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This is to certify that the

thesis entitled

Vegetation Responses to Prescribed

Burning in a Mature Red Pine Stand

presented by

Sandra J. Henning

has been accepted towards fulfillment
of the requirements for

M.S. degree in ForeStry

 

 

 

 

Major profekss/or

Date 2/14/92

 

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TO AVOID FINES return on or before one due.

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MSU Is An Affirmative ActiorVEquel Opportunity Institution
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w"

VEGETATIVE RESPONSES TO PRESCRIBED BURNING IN A MATURE RED
PINE STAND

BY

Sandra J. Henning

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

MASTER OF SCIENCE

Department of Forestry

1992

ABSTRACT

VEGETATIVE RESPONSES TO PRESCRIBED BURNING IN A MATURE RED

PINE STAND

BY

Sandra J. Henning

Prescribed burning techniques were explored in a red pine
(Pinus resigosa) plantation in northern lower Michigan to
promote wildlife, timber, and recreational benefits. Three
experimental blocks were divided into four treatment plots
which were burned every 2, 5, and 10-years, with one plot
serving as a control. Overstory and understory woody and
herbaceous vegetation were measured most recently in 1991, six
years after the study began. Results indicate that prescribed
burning, if done properly, will not adversely effect the
overstory. Burning had no significant effects on total
herbaceous cover or on herbaceous species richness. However,
it did effect species composition. Frequent burning reduced
the total number of woody stems present, and had a large
impact on species composition. Those species able to respond
to fire were primarily vegetative sprouters, with a larger
percentage of seeders present as time between burn intervals
increased. Initial findings indicate that burning at long
intervals under a thinned red pine stand will enhance

wildlife, recreation, and timber objectives.

ii

ACKNOWLEDGEMENTS

Many people have contributed.their time and effort in the
initiation and continuity of this study. I would personally
like to recognize Don Dickmann, my major professor, who was
responsible for making this study a reality. I feel fortunate
to have had a major professor with a background in fire and
siviculture, and one who could match my academic interests in
those areas with a hands-on project. My committee members,
Karen.Potter-Witter and.Bud.Hart, have also been supportive in
my educational goals and I thank them for their help in
preparing this thesis. Thanks also go out to the Department
of Natural Resources and the staff of the Pigeon.River Country
State Forest, who have been instrumental in project
continuity; In addition, I*would like to thank.those who.have
previously worked on this project and were responsible for
initial plot layout and data collection. Finally, I would
like to recognize Brian Palik who helped me considerably.

I sincerely thank him for his time and for showing an interest

in my work.

iii

List of Tables. . .

TABLE OF CONTENTS

List of Figures. . . . . . . . . . . . . . . .

Introduction. . . .

Statement of Problem.

Background. .

Objectives and Hypotheses of the Study

Methods. . . . . .

Experimental Site.

Fire Schedule.

Sampling Design .

Data Analysis.

Results and Discussion:

Overstory. . .

Ground Vegetation.

Woody Understory Density.

Species Richness - Woody Understory.

Woody Understory Composition.

Conclusions and Recommendations.

Appendix:

List of References.

iv

Completed ANOVA's for entire study.

14

LIST OF TABLES

Table
1. Stand & Stock Table for Red
2. Stand & Stock Table for Red

3. Stand Table for Red Pine in
Number of Trees per Hectare

4. Stock Table for Red Pine in

Pine in Block A.
Pine in Block B.

Block C; Mean
and per Acre. .

Block C; Mean

Gross Cu. Meters/Hectare and Cu. Ft./Acre. .

5. Overstory Characterisitics for

Blocks A, B, and C. . . . .

6. Effects of Burning Intervals on Total Percent

Cover and Species Richness of
Herbaceous Ground Vegetation. . . . .. . . .

7. Effects of Burning Intervals on Percent
Coverage of Various Understory Species in

a Mature Red Pine Stand . .

8. Species with Greater than 1% Ground Coverage,

Averaged by Treatment. . . .

9. Effects of Burning Interval

on Density

(stems/ha) of the Woody Understory

in a Mature Red Pine Stand.

10. Effects of Burning Interval on Average Species

Richness (no. of species) in the Woody
Understory of a Mature Red Pine Stand. . . .

11. Effects of Burning Intervals on Density

(stems/ha) of Various Woody

Understory

Species in a Mature Red Pine Stand. . . . .

12. Ranking of Species Importance,

Averaged by Treatment. . . .

13. Total Percent Cover of Herbaceous
Vegetation by Burning Interval and Block. .

Page

. 15

.16

.17

. 22

.25

. 31

.36

. 42

.46

.59

Table

14.

15.

16.

17.

18.

19.

20.

21.

22.

23.

24.

25.

26.

27.

28.

29.

30.

Species Richness of Herbaceous Vegetation

by Burning Interval

and Block. . . . . . .

Total Percent Ground Cover of Mosses and
Lichens by Burning Interval and Block. . .

Total Percent Ground Cover of Grasses by
Burning Interval and Block. . . . . . . .

Total Percent Ground Cover of Black Cherry

by Burning Interval

and Block. . . . . . .

Total Percent Ground Cover of Rubus Spp.

by Burning Interval

and Block. . . . . . .

Total Percent Ground Cover of Brackenfern

by Burning Interval

and Block. . .. . . .

Total Percent Ground Cover of Red Pine

by Burning Interval

and Block. . . . . . .

Total Stems per Hectare by Burning

Interval and Block.

