3
z a; - R 4 ‘
L. ‘ . Lw

..
$31.3. -‘ ' : . a ~ . ~ . ‘ ~~ ‘ .ztgfg-mw
“ ' '1. ' ‘ ' T33"? ‘ ‘13:;

n

1.. 1;: '1.

, A
.‘ N v ' .
fr‘f'rl‘: an ‘
3‘7 E113"
' .‘w I’

,_' 1 "3'1"" {Ft .
”1414;?" f“

 

IUIIHIIIll!Ill!Hllllllllllllllllllllllllllllfllllllllllllll

1293 01044 8342

This is to certify that the

thesis entitled

The Effects of Hydrology, HicrotOpography and
Hater Chemistry on Northern Hhite-Cedar Regeneration
in Michigan's Upper Peninsula

fresentcd by

Rodney'Allen Chilner

has been accepted towards fulfillment
of the requirements for

Masters Forestry

 

 

degree in

   

Major professor
13mm

0-7539 MS U is an Affirmative Action/Equal Opportunity Institution

 

 

Mammy
M'Chloan State
nlverslty

 

 

 

o :53 race: IQ

PLACE ll RETURN BOXtomnovotNoohookouftom younooord.
TO AVOID FINES Mum on or More data duo.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

MSU loAnNfinndlvomqud Opportunity Insulator:

 

 

THE EFFECTS OF HYDROLOGY, MICROTOPOGRAPHY AND WATER
CHEMISTRY ON NORTHERN WHITE-CEDAR REGENERATION IN MICHIGAN'S
UPPER PENINSULA

By

Rodney Allen Chimner

A THESIS

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

MASTERS OF SCIENCE

Department of Forestry

1994

ABSTRACT

THE EFFECTS OF HYDROLOGY, MICROTOPOGRAPHY AND WATER
CHEMISTRY ON NORTHERN WHITE-CEDAR REGENERATION IN MICHIGAN'S
UPPER PENINSULA

By

Rodney Allen Chimner

Many harvested cedar sites have not regenerated back to
cedar, but have been colonized by species such as balsam fir
(Abies balsamea M.) and tag alder (Alnus rugosa DuRoi.). A
naturally regenerating cedar swamp on Michigan State's Upper
Peninsula Tree Improvement Center (UPTIC), near Escanaba
Michigan, was used to study this problem. Significantly
more cedar regenerated in some areas of the study site while
large numbers of alder and shrubs regenerated in other
parts. Twenty-four plots (6m x 6m) where established to
collect data on; hydrology, water chemistry,
microtopography, stand composition and stem density.

Density of cedar regeneration was positively and
significantly correlated with high denSity of hummocks and
greater unsaturated soil depths. Cedar regenerated best in
drier conditions compared with alder and shrubs which

regenerated best in the wetter areas of the swamp.

Copyright by

RODNEY ALLEN CH IMNER

1994

iii

This research is dedicated to everyone involved with
northern white-cedar, especially those who work long hours

in cedar swamps.

iv

ACKNOWLEDGMENTS

I would first like to thank Dr. Bud Hart for his
assistance and guidance on my graduate program and research.
Plus his ability to allow me the freedom to chase my
educational dreams but yet still be there to keep me focused
and in the right direction. I would also like to thank my
committee members, Dr. King and Dr. Lantagne for greatly
aiding me with my thesis.

I am deeply indebted to Ray Miller for all his help and
insights on this project. Everything that I have learned
about cedar, I owe to him in one way or another. I am also
very thankful to the UPTIC staff of Brad Bender and Kyle
Zuidema. This research project would have been impossible
with out their hard work and help. I also owe thanks to
Mike Zuidema for his cedar knowledge and flexibility to
allow me to pursue my research while doing research for him.

I would like to thank U.P. Whitetails for helping fund
my research and others like it. I commend you on your
concern and ability to take action.

Thanks must be given to Andy Burton for all his help and
ability to run the DC-Argon Plasma machine. I would like to
thank all my friends in the Forestry Department who made
graduate school a positive experience which I will never

V

forget. Special thanks to Sigrid Resh and my family. They

have always been there for me, even if they didn't know it.

vi

TABLE OF CONTENTS

Page

LIST OF TABLES ........................................... ix
LIST OF FIGURES .......................................... Xi
CHAPTER 1. INTRODUCTION AND LITERATURE REVIEW ............. 1
Introduction .......................................... 1
Peatlands ............................................. 3
Peatland water chemistry .............................. 6
Peatland hydrology ................................... 10
Peatland microtopography ............................. 13
NOrthern white-cedar germination ..................... 15
CHAPTER 2. OBJECTIVES AND METHODS ....................... 18

Site location, history and preliminary study results .18

Objectives And hypothesis's ......................... 22
Research methods ..................................... 23
Hydrology ......................................... 23

Water chemistry ................................... 24
Microtopography ................................... 25

Data Analysis ........................................ 27
CHAPTER 3. RESULTS AND DISCUSSION ........................ 29
Stand Composition .................................... 29
Soils ................................................ 32
water levels ......................................... 34
Microtopography ...................................... 42
Water chemistry ...................................... 47
CHAPTER 4. SUMMARY AND FUTURE RESEARCH ................... 54

vii

Summary .............................................. 54

Future research ...................................... S9
APPENDICES
APPENDIX A. Number of trees and shrubs per plot. ........ 61
APPENDIX B. Data from.microtopography transects. ........ 67
APPENDIX C. Regression results. ......................... 74

APPENDIX D. Average surface elevations, depths of organic

soil (peat), water table elevations and maximum.water table

fluctuations. ............................................ 75
APPENDIX E. Water table profiles. ....................... 77
BIBLIOGRAPHY ............................................. 80

viii

LI ST OF TABLES

Table Page
1. Range of important characteristics of different
decomposition levels of peat from the northern
Lake States . .................................. S

2. Calcium, specific conductivity and pH levels for
peatland types ((Glaser et al., 1981, 1990).... 7

3. Summary of stand composition of study site.... 30

4. Depth of unsaturated soil (cm). ............... 41

5. The percent of trees and shrubs growing on
different microtopography types ............... 43

6. Microtopography percentages in regenerating

area. ......................................... 44
7. Specific conductivity, pH, dissolved oxygen and

calcium levels for 6/26/93 .................... 48
8. Specific conductivity, pH, dissolved oxygen and

calcimm levels for 9/10/93 .................... 49

9. Average calcium, specific conductivity and pH
levels of the study site compared to Glaser et
a1. (1981, 1990) levels. ...................... SO

A.1 Number of trees and shrubs in plots 510, 511,
512 and 513. .................................. 61

A.2 Number of trees and shrubs in plots 520, 521,
522 and 523. .................................. 62

A.3 Number of trees and shrubs in plots 530, 531,
532 and 533. .................................. 63

ix

Number of trees and shrubs in plots 540, S41,
S42 and S43. .................................. 64

Number of trees and shrubs in plots 550, 551,
552 and 553 ................................... 65

Number of trees and shrubs in plots S60, S61,
S62 and 563. .................................. 66

Data from microtopography transects. .......... 67

Results of regression between depth of organic
soil and density of cedar regeneration. ....... 74

Average surface elevations, depth of organic
soil (peat), water table elevations and maximum
water table fluctuations. ..................... 76

Figure

1.

10.

11.

LIST OF FIGURES

Page

Map of Michigan showing Escanaba. ............. 19
Location of cedar study site within UPTIC
wetland complex and estimated surface contour
lines. ........................................ 20
Study site layout. ............................ 21
Microtopography types. ........................ 26

Graph of data with line of best fit, form of
linear transformation and results of regression
between density of cedar(# per plot) and density
of shrubs (# per plot) ........................ 31

Ground, high water with flow lines, and mineral
soil surfaces. ................................ 33

Water table profiles for transect line 510—560
for dates; 7/6/94, 7/26,94, 8/25/96 & 9/10/94. 35

Water table profiles for transect line 511-561
for dates; 7/6/94. 7/26,94. 8/25/96 & 9/10/94. 36

Graph of data with line of best fit, form of
linear transformation and results of regression
between the fluctuation of the water table (cm)
and the distance from.the railroad ditch (m).. 38

Graph of data with line of best fit, form of
linear transformation and results of regression
between the density of cedar regeneration (per
plot) and water table fluctuation (cm). ....... 38

Graph of data with line of best fit, form of
linear transformation and results of regression
of July 6th water table elevations (m) vs.
density of cedar regenerating (per plot) ...... 39

xi

12.

13.

14.

15.

16.

17.

18.

19.

El.

Graph of data with line of best fit, form of
linear transformation and results of regression
between unsaturated soil depth (cm) for the July
6th water table and density of cedar
regenerating (per plot) ....................... 39

Graph of data with line of best fit, form of
linear transformation and results of regression
between unsaturated soil depth on July 6th and
density of shrubs regenerating (per plot) ..... 4O

Graph of data with line of best fit, form of
linear transformation and results of regression
between percent hummocks of plots and density of
cedar regenerating (per plot) ................. 46

Graph of data with line of best fit, form of
linear transformation and results of regression
between percent hummocks per plot and density of
shrubs regenerating (per plot) ................ 46

Graph of data with line of best fit, form of
linear transformation and results of regression
between June 26th dissolved oxygen levels (ppm)
and distance from the railroad ditch (m) ...... 52

Graph of data with line of best fit, form of
linear transformation and results of regression
between June 26th calcium levels (mg/l) and
distance from the ditch (m) ................... 52

Graph of data with line of best fit, form of
linear transformation and results of regression
between June 26th dissolved oxygen levels (ppm)
and density of cedar regenerating (per plot).. 53

Graph of data with line of best fit, form of
linear transformation and results of regression
between June 26th calcium levels (mg/l) and
density of cedar regenerating (per plot) ...... 53

Water table profiles for transect line 512-562
for dates; 7/6/94, 7/26,94. 8/25/96 & 9/10/94. 78

xii

E2. Water table profiles for transect line 513-563
for dates; 7/6/94, 7/26,94, 8/25/96 & 9/10/94. 79

xiii

CHAPTER 1
INTRODUCTION AND LITERATURE REVIEW
Introduction

Northern white-cedar (Thuja occidentalis L.) occupies
roughly 2 million acres of commercial forest land in the
northern Lake states with three-fifths occurring in northern
Michigan. The majority of northern white-cedar stands occur
in forested wetlands with organic soil (peatlands). Usually
northern white-cedar are intermixed with balsam fir (Abies
Balsamea M.), black spruce (Picea mariana M.), tamarack
(Larix laricina Du Roi) and black ash (Fraxinus nigra)
(Johnston, 1977).

The demand for northern white-cedar forest products
coupled with high browse demand by wildlife have caused a
serious crisis. Most cut cedar sites have not regenerated
back to cedar stands, but instead have been replaced by
species such as tag alder (Alnus rugosa DuRoi), balsam fir
and red maple (Acer rubrum L.)(Nelson, 1951; Zasada, 1952;
Thornton, 1957). A recent Michigan Department of Natural
Resources study shows that 50 years after cutting in a cedar
swamp, cedar is still absent with tag alder and balsam fir
dominating in the cut areas (Miller, Chimner & Zuidema,
1994). Because cedar regeneration success has been so low,
a partial moratorium on cutting cedar has been instituted in

the region by both state and federal agencies until suitable

regeneration systems can be developed (Miller, Elsing,
Lanasa & Zuidema, 1990).

