44° 25' 30.6" N 83° 33' 50.5" W 367 29 46
44° 25' 50.3" N 83° 32' 25.8" W 368 11 47
44° 26' 15.1" N 83° 38' 30.6" W 365 4 48
44° 35' 02.1" N 84° 15' 00.8" W 118 33 49
44° 39‘ 19.4" N 84° 06' 44.6" W 169 21 50
Upper Peninsula -
Michigan
UP-Raco 46°18'46.0" N 84° 53' 59.2" w 78 72 1
46° 18' 54.5“ N 84° 51' 47.5" W 78 17 2
46° 18' 57.1" N 84° 52' 40.5" W 78 16 3
46° 18' 56.1" N 84° 51' 29.2" W 78 23 4
46° 18' 37.2" N 84° 51' 56.9" W 78 27 5
46° 18' 18.1" N 84° 52' 23.4" W 78 55 6
46° 17' 50.5" N 84° 51' 47.5" W 78 80 7
46° 17' 26.9" N 84° 51' 10.4" W 78 46 8
46° 19' 07.6" N 84° 54' 00.1" W 78 69 9
46° 17' 58.2" N 84° 53' 52.5" W 78 4 10
46° 18' 51.7" N 84° 52' 50.1" W 78 18 11
46° 17' 46.6" N 84° 52' 51.9" W 78 40 12
46° 17' 39.9" N 84° 53' 23.8" W 78 39 13
46° 18' 45.9" N 84° 50' 14.3" W 79 19 14
46° 18' 48.9" N 84° 50' 18.2" W 79 18 15
46° 19' 51.5" N 84° 49' 41.1" W 79 3 16
46° 19' 42.8" N 84° 49' 58.5" W 79 9 17
46° 18' 49.1" N 84° 51' 09.5" W 79 22 19
46° 17' 33.2" N 84° 51' 09.5" W 79 25 20
46° 19' 05.5" N 84° 51' 02.6" W 79 33 21
46° 18' 35.9" N 84° 50' 57.3" W 79 45 22
46° 21' 01.0" N 84° 54' 24.4" W 58 71 23
46° 20' 18.2" N 84° 55' 28.7" W 58 68 24
46° 19' 42.0" N 84° 54' 52.9" W 58 17 25
46° 19' 51.5" N 84° 55' 40.3" W 58 27 26
46° 21' 42.6" N 84° 47' 56.4" W 49 4 27
46° 22' 03.2" N 84° 48' 03.2" W 49 61 28
46° 22' 24.8" N 84° 48' 02.9" W 49 60 29
46° 22' 27.2" N 84° 47' 40.7" W 49 5 30
46° 22' 14.8" N 84° 47' 18.4" W 49 9 31

 

99

Table A-1 (cont)

 