Total Stems per Hectare by Burning

Interval and Block,

0.109 cm. 0 O O O O 0

Total Stems per Hectare by Burning

Interval and Block,

2-5.9 cm. 0 e e e e e

Total Stems per Hectare by Burning

Interval and Block,

Species Richness in
by Burning Interval

Species Richness in
by Burning Interval

Species Richness in
by Burning Interval

Species Richness in
by Burning Interval

6-9.9 cm. . . . . . .

the Woody Understory
and Block. . . . . .

the Woody Understory
and Block, 0-1.9 cm. .

the Woody Understory
and Block, 2-5.9 cm .

the Woody Understory
and Block, 6-9.9 cm .

Total Stems per Hectare of Black Cherry

by Burning Interval

and Block. . . . . .

Total Stems per Hectare of Red Maple

by Burning Interval

and Block. . . . . . .

vi

Page

.62

.65

.67

.68

.69

.70

.71

.72

.73

.74

.75

Table

31. Total Stems per Hectare
by Burning Interval and

32. Total Stems per Hectare
by Burning Interval and

33. Total Stems per Hectare
by Burning Interval and

34. Total Stems per Hectare
by Burning Interval and

35. Total Stems per Hectare
by Burning Interval and

of Birch
Block. .

of White
Block. .

of Beech
Block. .

of Aspen
Block. .

of Choke
Block. .

vii

Page

77

78

79

80

81

LIST OF FIGURES

Figure
1. Experimental Design. . . . . . . . . . . . . . . . .
2. Average Percent Ground Cover, by Treatment. . . . .
3. Average Percent Ground Cover,

by Treatment and Species. . . . . . . . . . . . . .
4. Total Stems per Hectare by Treatment. . . . . . . .
5. Total Stems per Hectare by Size Class and Treatment.
6. Stems per Hectare by Treatment and Species. . . . .

viii

24

35

.37

45

INTRODUCTION

statement of Problem

Today, the forests of the Lake States contain over
486,000 hectares (1.2 million acres) of red pine (mug
regingga), an important component of the timber resource in
this region (Schone et. a1 1984). In addition, nearly 1/4 of
these stands in Michigan are 40 years and older (Dickmann et
a1. 1986). Red pine plantations, however, have often been
criticized as being poor wildlife habitat, especially
overstocked plantations. Because timber, wildlife, and
recreation are key management objectives on state and federal
lands in Michigan, and red pine represents a large component
of our forests, it is important to»employ proper silvicultural
management in this type. This argues for management of red
pine to improve wildlife habitat and aesthetics, especially
when confronted with the lack of conifer species alternatives
for timber due to the jack pine budworm and white pine blister
rust.

0n better soils, especially following thinning, middle-
aged red pine stands develop a dense hardwood or mixed
hardwood-conifer understory. The understory competes with the
pine for water, nutrients, and space. Moreover, as the
understory matures, wildlife browse is reduced, as are
accessibility and aesthetics. One technique for managing the
understory in pine stands is prescribed burning (Methven and
Murray 1974, Mobley et. al 1973, Van‘Wagner 1965). Prescribed

burning is a silvicultural tool that is commonly used

2

throughout the southern pine and western conifer regions (Wade
and Lunsford 1989, Walstad et al. 1990). In the Lake States
however, prescribed burning under pine is*virtually’unknown as
an operational practice (Dickmann 1991). Many managers are
unsure of its effects and lack experience in its use. In
addition, selecting proper fire conditions can be a problem
because of the unpredictable weather in Michigan. Until
underburning in red pine can be demonstrated to be safe, and
data on specific effects in stands growing on Michigan soils
are produced, this practice will not become an operational
part of forest land management in the Lake States. This study
investigates the effects of management of the understory in a
wide-spaced, mature red pine plantation with prescribed

burning.

Background

Immediately after regeneration, and then following the
first thinning, the total understory of a red pine stand is
available for the production of game food plants and shrubs,
and for hunting, without affecting the timber crop (Miller
1964). Prescribed burning can serve to manipulate understory
vegetation, to the advantage of wildlife habitat, aesthetics,
and timber management. Control of stand density and
composition are the principal means by which timber and
wildlife habitat needs are coordinated (Miller 1964). Red
maple (Agerg rubrum), grasses, and. brackenfern (Pteridium

agui 1i num) ; the most common plants found under wide-spaced red

3

pine; are favored forage species for deer at certain times of
the year (Rogers et al 1981). Correctly handled, prescribed
burning should benefit game by increasing herbaceous growth
and providing new sprout growth.of woody plants (Little 1952).
Frequent (5 - 10 year intervals), low intensity fires may kill
aerial portions of any hardwood vegetation, and thus promote
low coppice growth, which provides wildlife browse (Rouse
1988). Sprouts of many species are favored foods of white-
tailed deer (Perala 1974). Buckmann (1964) found close
relationships between wildfire and the maintenance of high
populations of white-tailed deer or sharp tailed grouse.
Sprouts occasionally form on standing live trees but sprouting
is most vigorous after the bole is felled or killed, such as
by fire (Perala 1974). Also, in areas valued for recreation,
fire can.make a stand more accessible as well as more visually
pleasing. The success of prescribed burning in controlling
woody plants and grass under a stand of trees depends upon the
presence of an overstory resistant to damage by fire and an
understory easily destroyed by fire (Buckmann 1964).

Red pine is a species ideally suited for intermediate
stand.management: it grows well over'a wide range of stocking
densities (Berry 1984); diameter growth responses to thinning
are excellent (Lundgren 1981); and from small sawtimber size
onwards, it is adapted.to the use of prescribed.burning in the
understory (Van Wagner 1970) . To increase recreation and
wildlife objectives, stocking densities below what might be

considered optimum for timber production could be adopted

4

(Dickmann 1991). Heavy thinnings, to 16 - 21 square meters
per hectare (7O - 90 square feet per acre), combined with
prescribed burning to maintain a low understory, produces
valuable, large diameter trees as well as a plant layer that
is utilized by wildlife.