Many reasons for such low cedar regeneration success
have been suggested through the years. The reasons are
mainly concerned with either silvicultural practices, or
with over browsing by wildlife. Both of these factors are
extremely important when trying to regenerate cedar.
Hydrological processes are another area that must be
understood if a complete picture of cedar regeneration is to
be drawn. These hydrological processes have been largely
ignored or only casually discussed in previous research.

All natural wetland functions are a result of or are
related to the hydrology of the wetland (Carter, Bedinger,
Novitzki & Wilen, 1978). As a result, when dealing with
forestry in wetlands, the hydrology must be taken into
consideration along with normal silvicultural considerations
and techniques. In fact, hydrology is probably the single
most important process in determining the chemical and
biological characteristics of wetlands (Mitch & GoSselink,
1986).

Another consideration that must be taken into account
when working with wetland forestry is the microtopography of
the area. Microtopography is micro relief (e.g., hummocks)

that is common in peatlands. The microtopography throughout

the wetland interacts with the hydrology creating many
diverse micro habitats.

This research was conducted to follow up results of a
preliminary study which found an increasing number of
northern white-cedar regenerating near a railroad ditch. My
objectives were to determine if hydrology, microtopography
and water chemistry of the area affected northern white-
cedar regeneration. In order to better understand the
research results, a literature review on peatlands, peatland
water chemistry, peatland hydrology and peatland

microtopography follows.

Peatlands

Almost 15 million acres of peatlands have formed in the
Great Lake States region since the end of the glacier period
(Boelter & Verry, 1977). Peatlands are wetlands that
accumulate organic material (peat) by creating more biomass
than can be decomposed. The rate of peat accumulation is
dependent on two opposing factors, rate of production and
decomposition rate of plant matter (Romanov, 1961; Ivanov,
1981; Stanek & Worley, 1984; Winter & Woo, 1990).

Different origins of peat deposits can form slightly
different physical properties. Peat is classified by its
origins in four main categories; sedimentary (i.e. floating

aquatic plants, algae), moss (remains of mosses), herbaceous

(i.e. remains of cattails, sedges, reeds) and woody peat
(i.e. remains of trees, shrubs). Peat deposits become
parent material for organic soils (Histosols). As peat
deposits weather, they decompose from identifiable plant
material to unidentifiable material that resembles colloidal
clay. Fibric is the least decomposed peat and can be
identified by the characteristic that almost all the organic
residue is identifiable. Hemic is partially decomposed
where only part of the organic residue can be identified.
Sapric material is the most decomposed with no identifiable
organic residue. Organic soils are described by their
degree of decomposition. If the organic soil is fibric,
than it is referred to as peat soil. Sapric deposits are
referred to as mucks, while hemic deposits are called mucky
peats (Soil Survey Manual, 1993).

Many physical properties are determined by the level of
peat decomposition (Table 1). The more decomposed the peat,
the lower the hydraulic conductivity. Fibric peat has large
pores which are easily drained while sapric peat has a
consistency and hydraulic conductivity similar to that of
clay. The rate of water movement through sapric peats are

often a thousand times slower than that of fibric peats.

Table 1.

Range of important characteristics of different

decomposition levels of peat from the northern Lake States

 

 

 

(Modified From Boelter and Verry, 1977).
Degree of Total Specific Hydraulic Bulk
Decomposition Porosity Yield Conductivity Density
(% volume) (% volume), (m/d) (g/cm3)
Fibric >90 >45 >1.3 <0.09
Hemic 84-90 10-4 0.01-1.3 0.09-2.0
Sapric <84 <10 <0.01 >0.20

 

 

 

 

 

As organic material begins to accumulate,

the older more

decomposed bottom.layers become buried by the newer less

decomposed top layers.

within peatlands.

This creates a vertical profile

This vertical zoneation in peatlands is

often delineated into two horizons, a relatively thin active

layer (acrotelm) and a usually thick inactive layer

(catotelm).

composed mainly of fibric peat.

has a high hydraulic conductivity.

The acrotelm is

The active layer is the upper most layer

This layer is porous and

subjected to frequent fluctuations of temperature, moisture

and aeration.
acrotelm into the catotelm.

comprised of sapric and hemic peats.

Most root systems do not penetrate below the

The lower inactive layer is

The catotelm has a

very low hydraulic conductivity which allows very little

 

water to flow vertically through peatlands. (Boelter &

Verry, 1977 & 1978; Ivenov, 1981; Winter, 1988)

Peatland water chemistry

Peatlands can be classified by their hydrological inputs
and chemical characteristics. Bog peatlands are isolated
from.the groundwater table (ombrotrophic) with precipitation
as their only source of water input. Bogs generally have
low pH, base status and nutrient levels. They are normally
considered to have low biodiversity consisting mainly of
black spruce (Picea mariana), sphagnum.mosses (Sphagnum
spp.), leather leaf (Chamaedaphne calyculata L.),
blueberries (vaccinium spp.) and sedges (carex spp.). Fen
peatlands have groundwater inputs (minerotrophic), and
generally have a higher nutrient status and pH than bogs.
Fens, therefore, have a greater diversity of species and
higher productivity. Some species associated with fens
include; northern white-cedar, tamarack, balsam fir,
sphagnum.mosses, sedges and numerous other species (Boelter
& Verry, 1977; Brown, 1988; Crum, 1988; Cwikiel, 1992).

Peatland water chemistry is primarily determined by the
source of their hydrological inputs. Bogs, which are fed by
atmospheric deposition, have water chemistry similar in
composition to that of rain water. The water chemistry of

minerotrophic fens reflect the composition of the

surrounding basin. The geology and soils of the area
interact with the local groundwater and surface water, which
in turn determines the water chemistry of the fen. For
example, groundwaters in calcareous terrain contain large
amounts of calcium and magnesium, while groundwaters in
granitic basins contain low amounts of these elements. The
nutrient status of fens located within these different
watersheds would be very different (Verry, 1975; Shotyk,
1984).

Fens can be further classified by their water chemistry.
Glaser et a1. (1981, 1990) delineated peatland types by pH,
specific conductivity and calcium groundwater levels (Table
2). A strong correlation was noticed in northern Minnesota
between specific conductivity, calcium and pH levels of the

groundwater and distribution of northern white-cedar with

cedar being an extremely rich fen indicator species.

 

 

 

 

 

Table 2. Calcium, specific conductivity and pH levels for
peatland types ((Glaser et al., 1981, 1990)
Peatland type pH Specific Calcium
Cond (uS cm-l) 4(mg/l)
Extremely Rich Fen >6.8 >82 >20
Rich Fen 6.0-6.8 23-82 10-20
Poor Fen 4.3-6.0 3-10
Bog <4.3 12-27 <3

 

 

 

 

 

 

Water flow and chemistry are primary factors in northern
white-cedar distribution and growth (Pregitzer, 1990; Glaser
et al., 1991). Many studies report that cedar are found in
areas with neutral to basic pH levels (5.5 - 8.0), with high
nutrient and oxygen levels (Curtis 1946; Nelson 1951;
Satterlund 1960; Johnston 1990; Miller, 1992). It has also
been reported that cedar are often found associated with
areas of lateral flow and not in stagnate water (Johnston,
1990).

Wetland soils differ from upland soils by the presence
of a high water table. As a result of the high water table,
oxygen diffusion rates decrease and anaerobic conditions
often occur. As the oxygen decreases, several chemical and
biological changes take place. The resulting changes
usually follow a sequential pattern caused by the oxidation
and reduction of compounds within the wetland system.
Oxidation—reduction reactions involve transfer of electrons
from electron donors to electron acceptors. Oxidation is
the loss of electrons while reduction is the addition of
electrons. Reduction is usually accomplished through the
respirational oxygen consumption of micro-organisms. The
oxidation reduction cycle is reversible. Any compound that
can be reduced can be reoxidized back to its original form.

The redox state of each compound is important because

reduced forms have different properties than oxidized forms
(Patrick, 1978; Patrick & Jugsujinda, 1992).

As long as oxygen is in adequate supply, aerobic micro-
organisms dominate the system keeping the other electron
acceptors inactive. The elimination of oxygen from.the
system, by flooding or other reducing environments, brings
into action other micro-organisms that can utilize alternate
electron acceptors that are more difficult to reduce than
oxygen.(Patrick, 1978; Sikora & Keeney, 1983).

In wetland systems, two distinct oxygenated zones are
present. There is an upper oxygenated layer over a lower
anaerobic layer (Patrick, 1978). The top layer of
oxygenated water is often attributed to atmospheric mixing
and photosynthesis. This oxygen rich layer can vary from 2
- 18 ppm oxygen and is often no more than a centimeter deep
(Yoshida, 1975). This thin layer of oxygenated water plays
an important role within the wetland by providing a place
for aerobic chemical transformations and nutrient cycling to
occur (Mitch and Gosselink, 1986). Without this upper
oxygen rich layer, some compounds can become toxic in
reduced conditions. For example, the upper aerobic zone
plays an important part in the nitrogen cycle for wetlands.
In reducing wetland systems, nitrate is reduced to ammoniwm,
which in high concentrations can become toxic, but the thin

layer of oxidized water allows for nitrification to take

10

place reducing the amount of ammonium in the system (Mitch
and Gosselink, 1986).

Underneath this oxidized layer is a zone of reducing
conditions. Some studies have found that conditions become
more reducing with depth, while others have shown cases
where bogs have an oxidized layer where it comes in contact
with the groundwater table (Shotyk, 1984). In effect,
unsaturated peat profiles can have an oxidizing layer at the

top and bottom and have reducing conditions in the middle.

Peatland hydrology

Depth to the water table is an important aspect in tree
germination, growth, survival and stand composition.
Research in Finland reveals that root growth, survival and
tree height of lodgepole pine (Pinus Cbntorta) within a
peatland are related to the depth to the water table. The
lower the water table, the better the conditions for
lodgepole pine (Boggie, 1972).

In Minnesota, Lieffers (1989) found increases in basal
area growth for black spruce and tamarack were negatively
correlated with depth to the water table. He concluded that
average depth to the water table should be at least 50 cm
for optimal basal area increment.

Water table depth is important for tree growth and

regeneration for several reasons. High water tables

11

decrease aeration of the soil restricting root growth and
lower redox potentials which alters nutrient availability.
McKee (1970) found that the depth to the water table is
strongly correlated with redox potentials. According to
Burke (1967), soil aeration is the most important factor
involved in tree growth and survival in poor drainage areas.
Most trees species that grow in peatlands, cedar included,
have the majority or their roots within 20-30 cm of the
surface (VOmpersky, 1968). Satterlund (1960) reported that
northern white-cedar roots normally do not penetrate much
below the average high water table depth in the growing
season.

A convenient way of studying the effects of water table
depths on tree growth is to observe tree growth
perpendicular to a drainage ditch. Northern white-cedar has
long been reported to have better growth near ditches. In
1930, Zon and Averell recorded excellent diameter growth
increases for cedar after ditching. The increased growth
decreased rapidly as you moved away from the ditches, and
disappeared completely around 150 feet from the ditch. The
percent increase in growth next to the ditches varied from
78% on excellent sites to 126% on good sites with poor sites
increasing 113%. LeBarron and Neetzal (1942) found
increased diameter growth for cedar in a swamp up to 200

feet away from a road ditch.