Region GPS Coordinates Compartment Stand Plot
Latitude Longflude
UP-Raco 46° 22' 01.1" N 84° 47' 23.8" W 49 11 32
46° 21' 51.1" N 84° 47' 13.3" W 49 21 33
46° 22' 01.6" N 84° 47' 11.0" W 49 29 34
46° 22' 01.4" N 84° 46' 56.2" W 49 30 35
46° 22' 02.3" N 84° 46' 44.4" W 49 36 36
46° 22' 23.9" N 84° 46' 13.7" W 49 23 37
46° 22' 06.2" N 84° 46' 21 .7" W 49 35 38
46° 22' 00.8" N 84° 46' 22.7" W 49 62 39
46° 22' 19.1 " N 84° 46' 09.8" W 49 34 40
46° 22' 04.5" N 84° 46' 13.7" W 49 67 41
46° 22' 02.6" N 84° 45' 23.1" W 49 71 42
46° 21' 49.6" N 84° 46' 28.9" W 49 38 43
46° 22' 23.7" N 84° 45' 45.8" W 49 70 44
46° 22' 38.5" N 84° 46' 03.1" W 49 68 45
46° 22' 33.9" N 84° 46' 07.9" W 49 33 46
46° 23' 23.9" N 84° 46' 11.0" W 30 8 47
46° 23' 18.5" N 84° 46' 07.0" W 30 30 48
46° 23' 16.7" N 84° 46' 19.2" W 30 39 49
46° 23' 55.3" N 84° 46' 48.2" W 30 5 50
46° 23' 46.1" N 84° 46' 15.2" W 30 9 51
46° 23' 13.3" N 84° 46' 27.5" W 30 32 52
46° 23' 07.2" N 84° 47' 13.5" W 31 37 53
46° 23' 17.9" N 84° 47' 28.4" W 31 24 54
46° 23' 26.4" N 84° 47' 00.7" W 31 36 55
46° 24' 04.9" N 84° 46' 55.7" W 31 30 56
46° 24' 08.7" N 84° 47' 38.1" W 31 53 57
46° 24' 29.6" N 84° 48' 04.8" W 31 18 58
46° 22' 36.3" N 84° 48' 09.3" W 32 3 59
46° 22' 36.1 " N 84° 49' 20.6" W 32 84 60
46° 24' 23.4" N 84° 48' 23.9" W 32 53 61
46° 23' 02.8" N 84° 48' 18.5" W 32 21 62
46° 23' 17.5" N 84° 50' 25.4" W 48 32 63
46° 22' 33.4" N 84° 50' 50.4" W 48 26 64
46° 22' 27.8" N 84° 48' 11.3" W 48 1 65
46° 22' 07.0" N 84° 48' 24.2" W 48 15 66
46° 22' 00.3" N 84° 48' 15.4" W 48 5 67
46° 22' 01.7" N 84° 49' 16.9" W 48 18 68
46° 19' 05.5" N 84° 53' 32.5" W 77 3 69
46° 19' 04.6" N 84° 53' 27.3" W 77 61 70
46° 19' 11.0" N 84° 52' 48.5" W 77 12 71
46° 19' 03.2" N 84° 52' 43.9" W 77 58 72
46° 19' 06.3" N 84° 51' 49.1" W 77 21 73
46° 19' 14.2" N 84° 51' 12.8" W 77 69 74
46° 21' 07.4" N 84° 54' 07.9" W 57 7 75
46° 21' 14.8" N 84° 53' 47.2" W 57 6 76
46° 21' 23.0" N 84° 52' 53.9" W 57 14 77
46° 20' 31.2" N 84° 52' 59.9" W 57 3 78

 

100

 

Table A-1 (cont)

 

Region GPS Coordinates Compartment Stand Plot
Latitude ngitude

UP-East 46° 20' 14.8" N 84° 52' 58.5" W 57 26 81
46° 38' 05.0" N 85° 44' 31.1" W 8 1 1
46° 39' 06.2" N 85° 37' 29.3" W 17 95 2
46° 36' 53.6" N 85° 36' 48.3” W 19 7 3
46° 40' 00.8" N 85° 34' 29.4'I W 23 12 4
46° 40' 18.4" N 85° 35' 35.3" W 23 14 5
46° 39' 24.9" N 85° 33' 13.7" W 25 8 6
46° 37' 31.8" N 85° 36' 08.8" W 26 61 7
46° 40' 17.6" N 85° 30' 31 .7" W 32 20 8
46° 40' 03.1" N 85° 28' 36.8" W 33 44 9
46° 40' 16.0" N 85° 27' 36.3" W 33 31 10
46° 40' 13.9" N 85° 27' 18.4" W 33 30 11
46° 41' 15.8“ N 85° 26' 18.6" W 33 3 12
46° 39' 31 .2" N 85° 27' 02.4“ W 34 3 13
46° 49' 23.7" N 85° 28' 03.9" W 34 36 14
46° 38' 40.3" N 85° 28' 12.0" W 34 25 15
46° 35' 52.2" N 85° 28' 30.5" W 35 54 16
46° 36' 42.2" N 85° 30' 06.6“ W 35 62 17
46° 36' 46.7" N 85° 29' 39.1" W 35 60 18
46° 36' 25.2" N 85° 29' 48.8" W 35 58 19
46° 39' 40.4" N 85° 26' 15.9" W 36 25 20
46° 39' 46.8" N 85° 26' 25.5" W 36 24 21
46° 39' 23.3" N 85° 26' 40.0" W 36 37 22
46° 40' 30.5" N 85° 26' 23.7" W 36 13 23
46° 40' 51 .6" N 85° 28' 09.6" W 32 10 24
46° 38' 44.5" N 85° 27' 15.6" W 36 87 25
46° 41' 46.8" N 85° 23' 51.9" W 38 25 26
46° 41' 56.6" N 85° 24' 51.1" W 38 39 27
46° 39' 49.2" N 85° 25' 30.8“ W 39 54 28
46° 25' 37.5" N 85° 50' 07.5" W 93 105 29
46° 42' 54.0" N 85° 08' 46.2" W 56 31 30
46° 42' 45.3" N 85° 08' 48.3" W 56 30 31
46° 38' 33.9" N 85° 07' 39.7" W 58 46 32
46° 38' 52.7" N 85° 04' 43.0" W 63 20 33
46° 44' 11.3" N 85° 01' 10.5" W 59 98 34
46° 45' 06.7" N 85° 06' 03.9" W 59 234 35
46° 35' 48.3" N 85° 06' 47.9" W 65 119 36
46° 38' 27.1" N 85° 04' 12.8" W 63 34 37
46° 38' 30.1" N 85° 04' 14.6" W 63 35 38
46° 40' 30.8" N 85° 06' 24.0" W 62 16 39
46° 41' 43.3” N 85° 05' 48.4” W 61 8 40
46° 42' 55.7" N 85° 05' 51.6" W 60 2 41
46° 43' 05.5" N 85° 05' 46.1" W 60 11 42
46° 37' 43.1" N 85° 06' 23.2" W 65 55 43
46° 37' 36.9" N 85° 07' 13.2" W 65 69 44
46° 46' 07.9" N 84° 57' 40.0" W 59 2 45
46° 38' 13.2" N 85° 06' 03.4" W 63 45 46