A thorough review of the multiple-use benefits and
techniques of prescribed burning in red pine stands was

prepared by Dickmann (1991).

Objectives and Hypotheses of the study (Dickmann 1990)
Objectives

1. Quantify the extent and composition of the understory in
once thinned red pine stands growing on good quality sandy
loam soil.

2. Assess the effects of spring prescribed fires in red pine
stands on overstory characteristics and understory composition
and development.

3. Determine the feasibility and effects of repeated
prescribed burns at 2, 5, and 10-year intervals on understory
composition and development as compared to no burning.

4. Provide conclusions and recommendations on burning

intervals in relation to timber and wildlife objectives.

Hypotheses
1. Thinning red pine stands on good soils stimulates the
development of a diverse and extensive understory of

herbaceous and woody plants.

5

2. Low-intensity prescribed fires will have little effect on
the overstory in mature red pine stands.

3. Burning at long intervals will hold back the development
of the woody understory in thinned red pine stands, but will
have little effect on the extent and diversity of the
herbaceous understory.

4. Repeated burns at short intervals will reduce both the
extent and.diversity of the herbaceous and woody understory in
thinned red pine stands. Fire intolerant species will die
out, whereas certain fire stimulated species will increase in

abundance.

METHODS
Experimental site

The study site was located in the Pigeon River Country
State Forest in northern lower Michigan; T33N, R1W, section
25. The forest is known for its game habitat; with white-
tailed deer, elk, snowshoe hare, turkey, and ruffed grouse
being most prominent. The study area is approximately a 61
hectare (150-acre) plantation which was established in 1931
with a mixture of red, white (Pings strobus), and jack pine
(Pinus banksiana) seedlings. In 1970, all white and jack pine
were thinned out, leaving an average residual basal area of 10
square meters per hectare (40 square feet per acre), an
understocked condition for this species. This is a productive
site for red pine; the Emmet sandy loam soils produce a site
index of 20 meters (65 feet) at 50 years of age.

During the summer of 1983, three experimental treatment
blocks were established (Blocks A, B, and C), which varied in
size from 6-8 hectares (15-20 acres). Blocks A, B, and C were
then divided into 7, 7, and 8 plots (experimental units),
respectively. Overstory density varied, with Block A the
heaviest at 24 square meters per hectare (104 square feet per
acre) and Block C the lightest at 13 square meters per hectare
(58 square feet per acre). Block C had the most dense
understory, followed by Block A and Block B. Block B was
recently thinned, accounting for its low stem density.

Each plot was randomly assigned a spring burning

treatment with a fire frequency of 2, 5, or 10 years. One

7
plot in each block was designated as a control for comparison
purposes, except in Block C where there were two control
plots“ ‘Within.each.plot, two transects were established which
ran on a north-south compass line. Along each transect in
Blocks A.and B, five subplots or points were randomly assigned
for measurement purposes. Six subplots were set out along
each transect in Block C. Each point was permanently marked
with a metal stake. Figure 1 depicts the overall

experimental design and treatment layout of each block.

Fire Schedule

Spring burning has taken place more or less according to
schedule. Burns in the two-year treatments have been
completed four times, in 1985, 1987, 1989, and 1991. Burns in
the five-year treatments have been completed twice, one in
1985, and one in 1990. A single burn was completed in the
ten-year treatments in 1985, and a second burn is scheduled
for 1995. Very little information regarding weather
conditions and fire factors for the prescribed burns, which
were conducted by the Department of Natural Resources (DNR),
are available. The burns have varied in intensity and in the
degree to which the understory vegetation was affected. Most
burns were moderate in intensity. Techniques of burning also
differed; some burns were backfired and others perimeter
ignited. It is hoped that better communications between the
Michigan State Forestry Department and the DNR.are kept in the

future to ensure fire information is recorded and passed on,

  

 

 

 

 

 

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9

and that proper firing techniques are also used (i.e. strip
headfires). Headfires should be used because they are often
less damaging than backfires; the heat is carried upward more
rapidly and high temperatures are not as long sustained near
the ground (Smith 1986).

It is also very important to keep in mind the length of
time elapsed since each of the plots was last burned. When
measurements were taken, six growing seasons had elapsed since
the 10-year plots were burned, one4growing season since the 5-
year burns, and zero for the two-year burns, with measurements
taken in the same year as these plots were burned- Therefore,
the results indicate the effects of fire after a growing
period of 2-months, 1-year, and 6-years since the last burn;

not 2, 5, or 10-years, respectively.

Sampling Design
The vegetation on each plot was divided into three
strata for measurement purposes: ground vegetation consisted
of all vascular plants less than 1.4 meters in height (4.5
feet); woody understory was all woody plants more than 1.4
meters in height and less than 10 centimeters (4 inches) in
diameter; while overstory comprised all trees over 10
centimeters in diameter, most of which was red pine.
Ground vegetation was measured at each sampling point
along every transect. Frequency and percent cover of all
species were estimated using one square meter circular

subplots randomly located along each transect, which

10

themselves were randomly located within each burning
compartment. A rope 56.4 centimeters (1.85 feet) long was
centered on each plot center (the stake) for data collection.
Each species of ground vegetation falling within that radius
as well as percent cover of each species within the circular
subplot was recorded” Ground vegetation could then be
characterized by relative frequency and percent cover. Blocks
A and B had 10 ground vegetation measurement subplots per
treatment, while Block C had 12. Each of those subplots
became a permanent measuring point and a basis for gathering
all data.