12

The distance which a ditch can lower a water table is
influenced by the degree of decomposition of the peat. The
more decomposed the peat, the lower the hydraulic
conductivity and hence the shorter the distance of ditch
drawdown. Highly decomposed sapric material will have a
very short ditching distance compared to less decomposed
fibric peat. The vertical zoneation of peatlands creates
two different hydrological conditions. The upper acrotelm
allows rapid water movement while the lower catotelm
restricts water movement. Rapid removal of water by runoff
or draining can occur when the water table is above the
catotelm but is reduced dramatically when the water table
drops into the catotelm (Boelter, 1972; Crum, 1988).

Boelter (1972) reported that in a northern Minnesota
bog, the water table was lowered only at a distance of five
meters or less when the water table was in the hemic peat
(catotelm), while the upper fibric layer (acrotelm) was
effectively drained at a great distance.

A high water table can do more than slow growth.
Excessively high water tables can kill cedar. For example,
roads with poorly constructed culverts have impeded
drainage, raising water table levels which killed trees or
drastically reducing their growth on thousands of acres in
forested peatlands in the Great Lakes region (Johnston,

1977).

13

Besides poor road building, timber harvesting can cause
water tables to rise in peatlands. In general, the heavier
the harvest the higher the water table will rise. The
rising water table is due to lower rainfall interception and
decreased transpiration. Clearcuts have been reported as
rising water table levels up to 10-40 cm, while thinnings
caused a smaller rise from 1-10 cm depending on the degree
of thinning (Heihurainen, 1968; Heihurainen & Paivanen,
1970). But not all not all Clearcuts cause a similar rise
in water tables. Verry (1980) reported very little rise in
water table levels after harvesting in Minnesota.

Besides raising water table levels, clear-cutting on
peatlands has also increased the number of grasses and
sedges occupying an area (Verry, 1980). Grasses and sedges
compete directly with cedar seedlings (Nelson, 1951).
Therefore an increase in herbaceous plants would be

detrimental to northern white-cedar seedling establishment.

Peatland microtopography

Anyone who has ever been in a peatland knows that the
surface is very rarely even, but instead has an undulating
morphology. This undulating surface creates areas of
elevated hummocks and depressional pools or hollows. Such

diverse microtopography allows for tremendous variation in

14

habitat, species composition, hydrological regimes and
chemical conditions throughout peatlands (Pregitzer, 1990).
The depth to the groundwater has a strong effect on the
establishment and growth of individual tree species. Thus
microtopography also has a strong effect by altering the
relationship between groundwater levels and the trees.
Elevated hummocks provide an aerated unsaturated growing
medium in an area surrounded by saturated conditions. These
drier spots are often the only places regeneration of trees,
alder excluded, takes place within peatlands. Trees are
often found in dense clumps on the hummocks while the pools
are usually uninhabited by trees (Vompersky, 1968).
Satterlund (1960) found that hummocks in forested
peatlands in the Upper Peninsula of Michigan, are the most
favorable microtopography type for regeneration and growth
of forest trees. Flat (intermediate) areas are moderately
favorable sites while depressions (pools) are very
unfavorable sites for tree growth. Hummocks are the only
favorable sites for tree growth and regeneration when the
water table is shallow (< 46 cm below average surface
elevations). However, when the water table remained more
than 46 cm below mean surface elevation, flat areas became
favorable sites for trees along with hummocks. Depressional
areas were found not to be favorable sites for trees at any

water table depth in peatlands.

15

Microtopography can be used to increase seedling growth
and survival. Artificial hummocks (i.e. beds) can be built
within wetlands to provide habitat for seedlings. This
practice creates an effect similar to draining, but instead
of lowering the water table, seedlings are elevated on
artificial hummocks. This effectively increases the amount
of aerated soil in the seedling root zone by increasing the
distance seedlings are above the water table. Once
seedlings become established they are capable of lowering
the water table through transpiration further improving

their growth (McKee, 1970; Smith, 1986)

Nbrthern white-cedar germination

Northern white-cedar seedlings germinate in a variety of
moist mediums but become established only on a few. The
main requirements for establishing cedar seedlings are
constant unsaturated moist conditions and warm temperatures
(Johnston, 1990). In Nelson's (1951) study on reproduction
of northern white-cedar, seedling mortality was caused by
various factors (in decreasing order of significance):
desiccation, spring frost, root rot, litter and duff
smothering, poorly developed root systems and competition
from grasses. Nelson (1951) also noticed that seedlings do
not germinate on alder litter. His opinion was that the

alder litter dried out in the summer creating unfavorable

16

conditions for cedar seedlings. He also noted that northern
white-cedar seedlings are found most often on decayed logs,
but were also found on moss mats, mineral and organic
substrates.

Curtis (1946) also made several observations on cedar
seedling mortality. Seedlings are less likely to survive on
top of old stumps and high hummocks (due to desiccation)
than they are in rotted wood on the forest floor. Sphagnum
mosses, when they become deep, can smother and kill
seedlings (Curtis, 1946).

Browsing is a serious threat to cedar seedlings. Cedar
is a valuable food source for white tailed deer (Odocoileus
virginianus). NCrthern white-cedar is the only food source
in northern Michigan from which deer can get all their
nutritional needs during the winter (Verme, 1965). Cedar
swamps are in high demand as deer yards in the winter not
only for food, but also because they provide shelter from
the elements. Because of slow growth, cedar are vulnerable
to browsing for many years (maybe up to 20 years). Slow
growth and high browsing demand makes cedar hard to
regenerate. It is well documented that cedar seedlings in
the browse size class are hard to find if not completely
eliminated from.many stands (Curtis, 1946; Nelson, 1951;

Miller et al., 1994).

17

In summary, cedar regeneration after harvesting is often
unsuccessful, leading to stands of tag alder and balsam fir.
The reason for this is not understood very well, but since
hydrology is the main controlling agent in a wetland system,
cedar regeneration might be tied in with hydrology.

Research in this area is lacking with more known about the
silvics of northern white-cedar than it's relationships to

hydrology.

CHAPTER 2
OBJECTIVES AND METHODS
Sits location, history and preliminary study results

This study was conducted at Michigan State University's
Tree Improvement Center (UPTIC), near Escanaba Michigan
(Figure 1). Property lines were cut and surveyed through
the southern area of UPTIC during the winter of 1991/1992.
While surveying this area, it was discovered that a clear
cut from an adjacent property extended partially on UPTIC's
property. Looking over this area, the survey team noticed a
great difference in the density of cedar regenerating along
the property line. Large numbers of regenerating cedar were
encountered near the railroad tracks and accompanying ditch,
but numbers declined rapidly as you moved away from the
tracks.

In the following summer of 1992, a small exploratory
study was done by Joe Feldman and the UPTIC staff to
determine if there was indeed a statistical difference in
the number of regenerating cedar within the study site
(Figure 2). Six transect lines, about 30-35 meters apart,
were cut roughly parallel to the ditch along the railroad
tracks (Figure 3). On each of these transect lines, four
plots (6 m,x 6 m) were established at roughly 15 meter
intervals. At each of the 24 plot locations, the number and

type of trees and shrubs over one foot in height were

18

20

    
 

__\ ,
@1715 7-

f 6‘ .. "
/. amen C) I,» Ovid/(As . , I,
. ' .w" / /.‘ .
. ’05 r.‘ \\ //, s /
' J: ,
, .

 

,._

 
  
 
  
  

 
 

'...-—._...___..~—.-.—— . —. - — - ._ -

*-

   

1.4

 
     

(’4.

I]

 
  

n

      
  

9 a ”I,
out»?

.’I

 
 

1

   

4r
4;

      

r

  
    

 
    

  
   

‘\\ \L/ \
'1 \4'/ /.\\\‘§ § \. *. ,_
‘“‘\x” " * \AR‘S /
2 Npssss i <

“‘ ‘\\ \.

4‘ \\\\§\\ x“ \e \ \

es" \s“ N ‘\
s..\ssae\se\.s§x
’1. . :.'// {41/ /V

95/;- fl // ’ %

\ .

       
 
      
    
 
 

 

    

  

«—-%Z‘
\ 4
\ Railroad //

WHTI SCALE
2|I2' SIOO' 4224' 5260'

_ - _ PROPERTY aouuonv 0' lose-

__ . - _ SIMPLAND COUNDMY

W mace

Figure 2. Location of cedar study site within UPTIC wetland
complex (lower right) and estimated surface contour lines.

Railroad tracks and

 

 

 

 

 

 

503
accompanying ditch 46 m I
l I
| U
513 512 I 511 510
|
|
I .
' ' 521 5;).
523 522 |
Uncut area : Regrowth
l
I s ' s s
533 532 : 531 530
l
l
543 l
I
I

   

 

 

 

 

. +
./
/'
./
/'
563 //552 561 560
I I . I '

 

. = Plot number

X = Piezometer well
in RR ditch

Figure 3. Study site layout.

 

177 m

22

counted. Also at each plot location, the depth of organic
soil was measured at one spot by inserting a long rebar into
the organic soil until mineral soil was encountered.

During the winter of 1992/1993, the average elevations for
each plot were surveyed.

The exploratory study found a significant difference in
the density of regenerating cedar near the tracks with the
highest density of cedar occurring near the tracks. It was
concluded that the difference seen in the number of cedar
regenerating was due somehow to the influence of the
railroad ditch along side the tracks (Ray Miller, personal
communications). This study was conducted to follow-up on

these preliminary findings.

Objectives and hypothesis's

The main objectives of this study were to determine
factors related to cedar regeneration at this study site and
suggest methods to successfully regenerate northern white-
cedar. This was accomplished by looking at wetland
hydrology, water chemistry and microtopography and their

relationships to northern white-cedar regeneration.

23

The hypotheses were:

1) The ditch will lower the water table to a measurable

distance away from the tracks.

2) The density of northern white-cedar regeneration is

related to the depth to the water table.

3) Increased density of hummocks is associated with

areas of higher northern white-cedar regeneration.

4) Calcium, pH, specific conductivity and dissolved
oxygen levels are related to higher levels of

northern white-cedar regeneration.

Research methods

The experimental design of the original preliminary
study was used (Figure 3). Plot size and placement where
not changed for this study. Data from the preliminary study
used for this research include; stand composition of each
plot, depth of organic soil at each plot, and average
surface elevations at each plot. Additional measurements
were taken on hydrology, water chemistry and

microtopography.

Hydrology

To measure the groundwater of the area, 26 piezometer

wells were built, inserted and surveyed within the wetland

24

study site. Piezometer wells were built by cutting 2' PVC
pipe into 2' lengths, drilling them full of holes and gluing
a cap on the bottom. Piezometer wells where inserted by
auguring a hole in the organic soil with a bucket auger and
pushing the wells vertically downward. One well was
inserted near the center of each of the 24 previously
established plot locations, and 2 additional wells were
placed in the railroad drainage ditch adjacent to the site
(wells 501 & 503, Figure 3).