 

101

Table A-1 (cont)

 

 

 

Region GPS Coordinates Compartment Stand Plot
Latitude Longitude
UP-East 46° 42' 22.4" N 85° 02' 41 .2" W 67 37 47
46° 41' 13.0" N 85° 06' 27.5" W 61 25 48
46° 43' 02.4" N 85° 01' 27.9" W 67 2 49
46° 40' 13.0" N 85° 28' 40.7" W 33 43 50
UP-West See Table C-2
UP-ONF 46° 37' 08.0" N 88° 37' 50.8" W 5 6 1
46° 36' 57.0" N 88° 39' 02.6" W 6 1 2
46° 37' 03.4" N 88° 39' 16.5" W 6 7 3
46° 36' 48.4" N 88° 38' 60.0" W 6 8 4
46° 36' 17.5" N 88° 51' 11.2" W 13 9 5
46° 35' 35.1" N 88° 51' 14.7" W 13 8 6
46° 36' 46.6" N 88° 38' 49.9" W 19 8 7
46° 36' 33.8" N 88° 37' 49.8" W 19 4 8
46° 33' 59.4" N 88° 49' 46.4" W 26 20 9
46° 35' 43.8" N 88° 50' 19.4" W 26 35 10
46° 35' 00.7" N 88° 37' 09.7" W 20 2 11
46° 34' 59.2" N 88° 50' 49.3" W 27 27 12
46° 34' 07.7" N 88° 50' 27.5" W 27 11 13
46° 34' 16.8" N 88° 51' 23.6" W 28 17 14
46° 34' 52.0" N 88° 51' 53.9" W 28 47 15
46° 34' 46.8" N 88° 52' 19.3" W 28 3 16
46° 33' 32.6" N 88° 57' 45.1" W 65 24 17
46° 33' 13.5" N 88° 58' 18.8" W 65 53 18
46° 33' 14.5" N 88° 58' 13.5" W 25 27 19
46° 32' 47.1 " N 88° 57' 58.1" W 65 56 20
46° 32' 24.8" N 88° 58' 54.4" W 73 51 21
46° 31' 55.5" N 88° 58‘ 31 .2" W 73 3 22
46° 38' 34.1" N 88° 37' 44.2" W 111 43 23
46° 33' 59.1" N 88° 49' 17.1" W 44 21 24
46° 34' 24.9" N 88° 49' 11.5" W 44 8 25
46° 31' 46.8" N 88° 56' 49.2" W 64 31 26
46° 30' 48.2" N 88° 56' 11.3" W 76 15 27
46° 34' 03.6" N 88° 50' 04.4" W 27 34 28
46° 37' 24.9" N 88° 39' 34.3" W 112 57 29
46° 37' 31 .6" N 88° 39' 49.9" W 112 56 30
46° 33' 07.5" N 88° 57' 27.9" W 65 10 31
46° 31' 59.2" N 88° 58' 19.5" W 73 48 32
46° 31' 49.3" N 88° 58' 32.5" W 73 32 33
46° 32' 12.5" N 88° 59' 09.4" W 73 5 34
46° 32' 33.5" N 88° 59' 00.1" W 66 22 35
46° 38' 33.6" N 88° 40' 22.5“ W 112 22 36
46° 37' 47.9" N 88° 40' 03.8" W 112 53 37
46° 37' 44.9" N 88° 39' 48.7" W 112 59 38
46° 37' 15.8" N 88° 39' 24.7" W 6 2 39
-- -- 73 39 40
46° 33' 11.7" N 88° 59' 21.8" W 38 13 41
46° 38' 51 .7" N 88° 38' 33.5" W 112 33 42