Woody’ understory’ was assessed. at two sample points
randomly chosen along transect lines using a 147 square meter
subplot. A rope, 14.8 meters long, running north and another
rope, 9.9 meters long, running east from the plot center stake
were used to lay out the sampling area. All woody understory
species more than 1.4 meters tall and less than 10 centimeters
in diameter were recorded into three different diameter size
classes: 0-1.9 cm, 2-5.9 cm, and 6-9.9 cm (0-0.75 in., 0.75-
2.3 in., and 2.3-3.9 in.). Woody understory vegetation could
then be characterized by frequency and density from a total of
four measurements per treatment.

Overstory measurements were taken at the point along each
transect where woody understory subplots were measured. A.
relaskop with a basal area factor of 10 was used to determine
basal area and tally trees. Each tally tree’s diameter at

breast height was measured with a diameter tape, and a

11

relaskop was used to determine merchantable height in 2.4
meter sticks (8 feet) to a 10 centimeter top (4 inches). This
protocol resulted in two overstory measurement points per
treatment. Overstory data was then entered into the inventory
program INVENPRO (an inventory processor for the Lake States)
to create stand and stock tables for each block.

Because the major objective of this study was to assess
the vegetative responses to prescribed burning, a complete
inventory of the area was completed in 1984, prior to the
first fire. Post-burn measurements have been made in three
different years, starting in 1985. The second set of
measurements were taken in 1988, and the third in 1991. Each
time data was collected after August 1. Data from each block
was totaled and averaged by treatment for recording and
analyzing purposes.

In instances where 3plot stakes ‘were 'vandalized or
missing, an attempt was made to relocate that point at it’s
original location as identified in the original data sheets.
It is safe to assume that relocated points were not in their
exact original position. IBlock.B was completely reset in both
1988 and 1991, most points being in slightly different
locations. In addition, this block was recently thinned to
its ‘present. density; making' comparisons. between. data of
different years very difficult. Therefore, 1991 data was used
for the principle comparisons and findings of this paper,

except where noted.

12

Data Analysis

Total percent cover of ground vegetation by treatment and
species was computed. Because data was expressed in
percentages, an arcsin transformation was done to normalize
the data. Analyses of variance (ANOVA’s) were conducted on
the transformed values, and F-max tests were performed to
ensure that variances were homogeneous. However, graphs and
tables which depict percent cover report original percentages,
and standard errors are based on those original percentages.
In all cases where separation of means were performed, the
orthogonal method was used. This method was used to compare
means in three different ways: 1) the 2 and 5-year treatments
against the 10-year treatment and control, 2) the 10-year
treatment vs. the control, and 3) the 2-year treatment vs. the
5-year treatment. It was assumed that these tests were based
on a two-sided hypothesis, and appropriate significance values
were used. Due to the low number of replicates and
heterogeneous nature: of the experimental blocks, a
significance value of 20% was deemed acceptable when
separating means for the entire study. A significance value
of 10% was acceptable for all analyses of variance.

F-max tests were performed on original data collected for
the woody understory. It was found that the variances were
not homogeneous, and therefore, transformation of the data was
necessary. For all data relating to stems per hectare (by
totals, size class, and species), transformations took the

form of ln(x+1), where x = the original value. It was

13
necessary to add one to each number before transforming due to
the presence of zeros in the original data sets. Subsequent
F-max tests were performed and variances were found to be
homogeneous. Analyses of variance were then conducted on
transformed values. Again, all tables and figures report
original values with means and standard errors based on that
original data. Complete ANOVA’s for the entire study may be
found in the Appendix of this document; the reader should

refer to them when necessary.

RESULTS AND DISCUSSION
Overstory

Stand and stock tables for Blocks A, B, and C are
presented as Tables 1, 2, 3, and.4. Block A was most dense at
24 square meters per hectare (104 square feet per acre),
followed by Block B at 68 and Block C at 60 square feet per
acre. Only Block C had species in the overstory other than
red pine which were greater than 10 cm (4 inches) in4diameter.
A t-test was performed which showed that Block A was
significantly different from Blocks B and C in terms of
density. Block B and Block C were not significantly
different. Obviously, these differences in stocking will have
some effect on species composition and understory stocking of
the woody understory and herbaceous ground cover.

To describe the effects of prescribed burning on the
overstory is not a primary objective of this study. However,
some important points regarding this stratum must be
discussed. In general, the prescribed burns which were
conducted had few adverse effects on the overstory. Some
problems did exist with overstory mortality at the initiation
of the study. Where fires burned very hot and slash
concentrations after initial thinnings were high, some
mortality occurred; e.g. Block A, plot 7 and Block B, plot 1.
However, as the DNR burning crews became more experienced and
after slash concentrations were diminished, the fires became
much more predictable. I could find no evidence of overstory

mortality related to any recent burns.

14

15

Table 1. Stand and Stock Table for Red Pine* in Block A

 

 

 

Dbh Mean Number of Trees Volume**
(cm.) (in.) per ha. per acre cu. meters/ha cu.ft./acre
28 11 5 2 1.3 19
31 12 20 8 9.3 133
33 13 22 9 13.4 192
36 14 40 16 26.8 383
38 15 32 13 25.8 369
41 16 40 16 35.1 502
43 17 15 6 16.2 231
46 18 20 8 21.1 301
48 19 2 1 1.7 24
51 20 5 2 6.3 90
53+ 21+ 2 1 4.3 62
Total 203 82 161.4 2306

(+-16.7) (+-239)
Basal Area 24 104

Table 2. Stand and Stock Table for Red Pine* in Block B

 

 

 

Dbh Mean Number of Trees . Volume**
(cm.) (in.) per ha. per acre cu. meters/ha cu.ft/acre
33 13 7 3 4.1 58
36 14 10 4 6.3 90
38 15 15 6 12.5 178
41 16 37 15 35.5 508
43 17 32 13 33.4 477
46 18 15 6 19.3 276
48 19 2 1 2.0 28
Total 119 48 113.0 1615
(+-7.9) (+-113)
Basal Area 15.6 68

* : The overstory of Blocks A and B contained only red pine

**: Species specific volume equations from Hahn (1984)

 

16

Table 3. Stand Table for Red Pine in Block C; Mean Number of
Trees per Hectare and (per acre).