The groundwater levels were recorded every few weeks
throughout the summer and fall of 1993 by inserting a
modified meter stick into the piezometer wells. To minimize
error, the meter stick was lowered until it was just
touching the water surface and then read. Water table
elevations were determined by subtracting the distance to

the water table from.the top of the piezometer well.

water chemistry

Water samples were collected once during summer and
again in the fall. The unfiltered water samples were
immediately taken to a field laboratory where pH, specific
conductivity, and dissolved oxygen levels where measured
using a portable ICM-51601 water analyzer. The water samples
were than refrigerated and taken to a Michigan State

University laboratory for calcium analysis using DC-Argon

25

plasma atomic emission spectrometry. The water was
centrifuged for ten minutes to remove suspended sediments.
water samples were collected from surface pools at each
of the 24 plot locations plus two in the ditch. The only
exception was during periods of low water when the pools
were dry and water samples were collected from piezometer
wells. The very low hydraulic conductivity of organic soil
caused problems when trying to collect water from the
Piezometer wells. When water was removed from the
piezometer wells, it took several days for the well to
refill, making it impractical to purge the well and then get
clean water samples. It also made it difficult to record

groundwater levels for several days.

Microtopography

Microtopography was classified into three main types:
hummocks, pools and intermediate areas (Figure 4). For
this study, hummocks were defined as elevated, convex
shaped areas above the observed normal high water line.
The observed normal high water line is the level where high
water occurs often enough to cause a distinct difference in
the topography and vegetation. The high water line was
found by looking for significant topographic breaks which

consistently occurred between the microtopographical types.

26

Pools are depression areas below the observed high water
line. Pools are normally filled with water, but can dry
out during dry summers. Pools were easily delineated by
their concave shape and presence of black decomposing
litter within them. Intermediate areas were defined as

flat areas very near the normal high water level.

Intermediate
Area

Hummock Pool

 

\i

 

      

significant topographic break significant topographic break

Figure 4. Microtopography types.

Microtopography for each plot was determined by two line
transects 6 meters (20') long by 41 cm (16') wide in each
cut plot, one oriented north-south and the other east-west
through the center of each plot. Using the criteria above,
the microtopographic types were delineated and their lengths

recorded for each transect. Along with micotopography type,

27

number and type of trees and shrubs were recorded. The two
transects in each plot were than combined to calculate the

percent of the area covered by each microtopography type.

Data analysis

Exploratory analysis of hydrology, microtopography,
water chemistry, soil and stem density data included
examinations of Pearson's product-moment correlation
coefficients, graphs, means, minimums, maximums and standard
deviations. Significance was determined by testing Pearson
correlation coefficients at alpha=.05 (*). High
significance was tested at alpha=.01 (**)

To achieve predictability, least-squared regressions
were used. Predictions were done for density of cedar and
shrubs regeneration using various hydrological, chemical,
soil and microtopographical factors. Predictions were also
done for water table fluctuations, dissolved oxygen and
calcium levels.

Graphs are used to present untransformed data. Graphs
also include the form of regression model, R2 results and
significance. Equations are discussed in the text.
Curvilinear data were linearly transformed when needed to
find the line of best fit. Regression models normally took

one of the following forms:

Wm

Linear
Exponential function
Power function

Logarithmic function

28

Beamssiommodel

Y=b+mx
lnY=lnb+mX
lnY=lnb+m(lnX)

Y=b+m(lnX)

Equation
Y=b+mx
Y=bemx
Y=me

Y=b+mln(X)

A constant of 1 was added to linearize cedar and shrub

density (some plots had zero trees),

to allow natural log

transformations. Equations where this was done are listed

as #cedar/plot-l and #shrubs/plot-l.

CHAPTER 3
RESULTS AND DISCUSSION
Stand composition

The eastern half of the study site regenerated naturally
after clearcutting in the mid-sixties, while the uncut
western half was an older mature stand. There is a major
shift in the forest composition from north to south in the
regenerating area (Table 3, Appendix A). The northern
portion of the study site is comprised mainly of northern
white-cedar and balsam fir with black spruce in lesser
numbers. Concurrently, the southern portion is dominated by
tag alder, willows, dogwood, and balsam fir. Deer browsing
was observed to be minimal and not a significant factor
precluding cedar regeneration at this site.

Plot #530 was different from all the rest of the plots
in composition. It was composed of mostly grasses with
shrubs being the overstory. A dense layer of sticks and
small logs where found under the grass composing the top
most layer of the peat profile. The area is also the
topographical lowest spot in the study site with very wet
conditions for most of the year (Table 6). The reason for
this isolated low grassy area is unknown, but is
hypothesized to be caused by a harvesting process (i.e. old

slash pile burn area).

29

30

Table 3. Summary of stand composition of study site
(trees per plot)(for complete listing see Appendix A).

 

 

 

 

 

 

 

 

 

 

 

Plot #1 Other
Cedar' Conifers2 Hardwoods3 Shrubs4

510 (C) 33 30 1 10
511 (C) 27 35 0 0
512 (N) 5 28 1 5
513 (N) 6 23 2 1
520 (C) 62 38 10 15
521 (C) 37 42 4 2
522 (N) 8 76 0 5
523 (N) 7 39 1 4
530 (C) 2 18 15 46
531 (C) 38 30 3 10
532 (N) 5 80 0 6
533 (N) 9 88 0 6
540 (C) 11 21 4 23
541 (C) 22 20 1 9
542 (N) 15 32 1 12
543 (N) 6 23 1 12
550 (C) 2 24 2 30
551 (C) 3 43 2 18
552 (N) 10 16 0 15
553 (N) 2 9 0 47
560 (C) 2 11 6 44
561 (C) 5 10 3 36
562 (C) 0 17 3 52
563 (N) 3 12 5 24
1(C): out area, (N) = Uncut area (grouped by row from north to south).

2mostly balsam fir with some black spruce, tamarack and white spruce.
3red maple, quaking aspen, balsam popular, white birch, ash and cherry.
4mostly tag alder with some alternate leafed dogwood and willow.

 

31

 

. shammx .
R ago-.767“

 

 

 

 

Figure 5. Graph of data with line of best fit, form of
linear transformation and results of regression between
density of cedar(# per plot) and density of shrubs (# per
plot).

A highly significant negative correlation (Figure 5) was
found between the density of regenerating shrubs (tag alder,
dogwood & willows) and cedar found within a plot according
to the equation: # cedar/plot-l =50.4 e‘0-0558*(#
shrubs/plot-l). This incompatibility has been stated in
earlier studies and explained as suppression of cedar by
either litterfall or competition from alder and shrubs
(Curtis, 1946; Nelson, 1951). Another possibility is that
cedar and shrubs require slightly different habitats. Cedar

‘may not be growing where there are numerous shrubs not

32

because they are being suppressed, but because they cannot

grow there.

Soils

The north end of the study site borders railroad tracks
and an accompanying ditch. The southern end of the site
extends into a larger swamp with a small ridge to the west
and south-west. The organic soils are mostly Tawas muck
with small inclusions of Carbondale muck and Brevort mucky
loamy sand. The soil interpretation for Tawas muck
describes it as a surface layer of sapric peat with a
substratum of sapric peat which developed from woody organic
deposits within outwashes, lakes and till plains overlying
sand. The hydraulic conductivities where not measured but
are estimated to be very low (<0.01 meters/day).

The surface of the wetland is extremely flat with an
average slope about one foot over the entire study site
(Figure 6, Appendix D). The majority of the area is
overlain with approximately 1 meter of organic soil which
varies from under a third of a meter to a deep spot of
almost 2 meters (Figure 6, Appendix D). The depth of
organic soil was found to have no significant correlation
‘with the number of cedar regenerating, water levels or water

chemistry (Appendix C).

 

“\%QQ\\S\\\ Ken“ (ix RR

U’th

North

West

high water with flow lines and mineral soil surfaces.

Ground,

Figure 6.

34

water levels

The piezometric surface converges towards transect line
#530 from.the north and from the south (Figure 6). Transect
line #530 slopes east towards portage creek. This is
locally different from the regional flow of groundwater
which flows south towards the Ford river, which drains out
to Lake Michigan. An explanation for this could be that the
area of higher ground to the south and west, along with the
ditch and Portage Creek to the north and east have caused
the local piezometric surface to slope in different
directions.

No significant effect of ditching was evident from the
piezometic surface elevations (Figures 7, 8 & Appendix E).
The ditch influence on the water table profile does not
extend to the first line of Piezometer wells (3 to 7 m).
This agrees with Boelter (1972) who reported a 5 meter ditch
influence in a hemic peat. The sapric peat encountered in
this study, with its very low hydraulic conductivity, should
result in even less of a drainage influence than the 5
meters Boelter measured. It may be possible that the ditch
may actually drain a large area and influence vegetation at
some distance if the ditch is effective in rapidly draining
the acrotelm but not effective in draining the catotelm.

The draining of the acrotelm could drop water levels just

enough to permit

.mm\oe\m masons» mm\e\s nod oemtoem mane; do Am-zv manhood wanes gone: .s museum

Sodom Sumo:

as :26 mm 60: mocmemé

 

 

 

 

com one 09 om o

momtsm o.m_.w

5 SEE I l

3 SEN: .I l . 3
mmxnwxm iI| 1 Boom m...
mmxoio. I I m.
U
- 0.3m M

r _ . 03m

 

 

 

00m 0mm ovm 0mm CNN O ..m

36

.mm\OH\m rescue» mm\m\s goo Hem-afim made; do Im-z. maeooua wanes none:

.m whomflm

 

 

 

 

 

 

 

Sodom Sumo:
REV :86 mm E0: 8850
com one 00? on .o
momtsw _ . q x 0.9m
mm\©\~ I: II.

mm\©m\~ II II .

mmxmmxm ill 1 mmem
T I H dull); I.
_ p _ vaFm
wwm rmm rvm rmm er rpm

(w) uoueAala

37

higher establishment and growth of cedar, but this would go
unnoticed unless water levels were recorded at least daily.

There is a significant relationship between the
magnitude of the water table fluctuation during the growing
season and distance from the railroad ditch according to the
equation: cm.fluctuation = 22*e0.0028*(m from ditch) (Figure
9)- The fluctuation of the water table was calculated by
subtracting the highest water table elevation by the lowest.
The water table was found to fluctuate least near the ditch
and increase at an increasing distance from the ditch
(Appendix D). The fluctuation of the water table showed a
highly significant relationship with cedar regeneration
according to the equation: # cedar/plot-l =210.1 x 106 *(cm
fluctuation)“‘4-99 (Figure 10).

Satterlund (1960) reported that high water table levels
in the growing season limit root growth for northern white-
cedar. The high water table levels in the growing season
also appear to play a role in cedar regeneration. The July
6th water table elevation (highest level measured in growing
season) was significantly and linearly related with the
number of cedar regenerating according to the equation: #
cedar/plot =30,009.4-140(water table elevation in m) (Figure

11). There were no significant relationships between water

38

 

hY-w
R sip-.899“

8

”HM“

 

 

 

 

Figure 9. Graph of data with line of best fit, form of
linear transformation and results of regression between the
fluctuation of the water table (cm) and the distance from
the railroad ditch (m).

 

sooth”)

3 8 £5 8 8 ES 8

‘0). . d

o
1’ a -1

v

20 26 so 5 40 45

 

 

O

 

“WWW“

Figure 10. Graph of data with line of best fit, form of
linear transformation and results of regression between the
density of cedar regeneration (per plot) and water table
fluctuation (cm).

39

 

 

10 I . u
0
° 1 1 1 9.1 ’

0 c
21400 214.06 21410 214.16 214.20 214.26
.0] 61h “hf Uh mm 0n)

 

 

 

Figure 11. Graph of data with line of best fit, form.of
linear transformation and results of regression of July 6th
water table elevations (m) vs. density of cedar regenerating

 

 

(per plot).
I) I I I
70- “-6va ..
Riga-.549“
li- ° -
in»
3,0.
3...
0
2°)-
10r- °
0 o : o 1

 

 

 

O 6 10 15 20
Momma-dumb»

Figure 12. Graph of data with line of best fit, form of
linear transformation and results of regression between
unsaturated soil depth (cm) for the July 6th water table and
density of cedar regenerating (per plot).