 

102

Table A-1 (cont)

 

 

Region GPS Coordinates Compartment Stand Plot
Latitude Longitude
UP-ONF 46° 35' 29.3" N 88° 36' 59.2" W 19 22 43
46° 38' 26.6" N 88° 37' 05.8" W 111 30 44
46° 38' 33.6" N 88° 37' 10.7" W 111 55 45
46° 37' 22.7" N 88° 39' 24.6" W 112 58 46
46° 33' 46.0" N 88° 57' 02.1 " W 65 1 47
46° 36' 55.9" N 88° 37' 48.5" W 5 2 48
46° 33' 55.5" N 88° 57' 26.4" W 39 25 49
46° 32‘ 39.7" N 88° 49' 31 .6" W 60 9 50
Wisconsin
Wl-State 44° 15' 22.1” N 90° 50' 34.0" W 5 8 1
44° 21' 58.6" N 90° 41' 18.5" W 39 10 2
44° 10' 45.5" N 90° 37' 04.5" W 93 2 3
44° 11' 51.6" N 90° 38' 19.0" W 84 2 4
44° 12' 40.2" N 90° 38' 09.8" W 79 7 5
44° 14' 01.5" N 90° 39' 15.6" W 72 10 6
44° 13' 35.8" N 90° 34' 09.9" W 76 4 7
44° 16' 18.4" N 90° 38' 36.7" W 64 5 8
44° 16' 11 .6" N 90° 36' 58.7" W 69 15 9
44° 15' 49.9" N 90° 37' 02.5" W 69 20 10
44° 15' 53.8" N 90° 36' 19.9" W 69 9 11
44° 20' 02.4" N 90° 40' 14.3" W 45 1 12
44° 19' 48.8" N 90° 34' 01.9" W 50 3 13
44° 20' 04.7" N 90° 39' 36.4" W 45 3 14
44° 18' 28.0" N 90° 38' 57.2" W 56 10 15
44° 23' 35.9" N 90° 44' 32.4" W 14 9 16
44°18'13.1"N 90°38'15.1"W 56 13 17
44° 17' 13.7" N 90° 38' 38.9" W 63 2 18
44° 16' 53.4" N 90° 38' 25.4" W 62 5 19
44° 20' 09.9" N 90° 41' 48.5" W 28 9 20
44° 22' 04.1" N 90° 41' 26.9" W 17 5 21
44° 19' 24.5" N 90° 38' 27.6" W 46 2 22
44° 15' 47.1" N 90° 35' 49.4" W 69 22 23
44° 21' 00.8" N 90° 44' 06.6" W 25 8 24
44° 18' 22.0" N 90° 39' 07.1" W 56 12 25
44° 24' 44.4" N 90° 39' 37.6" W 32 18 26
44° 25' 30.7" N 90° 40' 05.1" W 32 12 27
44° 24' 30.9" N 90° 39' 24.6" W 31 1 28
44° 24' 25.8" N 90° 38' 25.1 " W 33 1 29
44° 24' 16.5" N 90° 38' 54.3" W 33 6 30
44° 23' 48.9" N 90° 40' 39.5" W 34 6 31
44° 23' 40.0" N 90° 42' 00.9" W 10 14 32
44° 23' 32.3" N 90° 43' 08.1" W 12 1 33
44° 23' 05.3" N 90° 43' 03.0" W 12 5 34
44° 23' 07.8" N 90° 41' 30.0" W 11 7 35
44° 21' 56.7" N 90° 42' 11.1" W 18 2 36
44° 22' 59.5" N 90° 43' 18.7" W 13 2 37
44° 23' 29.2" N 90° 44' 12.4" W 13 11 38