 

 

 

Dbh
(cm.) (in.) Red Pine Sugar Maple White Pine Total
15 6 12 (5) o 0 12 (5)
28 11 5 (2) 0 0 5 (2)
31 12 2.5 (1) 0 2.5 (1) 5 (2)
33 13 7 (3) 0 0 7 (3)
38 15 5 (2) 2 (1) o 7 (3)
41 16 25 (10) 0 0 25(10)
43 17 12 (5) o 0 12 (5)
46 18 17 (7) 0 0 17 (7)
48 19 12 (5) 0 0 12 (5)
51 20 7 (3) o 0 7 (3)
Total 104.5 (43) 2(1) 2.5 (1) 109(45)
Basal Area 13.3 (58) .2 (1) .2 (1) 14 (60)

Table 4. Stock Table for Red Pine in Block C; Mean Gross Cu.
Meters/Hectare and (Cu. Ft./Acre) (without bark)*

 

 

Dbh
(cm.) (in.) Red Pine Sugar Maple White Pine Total
15 6 1.2 (17) o o 1.2 (17)
28 11 .6 (9) 0 0 .6 (9)
31 12 1.3 (18) 0 .7 (10) 2.0 (28)
33 13 4.3 (61) o o 4.3 (61)
38 15 2.1 (30) .3 (4) 0 2.4 (34)
41 16 20.4 (291) 0 o 20.4(291)
43 17 11.7 (167) 0 0 11.7(167)
46 18 18.2 (260) o 0 18.2(260)
48 19 13.5 (193) 0 o 13.5(193)
51 20 9.2 (132) 0 0 9.2(132)
53+ 21+ 1.5 (22) 0 0 1.5(122)
Total 84 (1200) .3 (4) .7 (10) 85 (1214)

+-12 (+-172)

* : Species specific volume equations from Hahn (1984).

17

Table 5. Overstory Characteristics for Blocks A, B, and C.

 

Basal Area Average Diameter Volume

2 2 3 3
m /ha ft./acre (cm.) (in.) m/ha ft./acre
Block A 24.0 104 42.4 16.7 161.4 2306
Block B 15.6 68 41.6 16.4 113.0 1615

Block C 14.0 60 43.4 17.1 109.0 1214

 

18

Mature red pine is tolerant of understory fires and many
authors have had successful results with underburning.
Niering (1970) conducted a study in which burning was done
with no mortality to the overstory. In fact, studies done
with red pine have failed to show any adverse effect of
underburning on overstory tree growth, provided excessive
crown scorch is avoided (Alban 1977, Methven and Murray 1974)

Red pine is essentially a fire-adapted species (Van
Wagner 1970) and several factors will determine if fire
injures or kills a tree. Those factors include lethal
temperature, season, bark characteristics, size and vigor of
the tree, and specific fire characteristics (Rouse 1988). A
few comments about each of those factors discussed by Rouse
(1988) follows:

Season - In spring, the forest floor litter layer is
winter cured and dry, whereas the fermentation and humus
layers are moist" ‘Wildfires spread quickly in red.pine stands
during this season, yet they burn shallowly, causing little
damage to the soil or roots. Different burning seasons have
been recommended for different burning objectives; spring
burning is addressed here because it is generally a more
reliable season for burning in the Lake States. In addition,
only spring burns were conducted for the present study; no
fall burns were possible due to improper weather conditions.

Lethal temperature - Researchers have shown that when
living tissue reaches 64 degrees Celcius (147 degrees

Farenheit), it dies almost instantaneously. Red pine is well

19
known for its ability to produce thick bark which, because of
its insulating qualities, enables the stem of mature trees to
withstand fire. Needles, however, can quickly reach lethal
temperature if they are in the convection column of a hot
surface fire (Dickmann 1991).

Fire characteristcs - Greater fire intensity means that
more energy is directed at the tree so the probability of
injury increases. The intensity of a flaming front can be
estimated from flame length" iMethods to estimate both rate of
spread and flame length in the field.have been devised (Simard
et al. 1989).

Size and Vigor - Until a red pine is around 18 meters
tall (60 feet) (approximately 50 years old), either the basal
cambium or crown can be killed. After the tree reaches this
height, the bark is thick enough to protect the cambium from
all but the most extreme fires and the majority of the crown
is far above the flames. Although tall trees are still
susceptible to crown damage, they may survive even though 75-
85% of their original crown was scorched (Van Wagner 1970).

Van Wagner (1970) found that the crowns of pine stands
maintain maximum flammability up to heights of around 18
meters (60 feet), and thereafter the possibility of crown fire
is lessoned by the increasing height of the open trunk space.
Crown fires in mature red pine stands are, thus, a rare
occurrence. The usual limitation to the survival of red pine
in a surface fire is its susceptibility to crown scorch by hot

gas rising above the flames (Van Wagner 1970). Burning on

20

cool days can minimize scorching (Dickmann 1991). Low
intensity fires of no more than 0.6 meter (2 feet) flame
heights cause little or no scorching and the risk of a crown
fire is slight. An average energy release of less than 165
kcal/sec.-m (200 Btu/sec.-ft.) will leave mature red pine

crowns untouched (Van Wagner 1970).