40

 

oswubtufl
6

8 8

 

 

 

 

O

O 6 10 16 20
Mahmuumm

Figure 13. Graph of data with line of best fit, form of

linear transformation and results of regression between

unsaturated soil depth on July 6th and density of shrubs
regenerating (per plot).

table elevations at other times of the year and the density
of regenerating cedar (Appendix C).

The depth of unsaturated soil above the water table is
determined by the water table level and average surface
elevation (Table 4). The depth of unsaturated soil was
calculated by subtracting the water table elevations from
average surface elevations (Appendix D). The unsaturated
soil depth was found to be a better measurement for
predicting cedar regeneration than water table elevations
and fluctuations, probably because it takes into account

surface topography as well as the level of the water. The

41

 

 

 

 

 

 

 

 

Table 4. Depth of unsaturated soil (cm).

Well 6/27 7/2 7/6 7/26 8/25 9/10

# 1993 1993 1993 1993 1993 1993 Avg.
510 19.81 20.42 16.15 21.64 33.53 39.32 25.15
511 17.07 17.37 12.80 18.59 29.57 34.75 21.69
512 12.34 13.26 8.69 14:78 25.15 30.02 17.37
513 10.67 13.41. 8.53 15.54 24.69 29.57 17.07
520 19.05 20.57 16.61 22.40 36.73 42.52 26.31
521 18.29 20.42 16.76 21.64 35.05 41.15 25.55
522 10.67 13.11. 8.53 14.94 27.43 33.53 18.03
523 12.19 13.72 9.75 16.46 28.65 33.83 19.10
530 4.57 6.40 3.05 8.84 21.34 28.96 12.19
531 11.43 12.95 10.21 15.09 27.89 36.42 19.00
532 12.19 14.02 10.67 17.37 29.26 36.58 20.02
533 12.04 15.09 11.13 17.83 28.80 35.81 20.12
540 5.64 8.08 5.03 11.73 26.06 35.81 15.39
541 10.06 11.58 8.53 15.24 28.04 36.58 18.34
542 9.91 11.43 8.38 15.09 26.67 34.29 17.63
543 16.76 15.24 11.58 18.29 30.18 37.80 21.64
550 12.95 15.39 11.73 18.75 35.81 48.01 23.77
551 11.58 14.02 10.67 17.37 32.92 41.76 21.39
552 10.67 14.63 10.67 17.68 30.48 40.84 20.83
553 9.30 11.89 8.69 14.78 28.19 37.95 18.47
560 5.94 9.30 6.25 13.26 32.46 48.01 19.20
561 10.97 14.33 10.97 17.98 34.44 46.02 22.45
562 7.32 10.67 7.01 13.72 29.26 41.15 18.19
563 8.23 11.58 8.53 15.24 29.57 41.15 19.05

 

 

 

 

 

 

 

 

 

42

unsaturated soil depths for July 6th (highest level measured
in growing season) was highly significant and linearly
related to the density of cedar and shrubs. The equations
are: # cedar/plot =-16.146+3.417(cm of unsaturated soil)
(Figure 12), and # shrubs/plot =50.39-2.65(cm of unsaturated
soil) (Figure 13). As water levels dropped, the
relationships became less significant and non-significant
(Appendix C). It appears that the high water table during
the growing season is the most important water table
relationship for determining cedar.

Using the regression equations, the depth of unsaturated
soil required for cedar to regenerate on this site was
calculated. Apparently cedar need around 12 cm of
unsaturated soil (measured from the average plot elevation)
to regenerate. If unsaturated soil depths become less than

12 cm, than it becomes to wet for cedar.

Microtopography

Only small hummocks, averaged about .5 to 3 meters in
length, where encountered in the study site, no large
hummocks where found. Since small hummocks are favorable
for tree growth, all hummocks on this site where assumed
suitable for regenerating trees. The heights of hummocks

were not measured but are estimated as 15-30 cm. The pools

43

were also small in size averaging around 1 meter or less in

length.

Microtopography transect data (Appendix B) for the

entire cut area were analyzed for occurrence of different

tree species on microtopographical features (Table 5).
majority of trees and shrubs,

found growing only on hummocks.

The

especially conifers, were

This was true of trees

growing in the wetter southern area and in the drier

northern area.

These results agree with other reports

citing that the majority of trees occur on hummocks (Curtis,

1946;

While conifers are confined to hummocks,

Satterlund, 1960;

Vompersky,

1968; Pregitzer,

alder,

1990).

shrubs and

hardwoods are found growing in pools and intermediate areas

as well as hummocks.

Table 5.

The percent of trees and shrubs growing on
different microtopography types.

 

 

 

 

 

 

 

 

Tree species Number of Hummocks Intermed. Pools

Trees % areas % %
Cedar 56 95 2 3
Balsam Fir 87 91 3 6
Alder 54 69 11 20
Shrubs1 51 73 17 10
B. Spruce 7 100 0 0
Hardwoods2 9 89 0 11

 

 

 

 

 

1alternate leafed dogwood and willow.
2red maple, quaking aspen, balsam popular, white birch, ash

and cherry.

 

44

 

 

 

 

Table 6. Microtopography percentages in regenerating area.
Plot % Hummocks % Intermediate Areas % Pools

Site N-S I s-w Avg. N-S l E-W Avg . N-S I E-W ML

Trans ects Transects Transects

510 87.5 73.5 80.5 0 8.5 4.25 12.5 18 15.25
511 86.5 76.5 81.5 0 15 7.5 11.5 8.5 10
520 92.5 83 87.75 0 4.5 2.25 7.5 12.5 10
521 78.5 70 74.25 8.5 9.5 9 13 20.5 16.75
530 14 40.5 27.25 62.5 43 52.75 23.5 16.5 20
531 80.5 77 78.75 0 17.5 8.75 19.5 5.5 12.5
540 45.5 49 47.25 12.5 27.5 20 42 23.5 32.75
541 71 69 70 9 7.5 8.25 20 23.5 21.75
550 55 39 47 0 20 10 45 41 43
551 42.5 60 51.25 0 6.5 3.25 57.5 33.5 45.5
560 30 31.5 30.75 45.5 23.5 34.5 24.5 45 34.75
561 58 54.5 56.25 11.5 13 12.25 30.5 32.5 31.5
562 41 36 38.5 13 4.5 8.75 46 59.5 52.75

 

 

 

 

 

 

 

 

 

 

 

 

The average plot microtopograpy (Table 6) was found to

be the best indicator of cedar regeneration success in this

study. The percent of the plot area consisting of hummocks

exhibits a very significant relationship with the number of

cedar and shrubs regenerating in that area according to the

equations: # cedar/plot =0.109+93.967(%hummocks“4) (Figure

14) and shrubs-1 =-0.449-39.44*ln(%hummocks)

The greater the percentage of hummocks,

the regenerating cedar.

(Figure 15).

the more numerous

Pools and intermediate areas have

limited cedar regeneration but increased shrub and alder

numbers.
stand composition.

percentages while cedar are found at high hummock

The percent of the plot that is hummocks predicts

Shrubs are most numerous at low hummock

45

percentages. For this site, it appears that there should be
at least 70 percent of the area covered by hummocks for good
cedar regeneration.

Combining the 12 cm of unsaturated soil with the average
height of hummocks (15-30 am), it appears that cedar need an
average of around 27-42 cm of unsaturated soil (as measured
from the top of a hummock) to successfully regenerate.

It appears that the slight difference in habits between
shrubs and cedar are due to their different tolerances for
water levels. The greatest density of shrubs are found in
the wetter areas (low unsaturated soil depths and low
percentage of hummocks) while cedar are found in relatively
drier areas (high unsaturated soil depths and high

percentage of hummocks).

46

 

Y-lH-IIXM
R syn-.856“

 

 

 

 

Figure 14. Graph of data with line of best fit, form of
linear transformation and results of regression between
percent hummocks of plots and density of cedar regenerating
(per plot).

 

 

 

 

 

Figure 15. Graph of data with line of best fit, form of
linear transformation and results of regression between
percent hummocks of plots and density of shrubs regenerating
(per plot).

47

water chemistry

All water samples on June 26th were collected out of
pools. Due to the late summer dry conditions, some of the
September 10th samples had to be collected from piezometer
wells. A water sample was not collected or analyzed on
September 10th for plot #560, because the water table had
dropped below the bottom of the piezometer well.
water chemistry has been cited as a major determining factor
in northern white cedar establishment (Curtis, 1946; Nelson,
1951; Pregitzer, 1990; Miller et. al, 1990). The four most
important chemical components cited are: pH, specific
conductivity, calcium and dissolved oxygen levels. Water pH
levels ranged from 6.6 to 7.16 on June 26th (Table 7), and
increased to 7.3 to 7.73 on September 10th (Table 8).
Specific conductivity levels on June 26th ranged from 171 uS
cm-l to 342 uS cm-l (Table 7), and increased by the end of
the summer to 232 uS cm-l to 487 uS cm—l (Table 8).
Regression analysis determined that cedar regeneration is
not significantly related to pH or specific conductivity
levels (Appendix C).

This can most likely be explained by comparing results
with Glaser's et a1. (1981, 1990) data (Table 9). Specific
conductivity and pH levels are likely not showing major
impacts on cedar because the entire study area would be

classified as an extremely rich fen. Since, northern white-

48

Table 7. Specific conductivity, pH, dissolved oxygen and
calcium levels for 6/26/93.

pH Spec fic Dissolved Calc um
Conductivity Oxygen
cm-l l
305 3. 46.
42 1

342 . 8.
189 8
190 42
188 49

21 41
234 . 42.
233 43.
2 48

20 . 7

239 42.

314 . 50.
1

213
234
241
277

221
24
25
250

171
207
2

252

245.7
47 2
342
171

 

49

Table 8. Specific conductivity, pH, dissolved oxygen and
calcium levels for 9/10/93.

pH Specif c D ssolved Calc um
Conductivity Oxygen
uS cm-l l
40 6 .
472 67

\14

276 47.
320 49
376 3.
320 1

\IQQQ

297 45

57 7
415 60.
332 . 0.

\IQQQ

48 58

4 50.
346 . 44.
456

\IQQQ

232 35.
273 . 38
288 . 41.
324 . 46

7.
7.
7.
7

487 55
2 4
330 27
1 . 41

\IQQQ

A N
31 37.

 

50

Table 9. Average calcium, specific conductivity and pH
levels of the study site compared to Glaser et al. (1981,
1990) levels.

Peatland type Specific Calcium
1 l
r l > 2 >20
ch Fen . . 23-82 10-20
r F . 3-10
12-27 <

 

f r st . 295 44.4

cedar is an indicator species of extremely rich fens and
rarely found in the other peatland types, the entire study
site is excellent habitat for cedar. The variations seen in
water pH and specific conductivity are small compared with
the changes needed to alter peatland types (cedar habitat).
If pH or specific conductivity levels had dropped below
acceptable levels of cedar habitat, cedar may have then been
adversely effected.