 

103

Table A-1 (cont)

 

Region GPS Coordinates Compartment Stand Plot
Latitude Longitude

Wl-State 44° 23' 26.9" N 90° 43' 58.9" W 13 13 39
44° 23' 17.6" N 90° 44' 02.3" W 13 4 40

44° 22' 46.0" N 90° 40' 15.7" W 35 8 41

44° 21' 53.7" N 90° 41' 54.5" W 18 1 42

44° 20' 09.0" N 90° 45' 09.0" W 30 2 43

44° 22' 04.1" N 90° 44' 53.7" W 21 2 44

 

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APPENDIX B

109

APPENDIX B

Measurement Conversions

Table B-1. Metric - English conversion table.

 

 

 

 

 

 

Metric English
Length
1 m 3.281 ft
Area
1 m2 10.76 n2
1 ha 2.477 ac
1 mz/ha 4.346 ftz/ac
Volume
1 m3 35.32 0"
1 m3 0.4205 cds
1 m3/ha 14.26 ft3/ac
1 mama 0.1698 cds/ac
Suelndex
14.9 m 49ft
16.8 m 55 ft
18.3 m 60 ft
Basal Area
16.1 m2/ha 7o tt2/ac
25.3 mzlha 110 ftzlac

 

110

REFERENCES CITED

111

REFERENCES CITED

Alban, D.H., and Pastor, J. 1993. Decomposition of aspen, spruce, and pine holes on
two sites in Minnesota. Can. J. For. Res. 23: 1744-1749.

Attiwill, RM. 1994. The disturbance of forest ecosystems: the ecological basis for
conservative management. For. Ecol. and Mgt. 63: 247-300.

Beland, M., and Bergeron, Y. 1996. Height growth of jack pine (Pinus banksiana) in
relation to site types in boreal forests of Abitibi, Quebec. Can. J. For. Res. 26: 2170 —
2179.

Benzie, J .W. 1977. Jack pine in the north central states. US. For. Ser. Gen. Tech. Rep.
NC-32.

Bemdt, L.W. 1988. Soil survey of Baraga County, Soil Conservation Service.

Beyer, Tim. Wisconsin Department of Natural Resources, Black River State Forest
Manager. January 30, 2004.

Born, Doug. USDA-Forest Service, Hiawatha National Forest Silviculturalist. January
27, 2004.

Bowman, J .C., Sleep, D., Forbes, G.J., and Edwards, M. 1999. The association of
small mammals with coarse woody debris at log and stand scales. For. Ecol. & Man.
129: 119—124.

Boyer, W.D. 1987. Volume growth loss: A hidden cost of periodic prescribed burning in
longleaf pine. S. J. Applied For. 11: 154 — 157.

Brooks, J.R., Flanagan, L.B., and Ehleringer, JR. 1998. Responses of boreal conifers
to climate fluctuations: indications from tree-ring widths and carbon isotope analyses.
Can. J. For. Res. 28: 524 — 533.

Brown, J.K. 1966. Forest floor fuels in red and jack pine stands. USDA For. Serv. Res.
Paper NC-9.

Brubaker, LB. 1978. Effects of defoliation by douglas-fir tussock moth on ring
sequences of douglas-fir and grand fir. Tree-Ring Bull. 38: 49 - 60.

Butts, S.R., and McComb, W.C. 2000. Associations of forest floor vertebrates with

coarse woody debris in managed forests of western Oregon. J. of Wildlife Man. 64(1):
95-104.

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