Ground Vegetation

It would appear that there is a difference between
treatments when comparing total percent cover (Figure 2) .
However, upon examining Table 6, no significant differences
were found after conducting an analysis of variance. 'This may
be due to the low sample size and large variability between
experimental units. Block C had the largest percent cover,
followed by Blocks A, and B. These differences between blocks
probably affected treatment values. Block C had the most open
canopy, accounting for a high ground cover percentage, whereas
Block B had been recently logged, probably accounting for a
relatively lower percentage of ground cover. In any event,
total percent ground cover varied anywhere from 35% to 55%
between treatments. Due to the scattered distribution of the
vegetation, no definite relationship to burning frequency
could be determined.

Species richness of ground vegetation, which may be
defined as the total number of different species found in a

certain treatment, was also examined. No significant

60

50

40

30

percent ground cover

21

 

 

 

 

 

 

 

 

 

 

 

 

 

2 years 5 years 10 years
burn interval

Figure 2. Average Percent Ground Cover,

control

by Treatment

 

22

Table 6. Effects of Burning Intervals on Total Percent Cover
and Species Richness of Herbaceous Ground Vegetation*

Burning Interval

 

 

2 years 5 years 10 years control
Percent Cover 35.8 42.4 55.9 35.3
(8.7) (12.0) (13.4) (6.8)
Species Richness 21 19 23 22
(No. of spp.) (2.5) (4.0) (2.6) (3.5)

*: Treatments were not significantly different. Standard
errors are shown in parentheses.

23

differences were found between treatments (Table 6). Species
richness ranged from 19 different types of vegetation in the
5-year treatment to 23 species in the 10-year treatment.
According to this analysis, burning had no effect on species
richness of ground vegetation.

Although burning did not have significant effects on
total percent ground cover or species richness, it did appear
to effect species composition and importance (Figure 3) . Those
species which appear to be most affected by burning include
mosses and lichens, MAE spp. , grasses, brackenfern and black
cherry (Ergngs sergtin§)-

A significant difference between treatments existed at
the 5% error level for coverage of mosses and lichens (Table
7) . Significant differences were found between percent ground
cover of short-rotation.fires (2-year and 5-year intervals) as
compared to fires with a longer rotation (10 years) or no fire
at all; the percentage of mosses and lichens increased as
time between burns increased (Figure 3). There was also a
significant difference between one burn and no burn at all, as
seen when comparing the 10-year treatment to the control
(Table 7) . However, no significant difference existed between
the 2-year and 5-year treatments. Burning’s net effect on
mosses and lichens was to reduce their abundance. Mosses and
lichens decreased from approximately 9% cover in the control
to 4% in the 10-year treatment to about 2% in the 2 and 5-
year treatments.

There appears to be an obvious pattern between burning

24

 

 

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QZ-years S-years 4” IO-years @wntrol

brackenfern moss/lichen rubus

Average Percent Ground Cover,

by Treatment and Species

Figure 3 .

25

Table 7. Effects of Burning Intervals on Percent Coverage of
Various Understory Species in a Mature Red Pine Stand.*

Burn Interval (years)

 

Species 2 5 10 control
Moss and 2.2 a 2.0 a 4.3 b 9.1 c
Lichens (0.46) (0.96) (1.3) (1.5)
Grasses 4.4 a 12.7 a 16.9 a 3.8 a
(2.6) (5.6) (8.9) (1.2)
Black 1.6 a 1.5 a .26 b 0.5 b
Cherry (0.41) (0.26) (0.12) (0.25)
Rubus spp. 7.4 a 6 a 9.5 a 2.8 a
(3.4) (1.7) (5.0) (0.4)
Brackenfern 10.9 a 6.8 a 14.1 a 5.0 a
(5.7) (3.8) (11.3) (4.4)
Red pine 0.6 a 1.8 b 1.7 c 1.6 c
(0.5) (1.3) (0.9) (0.8)

 

*: Means followed by the same letter are not significantly
different (p <= 0.2) using the orthogonal test. Standard
errors shown in parentheses.

26

frequencies and grass cover (Figure 3) . However, differences
between treatments were not conclusive upon analysis of
variance. However, I think it is safe to conclude that
burning, especially at 5 or 10-year intervals, stimulates
grass growth. Other authors have reported similar findings.
For example, Luppino (1984) found that grasses occurred more
frequently and covered more area in burned sections than in
unburned sections in a similar study in the same area.
Ahlgren (1979) found that grass seeds were more abundant in
burned areas than in unburned areas in a Minnesota study.
Burning stimulates the growth of grasses (Ffolliott et. al.
1977, Lewis et al. 1982, Pearson et al. 1972, White 1983) and
may also benefit wildlife by increasing production of grass
seeds (Ahlgren and Ahlgren 1960). Buell and Cantlon (1953)
found that the herbaceous layer increases in cover with
increasing frequency of burning; much of the increase in cover
was contributed by grasses. Frequent burning causes the
development and maintenance of a comparatively lush
undergrowth of herbs, often with grasses as the dominant
species. Fire stimulates perennial herbs, grasses, and ferns
to root sucker and sprout vigorously. Fire also can stimulate
flowering, especially in monocots such as lillies and grasses
(Trabaud 1987).

There were detectable differences between treatments in
black cherry ground cover (Table 7). Separation of means
showed only a significant difference when comparing the 2- and

5-year treatments against the 10-year treatment and the

27

control, however. Coverage ranged from approximately 0.3% and
.5% in the control/10 year treatment to about 1.5% in the 2-
year/S-year treatments. This would indicate that black cherry
responds to more frequent burning intervals (2-year and 5-
year) than to longer rotations of fire or no fire at all.
Black cherry is one of the few woody species that is being
recruited in areas having 2-year and 5-year interval fires;
total stems per hectare for these two treatments is made up
mostly of black cherry stems. Black cherry stems per hectare
were also high in the control, but not nearly as important as
in the 2-year and 5-year treatments. Obviously, fire will
dictate species composition and importance. Seeds of fire-
adapted species can sprout after fire and compete effectively,
whereas in the control plots, these same species are
outcompeted for light, space, and nutrients.