Calcium levels ranged from 23.2 mg/l to 61.3 mg/l (Table
7) and 27.7 mg/l to 67.3 mg/l (Table 8). Dissolved oxygen
levels for June 26th, ranged from 1.8 ppm to 6.9 ppm (Table
7), and increased to 4.9 ppm to 9.9 ppm on September 10th
levels (Table 8). The highest calcium and oxygen levels
were found in the ditch and the lowest were found farthest
from the ditch. Calcium and dissolved oxygen levels for
June 26th are significant related to the distance from the

ditch. The equations are: oxygen(ppm) =9.43-1.359*ln(m from

51

ditch) (Figure 16) and calcium(mg/l) =42.434-0.061*(m from
ditch) (Figure 17).

June 26th dissolved oxygen levels show a highly
significant relationship with cedar density: # cedar/plot-l
=0.833*(ppm oxygen)"2-01 (Figure 18). June 26th calcium
levels also showed a highly significant relationship with
cedar density: #cedar/plot-l =0.0156 * exp(-1'785"'m9/l Ca)
(Figure 19). Neither oxygen or calcium levels, for
September 10th, showed any significant relationship with
cedar density.

Dissolved oxygen and calcium levels were more
significantly related with distance from the ditch than
cedar density. It is not known therefore if oxygen and
calcium levels directly affected cedar regenerating, or if
the cedar were resulted from other factors related to the

ditch.

52

 

 

masses-Mammary»

 

 

 

O 60 100 160 zoo

Figure 16. Graph of data with line of best fit, form of
linear transformation and results of regression between June
26th dissolved oxygen levels (Ppm) and distance from the
railroad ditch (m).

 

.1
«I1
.1

6

I

 

mmmmm

 

 

 

25' )hhmx .
Rapfifl” °
2°. .3 .30 .4 200
numuwmnamuo

Figure 17. Graph of data with line of best fit, form of
linear transformation and results of regression between June
26th calcium levels (mg/l) and distance from the ditch (m).

 

53

 

w T I I I 7
7° hYSth-IIKIIIX) _‘
Raga-.475“

u>- ’ -
a so . , .
I ,0 _ .
i J

m '- .1
. O

20 .. ° .

so - ° .

o 1 c ° 1. . 1 1 1

 

 

 

1 2 6 4 6 6 7
mmmmmm

Figure 18. Graph of data with line of best fit, form of
linear transformation and results of regression between June
26th dissolved oxygen levels (Ppm) and density of cedar
regenerating (per plot).

 

    

w r I I I
70»- hY-iIb-HIX .,
nun-mu

so» ' 4
3w» -(
3“,.
g”)-
.

m:-

10*-

0 ‘ 1 1.1.. 1

 

 

 

20 26 so u 40 46
manhunt-sum

Figure 19. Graph of data with line of best fit, form of
linear transformation and results of regression between June
26th calcium levels (mg/l) and density of cedar regenerating

(per plot).

 

CHAPTER 4
SUMMARY AND RECOMMENDATIONS

Summary

The main objectives of this study were to determine
factors related to successful cedar regeneration at this
study site and suggest methods to successfully regenerate
northern white-cedar. This was accomplished by looking at
wetland hydrology, water chemistry and microtopography and
their relationships to northern white-cedar regeneration.
The hypotheses were:

1) The ditch will lower the water table to a measurable

distance away from the tracks.

2) The density of northern white-cedar regeneration is

related to the depth to the water table.

3) Increased density of hummocks is associated with

areas of higher northern white-cedar regeneration.

4) Calcium, pH, specific conductivity and dissolved
oxygen levels are related to higher levels of

northern white-cedar regeneration.

The railroad ditch was not effective in lowering the

water table at distances needed to explain an increase in

cedar regeneration. Instead, it appears that the density of

54

55

hummocks and hydrology of the site explained most of the
variance found in the density of cedar regeneration.

The water table was found to fluctuate least near the
ditch and increase at an increasing distance from the ditch.
The fluctuation of the water table showed a highly
significant relationship with cedar regeneration according
to the equation: # cedar/plot-l =210.1 x 106 *(cm
f1uctuation)“'4°99 (R2=.540**). The high water table level
in the growing season was measured on July 6th. The high
water table level in the growing season was significantly
and linearly related with the number of cedar regenerating
according to the equation: # cedar/plot =30,009.4-140(water
table elevation in m)(R2=.324*).

The unsaturated soil depth was found to be a better
measurement for predicting cedar regeneration than water
table elevations and fluctuations, probably because it takes
into account surface topography as well as the level of the
water. Unsaturated soil depths for July 6th (highest level
measured in growing season) was highly significant and
linearly related to the density of cedar and shrubs. The
equations are: # cedar/plot =-16.146+3.417(cm of unsaturated
soil) (R2=.549**), and # shrubs/plot =50.39-2.65(R2=.457**).
As water levels dropped, the relationships became less

significant and non-significant. It appears that the high

56

water table during the growing season is the most important
water table relationship for detenmining cedar regeneration.

Using regression equations, the depth of unsaturated
soil required for cedar to regenerate on this site was
calculated. Apparently cedar require approximately 12 cm of
unsaturated soil during high water in the growing season
(measured from.the average plot elevation) to regenerate at
this site.

The average plot microtopograpy was found to be the best
indicator of cedar regeneration success in this study. The
percent of the plot area consisting of hummocks exhibits a
very significant relationship with the number of cedar and
shrubs regenerating in that area according to the equations:
# cedar/plot =0.109+93.967(%hummocks“4) (R2=.856**) and
shrubs-1 =-0.449-39.44*ln(%hummocks) (R2=.744**). The
greater the percentage of hummocks, the more numerous the
regenerating cedar. For the study site, 95% of cedar were
found on hummocks. Pools and intermediate areas have
limited cedar regeneration but increased shrub and alder
numbers. The greatest density of shrubs are found in the
wetter areas (low unsaturated soil depths and low percentage
of hummocks) while cedar are found in relatively drier areas
(high unsaturated soil depths and high percentage of

hummocks). For this site, it appears that there should be

57

at least 70 percent of the area covered by hummocks for good
cedar regeneration.

Combining the 12 cm of unsaturated soil with the average
height of hummocks (15-30 cm), it appears that cedar require
an average of approximately 27-42 cm.thickness of
unsaturated soil during high water in the growing season (as
measured from.the top of a hummock) to successfully
regenerate. If unsaturated soil depths become less than 27-
42 cm, than it becomes to wet for cedar. The hummocks are
important at this site because they are the only places
where 27-42 cm of unsaturated soil (as measured at high
water for the growing season) can be found.

Throughout the wide spectrum of peatland ecotypes, water
chemistry is very important for determining northern white-
cedar distribution. But the role of water chemistry in
cedar regeneration at this site is inconclusive. Specific
conductivity and pH levels where not significantly related
with the density of cedar. However, June 26th calcium and
dissolved oxygen levels were significantly related to
density of cedar regeneration while September 10th levels
were not. Both calcium and dissolved oxygen levels were
better correlated with distance from the ditch than with
cedar regeneration. I conclude that while water chemistry

is important, hydrology and microtopography are the dominant

 

58

factors controlling differences in cedar regeneration at
this site.

This study reveals that it may be possible to predict
potential cedar regeneration in extremely rich fen wetlands
by knowing how much of an area will be suitable cedar
habitat after harvesting. The microtopography of an area
can give an estimate of suitable cedar habitat. Small
hummocks are suitable cedar habitat if there is at least 27-
42 cm.of unsaturated soil during high water during the
growing season. If there is less than 27-42 cm than cedar
may not be able to regenerate on the hummocks. Large
hummocks can usually be delineated from small hummocks by
the absence of moss growing on the upper regions of large
hummocks, and are not generally suitable for cedar
regeneration. Large hummocks will dry out in the mid-summer
creating unfavorable conditions for cedar. Cedar might be
able to regenerate on the edges of large hummocks, but this
needs to researched further. Pools are not suitable for
cedar under any conditions. Intermediate areas are not
suitable for cedar regeneration unless the high water table
during the growing season is greater than 46 cm (Satterlund,
1960).

Groundwater tables may be measured by using piezometer
wells. Using the high water table during the growing

season, which seems to be the most influential for cedar

59

establishment, the thickness of unsaturated soil above the
water table can be calculated. If significant water table
changes after harvesting are predicted, than the amount of
potential cedar habitat after harvesting can also be
calculated. All small hummocks with at least 27-42 cm of
unsaturated soil, after adding the water table changes due
to harvesting, will be potential cedar habitat. Any
intermediate areas with at least 46 cm of unsaturated soil,
after harvesting, will also be potential cedar habitat. All
other microtopography types will not be beneficial to cedar
regeneration. This study reveals that cedar need at least
70% of the area composed of suitable cedar habitat to
successfully regenerate on this site. If there is less than
70%, than the site will most likely become dominated by
alder, shrubs and other trees species better adapted for
wetter sites.

This study reports important relationships and increases
our understanding of the hydrological and microtopographical
effects on northern white—cedar regeneration. The values
obtained in this study are notable, however, some of the

values may change with additional research.

Future research recommendations
Research is needed to determine the hydroperiods (the

upper and lower limits of water levels that a species can

60

live in) for northern white-cedar and other peatland tree
and shrubs species. Knowing the hydroperiods of different
species is important when dealing with activities which can
alter water table levels in peatlands (e.g., draining,
harvesting or road building). If water tables are altered,
different species can take advantage depending on where the
water table levels are and the microtopography of the site.

Research needs to be conducted to further define the
relationship between cedar regeneration to the water
chemistry. Research also needs to consider the effect of
deer browsing on cedar seedlings. There seem to be many
reports on the negative effects of deer browsing pressure,
but few research studies that actually address this area.
Methods must be devised to keep deer out of regenerating
areas until seedlings are above the browse height.

More research needs to be done on harvesting effects on
peatlands. The effects of harvesting should be quantified
for different sites and treatments. The hydrology,
microtopography, light, temperature and browsing pressure
can all be altered by harvesting. Methods should be devised
to maintain the microtopography when harvesting in
peatlands. Hummocks can be easily destroyed by harvesting
methods. Harvesting effects need to be better understood if
we are to successfully harvest and regenerate cedar in

peatlands.

APPENDICES

 

APPENDIX A. Number of trees and shrubs per plot.

Table A.1. Number of trees and shrubs in plots 510, 511,

512 and 513.
Species Plot number
Min—W

Northern white cedar 33 27 5 6 71
Balsam fir 27 26 28 21 102
Black spruce 3 9 2 14
White birch 1 1
Balsam popular 0
White pine 0
Alt. leafed dogwood 8 2 10
Tag alder 1 3 1 5
Quaking aspen 0
Ash 0
Willow species 1 1
Red maple 1 2 3
Cherry 0
Tamarack 0
White spruce 0
Totals 74 62 39 32 207

61

62

Table A.2. Number of trees and shrubs in plots 520, 521,
522 and 523.

Species

Northern white cedar
Balsam fir

Black spruce

White birch
Balsam.popular
White pine

Alt. leafed dogwood
Tag alder

Quaking aspen

Ash

Willow species

Red maple

Cherry

Tamarack

White spruce

Totals

Plot number

W
62 47 8 7 124
31 37 75 39 182
7 2 1 10
0
O
0
0
3 2 5 4 14
3 l 4
1 1
12 12
O
7 3 10
2 2
1 1
125 95 89 51 360

63

Table A.3. Number of trees and shrubs in plots 530, 531,
532 and 533.
Species Plot number
W31
Northern white cedar 2 38 5 9 54
Balsam fir 18 23 80 88 209
Black spruce 7 7
White birch 12 14
Balsam popular 1 1
White pine 0
Alt. leafed dogwood 3 3 6 5 17
Tag alder 40 5 45
Quaking aspen 1 1
Ash 2 2
Willow species 3 2 1 6
Red maple 0
Cherry 0
Tamarack 0
White spruce 0
Totals 81 81 91 103 356

 

64

Table A.4. Number of trees and shrubs in plots 540, 541,
542 and 543.
Species Plot number
WM].
Northern white cedar 11 22 15 6 54
Balsam fir 19 18 32 23 92
Black spruce 1 2 3
White birch 1 1 1 3
Balsam popular 3 3
White pine 1 1
Alt. leafed dogwood 21 6 4 4 35
Tag alder 1 6 8 15
Quaking aspen 0
Ash 1 1
Willow species 2 2 4
Red maple 0
Cherry 0
Tamarack 0
White spruce 0
Totals 59 52 58 42 211

65

Table A.5. Number of trees and shrubs in plots 550, 551,
552 and 553.
Species Plot number
W
Northern white cedar 2 3 10 2 17
Balsam fir 23 42 16 9 90
Black spruce 1 1
White birch 1 2 3
Balsam popular 1 1
White pine 0
Alt. leafed dogwood 11 38 49
Tag alder 24 12 4 9 49
Quaking aspen 0
Ash 0
Willow species 6 6 12
Red maple 0
Cherry 0
Tamarack 1 1
White spruce 0
Totals 58 66 41 58 223

 

66

Table A.6. Number of trees and shrubs in plots 560, 561,
562 and 563.

Species

Northern white cedar
Balsam.fir

Black spruce

White birch
Balsam.popular
White pine

Alt. leafed dogwood
Tag alder

Quaking aspen

Ash

Willow species

Red maple

Cherry

Tamarack

White spruce

Totals

Plot number

WW
2 5 3 10
11 10 17 12 50
0
4 3 2 5 14
0
0
0
44 36 52 24 156

63 54 72 44 233

APPENDIX B. Data from.microtopography transects.

Table 8.1 Data from microtopography transects.
(Trans=trancest number), (Seg=segment number), (Topo
type=topography type{2=hummock, 3=intermediate area,

4=pool}), (NWC=northern white-cedar), (ALthag alder),
(BF=balsam fir), (SH=shrubs;dogwood,willows), (BS=black
spruce), (HW=hardwoods;red maple,aspen, balsam popular)

Plot Trans Seg Topo Length NWC ALD BF SH BS
ft 4 I: i i i

510
510
510
510
510
510
510
510
510
510
510
510
510
510
510
510
510
510
511
511
511
511
511
511
511
511
511
511
511
511
511
511
511
511
Table

qmmkwNHooxlmmanHr-xoooqmmwat—I

PMNNNNNHHHHHHHHHHNNNNNNNNHHHHHHHHHH

r7

pmmunwwpwewwwewwwomwwwnwewwwwnwwow a
wawoquHprHowwpwwwwwomowwwNHwoow
wammmomqHM4mmOquwmowmpmmOOHwommH
OOOOOOOHHOHOOOONOOHHNOOOONHwNOONOH
OHOOOOOOOONOOOOHOONHOOOHOHHOOOHOOO
oooooooooooooooooooooooooooooooooo
oooooHooooooooooooooowoooooooooooo
OHOOOOOOOOOOOOOOOOHOOOOOOOOOOOOOOO

ammowNHHmm

1 Co

W

 

OOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOOO

68

000000010032100000000000000000000000000001000000

000000000000000000000000000000000000000000000000

000000000000000000000000000000000000000000000000

000000000000000000000000000000000000000000000000
100102103025301003000110000000200011100204300010

00000011..0030100022010100020010100001000000000100

805061406848946701889104107825055608185735497804

13020122103202402211033021..0020100010200003320311

232242222222422422423223222424342222242232224224

01

0123456789 t
789123456789111234567891234567891111111111123456m
C

1..
2221111..11111112222222221111111111111111111222222Rm

511
511
511
520
520
520
520
520
520
520
520
520
520
520
520
520
520
520
520
520
520
520
520
521
521
521
521
521
521
521
521
521
521
521
521
521
521
521
521
521
521
521
521
521
521
521
521
521
Table

69

000000000000000000000000000000100000000000000000

000000000000000000000000000000010000000010100000

000000011002000201000000000000000000000000000000

000000000100000100000000000000000000000000000000
000000000000000000000000000000210001030402202000

000000000000000000000000000000010200010300200000

049504134765635655723355418345947188634fi04011570

210022113201210100122131111110230100010331412001

232343423332434343423233242324224242424224242323

2 .0112 t
1123456789111123456m
C

01

0 23 01..
789111234567891 1112345678911

.1

222221111111111111222222222222111111111111222222B

Table

111110000000000000000000000000111111111111111111
222223333333333333333333333333333333333333333333
555555555555555555555555555555555555555555555555

7O

000000000000000000000000000000000000000000000000

000000000000000000000000000000200000000000000000

000000012250000000000002100103010000000000000004

000000000010000000000003000000000000000000000101

000101030060101000000000000000100000000000000000

003000000010001000000000000000101000000000000000

358659335289408913332258698910302319090510862184

1011.13112274011111322401000031611021111124302111

232232423424242424323242423242232422424342242242

012 01012 0 t
789111123456123456789111234567891111234567891123 n

.1 Co

222222111111222222222221111111111112222222222111B

531
531
531
531
531
531
540
540
540
540
540
540
540
540
540
540
540
540
540
540
540
540
540
541
541
541
541
541
541
541
541
541
541
541
541
541
541
541
541
541
541
541
541
541
541
550
550
550
Table

71

000000000000000000000000000000000000000000000000

000000000000000000000000000000000000000000000000

41.000000001900000000000000020000000000000000000000

0406010000000000000000300000000000000000l1015211
000000010100000000000000000000000000000001..000000

000000000000000000000000000000000000000000000000

058413439077438018200072828451210001793081182742

210011.111400310121114272010111212134211411204016

424242424242424242423242424224242442423242432233

0123 012 0 t
456789111112345678911112345678911234567812345678m

C

1

1111111111222222222222111.11111112222222211111111Ru.

550
Table

000000
555555
555555

550
550

0000000
5555555
5555555

550
550

0000111
5555555
5555555

551
551

111111111111100000000
555555555555566666666
555555555555555555555

2
7

000000000000000000000000000000000000000000000000

000000000000000000000000000000000000000000000000

000000000000000000000000000000000521500000000000

700000000006015000000000000000001000000000000000
000000000000100000000011000000000000000000000000

000000000000000000001001000000000000000000000000

709654452320938411287933278589306405582659682996

01023321212211102152101113021..1311113301014315100

244243424324342324242422423232423234242224424232

0 01 0 0 t
91.1234567891122345678911345678911234567891123456n

CO

1
112222222221111111111111222222221111111111222222Rm

560
560
560
560
560
560
560
560
560
560
560
561
561
561
561
561
561
561
561
561
561
561
561
561
561
561
561
561
561
561
561
561
562
562
562
562
562
562
562
562
562
562
562
562
562
562
562
562
Table

562
562
562

2

‘OCDQ

IbNIb

NNO

O\\OU'|

OOO

APPENDIX C. Regression results.

Table C.1. Regression results and equations for various

factors (*

Equation

=S% Significance, ** =1% Significance)

R,sauare

Peat (m)=241.034-1.121*(7/6/93 water elevation(m)) R2=.122

Peat (m)=213.839-0.061*(9/10/93 water elevation(m))R2=.016

#cedar(per
#cedar(per
#cedar(per
#cedar(per
#cedar(per
#cedar(per
#cedar(per
#cedar(per
#cedar(per
#cedar(per
#cedar(per
#cedar(per
#cedar(per
#cedar(per
#cedar(per
#cedar(per

#cedar(per

plot)=-6.996+28.671*(m of peat) R2=.14o
plot)=29,499-138*(6/26 water table(m)) R2=.373*
plot)=30,689-143*(7/2 water table(m)) 32:.341*
plot)=30,813-144*(7/26 water table(m)) R2=.291
plot)=30,084-141*(8/25 water table(m)) R2=.203

plot)=8,915-41.6*(9/10 water table(m)) R2=.01s
plot)=1.27*e°18*(6/26 unsat. depth(cm))RZ= 498**

plot)=.877*e-177*(7/2 unsat. depth(cm)) R2=.403*
plot)=.479*e-135*(7/25 unsat. depth(cm))R2=.329*
plot)=1.55*e:051*(8/25 unsat. depth(cm)) R2=.042
plot)=111.8*e’-059*(9/10 unsat. depth(cm))R2=.o52

plot)=—28.9+7.14*(6/26 pH levels) R2=.001
plot)=-177.5+26.2*(9/10 pH levels) R2=.027
plot)=-14.6+0.15*(6/26 s. cond (uS)) R2=.001
plot)=35.9-0.051*(9/10 s. cond (uS)) R2=.023

plot)=6.56x10‘4+10.62*ln(9/10 oxygen(ppm))R2=.297
plot)=-10.5+0.65*(9/10 calcium (ppm)) R2=.064

74

APPENDIX D. Average surface elevations, depths of organic
soil (peat), water table elevations and maximum.water table

fluctuations.

75

76

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

m.mm Nvaéam HNQEN >3.va omaéam bwméam maméam omméam mmméam mmmé mom
Hem mmaéam mom.mam Hmoéam :3".va vvméam boméam Heméam vaméam mmbé mom
Emm vmaéam www.mam eooéam mwaéam mmméam moméam mmméam mvméam mmmé Gm
Ewe Noaéam eaméam obméam mmaéam mmméam Homéam mmméam vmméam omm.o 8m
m.mm Hmoéam waméam vmméam mmaéam mmazvam bmaéam mmaéam mbméam Hawtfi mmm
m.om bmoéam www.mam Hamimam maaéam mmaéam mvaéam mmaéam mmméam acorn «mm
drum Hmoéam www.mam mhméam andeam maaéam mmaéam mmaéam moméam mmm.o Hmm
m.mm wmoéam mmm.mam mvm.mHm SHEEN wmaéam aeazvam 3%.va moméam mmmé omm
mom mmaéam vmméam 9;.va mmaéam mmméam mmaéwm veaéam Heméam mvoé mom
m.m~ mmaéam obméam ovoéam mmaéam mmméam mafivam 93.va maméam Hon; «3
o.m~ hmoéam mflméam oooéam mmaéam mmaéam mwaéam omaéam omméam Hmvé 3m
m.om mmoéam mmm.ma~ Hagan «madam Homéam «SHJHN mmaéam mmméam Hmmé o3
hem meméam www.mam www.mam mmmfiam mmo.v.nm mmméam vmoéam evaéam ooaé mmm
m.mm www.mam www.mam mmm.mam vmméam Hmoéam mmm.m.fim mooéam mmaéam mmmé mmm
«.mm www.mam www.mam 5.3.03 mmm.mam vaoéam rampam Nooéam mHHJHN coo...” Hmm
m.mm mamdam omimam www.mam HmmAMHN mooéfim wbméam emmeHm oeoéam mvoé omm
szm boosvam omm.mam maméam «madam Hoaéam Hwoéam whoéam mmaéflm mac...” mmm
o.mm bmméam meméam mom.ma~ mmoéam mmoéam ovoéam 02....va 294.3 v.36 «mm
vzvm Hmm.m._nm mmm.mam www.mam Hmoéam 2.5..va mvoéam vwoéam bvméam mmmé Hmm
¢.mm mbméum baméam mbméam maoéam whoéam bmoivam mmojvam 2.5.va boa; omm
oém mmoéam Hogan omm.m.nm meoéam NHHJHN mmoéam omoéam hmaéam mmhé mam
mém Soéam omméam $5.3m meoéam «oaéam mmoéam bwoéam Hmaéam mmmé «Hm
mtnm maoéam www.mam mmmgflm mvoéam boaéam Hmoeam emoéam mmméaw mmmé Ham
N.mm mboéam mmm.mam Hmm.m.nm 92”.va mwaéam «wt—”Jam mmaéam wmméam mmbé 3m
Ema www.mHN maaéam mmaéam mmm.m.nm mom.mam mmm.mam mwmdam omm.m.fim ooo.o mom
Ema www.mam mafimam moméam www.mam bmm.mam Nom.mam eaméam omm.mam ooo.o .Sm
e64 ES .94 835 383 Reg Rab. Rm? Ema E is 8 am a
name... Egfig 885 98 as:
.chADMsDUoHu manna noun.» §waofi one mnofluo>oao
wagon HonoB .Auooo. Hfiom oficomuo mo snoop .moofluo>oao moouuom muouo>¢ .H.Q manna

 

APPENDIX E. Water table profiles.