Again, although there may be a trend, no detectable
differences existed between treatments in terms of Rub—us
coverage (Table 7). Looking back at Figure 3, however, it
would appear that burning increased.ggbu§ coverage. Coverage
was lowest in the control (2.8%) and reached.a high in the 10-
year burn treatment (9.5%). The fact that fire increased
abundance of 3% species, especially red raspberry, is
supported in the literature. Raspberry vegetatively sprouts
and fruits heavily after fire (Ahlgren 1979). Luppino (1984)
also found raspberry occurring more frequently and covering
more area in burned versus unburned areas. Red raspberry

typically increases dramatically after fire (as cited by

28

FEIS). In addition to vigorous sprouting, raspberry is also
capable of forming dense thickets after disturbance. Although
it ‘vigorously invades and. colonizes disturbed. sites, it
decreases as canopies close (as cited by FEIS). In addition,
seed may persist in the soil for many years until conditions
for germination are favorable. Most sprouting shrubs appear
to have great longevity owing to their extensive underground
parts (Abrahamson 1984).

Brackenfern was also a large component in many treatment
plots. Although there appears to be a trend in its
coverage, which is similar to that of Rubus, no significant
differences were detected between treatments. However, there
were differences between experimental blocks, which may have
masked the responses expected from brackenfern. This was most
likely due to data from Block B, in which virtually no
brackenfern was recorded in any of the plots. Looking back at
Figure 3, brackenfern coverage (although not significant) was
highest in the 10-year treatment (14%) , and lowest in the
control at 5 % coverage. This would suggest that brackenfern
responds to fire, a fact which is supported in the literature.
Brackenfern is known to be a competitive plant that invades
disturbed areas. Brackenfern, another species which
vegetatively reproduces, appears to require soil sterilized by
fire for spore germination (as cited by FEIS). Brackenfern is
considered a fire adapted species throughout the world (as
cited by FEIS) and repeated fires favor its growth. It’s

deeply buried rhizomes sprout vigorously after fires, before

29

most competing vegetation is established. In the burned
compartments, brackenfern was, other than grasses, the most
widespread species in the understory.

There were significant differences between treatments in
red pine cover (Table 7). This was especially true in
relation to frequency of the prescribed fires. A separation
of means test showed significant.differences between the 24and
S-year treatment. vs. the 10-year 'treatment and control.
Significant differences also existed between the 2-year
treatment and the 5-year treatment, but not between the 10-
year treatment and the control. Red pine coverage was lowest
in the 2-year treatments at less than 1%, and relatively
similar in other treatments at approximately 2% (Figure 3).
Frequent burns kill the small, unprotected red pine seedlings.
In fact, only a very small portion of these seedlings are
being recruited into the woody understory, and none at all
into the overstory. Woody stems per hectare was greatest in
the control plots. Burning of any kind seems to discourage
red pine recruitment, not regeneration. In fact, until a red
pine is approximately 50 years old, fire can be lethal (Rouse
1988). Although red pine can depend on fire for producing
mineral seedbeds necessary for regeneration, fires of more
than moderate intensity during the first 50 years would likely
destroy the whole stand (Van Wagner 1970). In addition to
differences between treatments, there were also differences
between experimental blocks. Red pine seedlings were highest

in Block B and lowest in Block C. This could be due to the

30

lower stocking density in Block B, and also to the fact that
fires in Blodk B burned hotter, thus creating more mineral
soil ideally suited for regeneration.

Other species which were tested for differences included
red maple, sugar maple (Age; saccharum), and hawkweed
(W) (Table 8). No significant differences
between treatments were found for any of these species.
Maples will be discussed extensively in the woody understory
results, but were not much of a factor in the ground
vegetation, representing greater than 1% coverage only in the
control plots.

Correctly handled, prescribed burning should benefit game
by increasing herbaceous growth (Little 1952). During the
first three post-fire growing seasons, vigorous growth of
herbs and shrubs can. be expected, especially aster and
raspberry (Ahlgren 1976). Ahlgren also stated that in a
Minnesota study herbs and shrubs of early post-fire years
gradually declined and that 13 years after fire, major plants
included the herbs big-leafed aster (Aster macropnyllus) ,
false lily-of—the-valley (Maianthemum canadense), and wild
sasparilla (Aralia nudicaulis). In addition, species with
seeds that are wind disseminated after fire germinated in soil
from burned areas only (Ahlgren 1979).

Repeated fires can substantially increase overall
understory richness (White 1983). Presumably, the continued
application of prescribed fire would favor the most vigorous

hardwood and shrub sprouters (Dickmann 1991). In addition,

31

Table 8. Species with. Greater than 1% Ground Coverage,
Averaged by Treatment

Two Year Burns % Coverage Five Year Burns % Coverage
1. Brackenfern 10.9 1. Grasses 12.7
2. Rubus 7.4 2. Brackenfern 6.8
3. Grasses 4.4 3. Rubus 6.0
4. Moss/Lichens 2.2 4. Hawkweed 2.8
5. Black cherry 1.6 5. Wild Saspirilla 2.7
6. Aster 1.5 6. Moss 2.0
7. Red pine 1.8
8. Black cherry 1.5
9. Strawberry 1.0