77

78

 

 

 

 

 

 

 

.mm\oa\m Smoounu mm\w\b MOM Nmmtmam maam3 «0 Amuzv daemoun manna Hmuoz .H.m munuwm
Losom sumo:
REV :86 mm Eo: mocmED
OON Om: OO_. 00
835m 4 _ _ 0.03
m©\©\n .I ll
m®\ON\N.II.II . 2L
8thme i!) - 38 m
mm\ow\m . l l r I W."
\ \‘OIIII cl. U
OI: II II. I. i ll 1. ' OI \\\ 0., In." . \.I
9.)) I).I|uhHW ll.|lu.lbtAV\ b): o
n) I) )v u! I). ..\
_ _ _ @er
mxwmu mwmxw mwvmw Mwmxw NSWmu

.ma\oa\a rescues ma\e\e hoe mem-mam made; No 1m-z. aaahoaa mane» hone: .~.m magmas

boson ammo:

AEV :86 mm So: 8:220

 

 

 

 

 

com 09. 09 on o
momtam _ _ _ . 0.9m
9 8me I I
7 mm\om\x I I . B
mahmxm .II r harm m
maxoexm. I I 7 m.
oI I I .9. I I I \ \MIIIhtnluhI“. U
r OIIIIIIIIIIIIOIII'IIIIII II. \“\\n ”II-OI III III O..V—.N M
o. III-III)“ )I.II IIIIIIIII§o\\)\§/.MI I I I
unwititirtw) 1).
_ b — Orv—am

 

 

mmm mmm MVVm Muflm “NW 0 PW

BIBLIOGRAPHY

BIBLIOGRAPHY

Boelter D.H., 1972. Water table drawdown around an open
ditch in organic soils. J. of Hydrology 15, 329-340.

Boelter D.H., & E.S. Verry. 1977. Peatland and water in the
northern lake states. USDA For. Serv. Gen. Tech. Rep.
NC-31: North Cent. For. Exp. Stn., St. Paul, Minnesota

pp. 22.

Boelter D.H., & E. S. Verry. 1978. Peatland hydrology. In:
Wetlands functions and values: the state of our
understanding. American Water Resources Association.

Boggie, R. 1972. Effect of water-table height on root
development of Pinus contorta on deep peat in Scotland.
OIKOS 23: 304-312. Copenhagen.

Brown, 5.8. 1988. Wetland Protection Guidebook. Michigan
Dept. of Nat. Res. Division of Land and Water. State
of Michigan. Lansing.

Burke, W. 1967. Principles of drainage with special
reference to peat. Irish Forestry. Vol. 24.1

Carter, V., M.S. Bedinger, R.P. Novitzki & W.O. Wilen. 1978.
water resources and wetlands (Theme Paper). In: Wetland
Functions and Values: The State of our Understanding.
Greeson, P.E., J.R. Clark, J.E. Clark. eds. National
Symposium on Wetlands; Falls Hydraulic Laboratory.
American Water Resources Association. November. pp.
344-376.

Crum, H. 1988. A focus on peatlands and peat mosses.
University of Michigan Press.

Curtis, J.D. 1946. Preliminary observations on northern
white-cedar in Maine. Ecology 27, No. 1;23-36.

Cwikiel, W. 1992. Michigan Wetlands, Yours to Protect A
Citizen's Guide to Local Involvement in Wetland
Protection. Tip of the Mitt Watershed Council. Conway
Mi.

Glaser, P.H., G.A. Wheeler, E. Gorham & H.E. Wright Jr.
1981. The patterned mires of the Red Lake peatland,
northern Minnesota: Vegetation, water chemistry and
landforms. J. of Ecology. 69:575-599.

80

81

Glaser, P.H., J.A. Janssens & D.I. Siegel. 1990. The
response of vegetation to chemical and hydrological
gradients in the lost river peatland, northern
Minnesota. J. of Ecology.

Heikurainen, L. 1968. On the influence of cutting on the
water economy of drained peat lands. Acta Forestalia
Fennica. Vol:82.

Heikurainen, L. & J. Paivanen. 1970. The effect of
thinning, clear cutting, and fertilization on the
hydrology of peatland drained for forestry. Acta
Forestalia Fennica. Vol. 104

Ivanov, K.E. 1981. Water Movement in Mirelands. Academic
Press Inc. New York, NY. 276 p.

Johnston, W.F. 1977. Manager's handbook for northern white-
cedar in the north central States. USDA For. Serv.
Gen. Tech. Rep. NC-35, 18 p. North Cent. For. Exp.
Stn., St. Paul, Minnesota.

Johnston, W.F. 1990. Northern White-Cedar. In: Silvics of
NOrth America: 1. Conifers. Burns, Russell M., &
Barbara H. Honkala, tech. coords. Agriculture Handbook
654. USDA For.serv. Washington, DC. 675 p.

LeBarron R.K. & J.R. Neetzel. 1942. Drainage of forested
swamps. Ecology, Vol. 23, No.4:457-465

Lieffers, V.J. 1989. Growth and foliar nutrient of black
spruce and tamarck in relation to depth of water table
in some Alberta peatlands. Can. J. For. Res. Vol. 20.
805-809.

McKee, W.H. Jr. & E. Shoulders. 1970. Depth of water table
and redox potential of soil affect slash pine growth.
Forest Science, Vol. 16:4

Miller, R.O. 1992. Ecology and management of northern
white-cedar. In: Proceedings of a workshop held in
North Bay on December 4th and 5th 1990. Central
Ontario Forst Technology Development Unit. Tech.
Report No. 28

Miller, R.O., D. Elsing, M. Lanasa & M. Zuidema. 1990.
Northern white-cedar: Stand assessment and management
options. In: Proc. of Northern White-Cedar in Michigan
workshop. Sault Ste. Marie, Mi Feb. 1990.

82

Miller, R.O., R. Chimner & M. Zuidema. 1994. Bob's Lake
Study. Mich. Dept. Nat. Res., Escanaba office. In
preperation.

Mitch, W.J. & J.G. Gosselink. 1986. Wetlands. New York:
Van Nostrand Reinhold Company.

Nelson, T.C. 1951. A reproduction study on northern white-
cedar. Res. Rep. for the Game Division of the Michigan
Department of Conservation. Lansing, MI. p. 99

Patrick, W.H., Jr. 1978. Chemistry of flooded soil and
effects on mineral nutrition. In: Proc. Soil
Moisture, Site Productivity Symposium. ed. William E.
Balmer. Myrtle Beach, S.C. Nov 1-3, 1977. pp. 40-48.

Patrick, W.H., Jr. & A. Jugsujinda. 1992. Sequential
reduction of inorganic nitrogen, manganese, and iron in
flooded soils. Soil. Sci. Soc. Am. J. 56:1071-1073.

Pregitzer, K.S. 1990. Northern white-cedar: Stand
assessment and management options. In: Proc. of
Northern White-Cedar in Michigan workshop. Sault Ste.
Marie, MI. Feb. 1990.

Romanov, V.V. 1961. Hydrophysics of bogs. Israel program
for scientific translations. Jerusalem.

Satterlund, D.R. 1960. Some interrelationships between
groundwater and swamp forest in the western Upper
Peninsula of Michigan. Dissertation. University of
Michigan.

Shotyk, W. 1984. An overview of the geochemistry of
peatland waters. In: Proc. Advances in Peatland
Engineering. Carleton University, Ottawa, Canada.
National research Council of Canada. pp. 159-171.

Sikora, L.J. & D.R. Keeney. 1983. Further aspects of soil
chemistry under anaerobic conditions. In: Ecosystems of
the World. Vol 4A. Mires:Swamps, Bog, Fen and Moor.

New York, NY. Elsevier Science Pub. Co. pp. 247-255.

Smith, D.A. 1986. The Practice of Silviculture. 8th
Edition. John Wiley & Sons, Inc.

Soil Survey Manual. 1993. USDA Handbook No. 18. Washington
D.C.

Stanek W. & I.A. Worley. 1984. A terminology of virgin peat
and peatlands. In: International Symposium on Peat

83

Utilization. C.H. Fuchsman and S.A. Spigarelli, eds.
Bemidji State University Center for Environmental
Studies.

Thornton, P.L. 1957. Problems of managing upper Michigan's
coniferous swamps. J. For. 5:192-197.

Verry, E.S. 1975. Streamflow chemistry and nutrient yields
from upland-peatland watersheds in Minnnesota.
Ecology. 56:1149-1157.

Verry, E.S. 1980. Water table and streamflow chanes after
stripcutting and clearcutting an undrained black spruce
bog. In: Proc. of the 6th International Peat Congress.
Internation Peat Society.

Verme, L.J. 1965. Swamp conifer deeryards in northern
Michigan: their ecology and management. J. For. 63:523-
529.

Vompersky, S.E. 1968. Biological foundations of forest
drainage efficiency. U.S. Dept. of Commerce. Natl.
Tech. Info. Service, Springfield, Va.

Winter, T.C. 1988. A conceptual framework for assessing
cumulative impacts on hydrology of nontidal wetlands.
Environmental Management. 12:605-620.

Winter, T.C. & Woo, M-K. 1990. Hydrology of lakes and
wetlands. In: Surface water Hydrology. M.G. Wolman &
H.C. Riggs,eds. Boulder, Colorado. Geological Society
of America, The Geology of North America.

Yoshida, T. 1975. Microbial metabolism of flooded soils.
In: Soil Biogeochemistry. Vol 3., eds. E.A. Paul and
A.D. McLaren. New York. Marcel Dekker, Inc.

Zasada, Z.A. 1952. Reproduction on cut-over swamplands in
the Upper Peninsula of Michigan. U.S.D.A. Forest
Service, Lake State Forest Experiment Station. Station
Paper No. 27.

Zon, R. & J.L. Averell. 1930. Growth in swamps before and
after drainage. J. Foresrty 28:100-101.