Ten Year Burns Control Plots

1. Grasses 16.9 1. Moss/Lichens 9.1
2. Brackenfern 14.0 2. Brackenfern 7.3
3. Rubus 9.1 3. Grasses 4.2
4. Moss/Lichens 4.3 4. Rubus 2.8
5. Red pine 1.7 5. Choke cherry 1.4
6. Hawkweed 1.5 6. Wild Sasparilla 1.4
7. Strawberry 1.5 7. Red pine 1.4
8. Bergamot 1.2 8. Hawkweed 1.3
9. Sugar maple 1.2

32

forage increases in underburned stands because burning
stimulates the growth of grasses and forbs (Ffolliott et al.
1977, Lewis et al. 1982). Other benefits to wildlife include
cover and increased production of fruit and seeds by grasses,
herbs, and shrubs (Ahlgren. and .Ahlgren 1960, Lewis and
Harshbarger 1986) . Burning under pine can also increase
quantity and nutritional value of browse and forage (Dickmann
1991). Rubus, herbs, grass, and sedges increase after
burning, causing an improvement in deer forage conditions.
Frequency of prescribed burns is also important. Two-
year burn intervals may be too soon because sprouts haven’t
recovered sufficiently to produce seed (Ahlgren 1979).
Indeed, the two-year burn intervals in this study (although
differences were not significant) had the lowest percent
ground cover. The highest percent ground covers, although
again results were not significant, were found in the 5-year
and 10-year treatments. This would seem to be supported by
the literature as cited earlier. The control plots also had
lower coverage, most likely due to greater competition and a
high percentage of mosses and lichens outcompeting other
species for water, nutrients, and space. In this sense,
burning also affects species composition and species
importance. For example, while mosses and lichens were
highest in the control.plots (9%), grasses were most important
in the 10-year and 5-year treatments, representing 17% and 13%
of total coverage, respectively. Fox (1986) reported that

sites burned twice in 12 years had significantly more plant

33
species, higher shrub density, and a greater cover than those
burned only once. In addition, the understory that had
experienced two fires in 12 years was significantly richer
than that which was burnt only once.

On post-fire lands, ashes often stimulate a lush, early
herb and shrub growth. Lemon (1949) has shown that survival
and increase of herbs under prescribed burning are related to
life form and life history of the species concerned ( as cited
by Buell and Cantlon 1953). Buell and Cantlon (1953) found
that when stands were burned at 3-year intervals or oftener,
cover by the shrub layer was reduced by as much as 50%. Two
to five burns during a 5-year period caused a reduction in.the
average height of shrubs by 30 - 40% in one study (Little and
Moore 1945). Little and Moore (1945) also reported few
changes following single burns; the effects largely
disappeared within the ensuing five years. Two annual burns
so reduced the shrub and humus layer that it no longer would
carry a fire. However, a 10-year burn interval may not be
frequent enough to ensure antabundant.herbaceous cover, due to
the buildup of woody vegetation, producing competition and
shade. Forbs could decrease in subsequent years as grass and
woody vegetation cover increases. Therefore, fire can be a.
dominant factor in controlling species composition and species
importance of the herbaceous understory, with fire frequency

playing a large role.

34

Woody Understory Density

Total stems per hectare was lowest in the 2-year
treatment at 210 stems/ha, and increased as time between
burning increased (Figure 4). The trend was nearly
exponential, with 385 stems per hectare in the 5 year-
treatments, 2069 in the 10-year treatments, and reaching an
average high of 4336 stems per hectare in the control plots.
There were significant differences in total stems per hectare
between treatments at an alpha level of 10% (Table 9).
Significant differences existed when comparing the 2- and 5-
year treatment against the 10-year treatment and the control.
This suggests a definite relationship between frequent burn
intervals (2 and 5-years), and longer burning intervals (10
years) or no burning at all. Significant differences were
also found. between the 2-year treatment and the 5-year
treatment, but not between the 10-year treatment and the
control.

Table 9 and Figure 5 further break down total stems per
hectare by treatment into the various size classes; 0 - 1.9
cm, 2 - 5.9 cm, and 6 - 9.9 cm respectively (0-0.75 in., 0.75-
2.3 in., and 2.3-3.9 in.). Total number of stems per hectare
was lowest in the 2-year treatment and reached a high in the
control. In addition, it appears that burning affected the
number of stems in each size class, with larger trees (6 - 9.9
cm) appearing mostly in the control plots. Little and Moore
(1945) also reported that two or more burns within a 5-year

period resulted in a net decrease of 18 - 51% in all

35

 

 

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41

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Figure 4. Total Stems per Hectare by Treatment

36

Table 9. Effects of Burning Interval on Density (stems/ha) of
the Woody Understory in a Mature Red Pine Stand.*

 

Diameter Size Burn Interval (years)
Class (cm) 2 5 10 control
All classes 209 a 385 b 2069 c 4336 c
(169) (166) (767) (1646)
0 - 1.9 181 a 283 b 1944 c 2907 c
(181) (193) (740) (1045)
2 - 5.9 6 a 79 b 79 b 1088 c
(6) (37) (54) (522)
6 - 9.9 23 a 23 a 45 b 340 c
(23) (23) (20) (142)

 

*: Means followed by the same letter are not significantly

different (p <= 0.2) using the orthogonal test. Standard
errors shown in parentheses.

37

 

 

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6-9.9 cm

 

 

 

 

 

3500

3000 L

8362580....

2-5.9 cm
size class

Q ’2 year burns ’5 year burns ’10 year burns E] control

 

Figure 5. Total Stems per Hectare by Size Class and

Treatment

38

reproduction. The loss of seedlings between 0.5 meters and
1.1 meters tall (1.6 and 3.5 feet) was approximately 95%, and
in those over 1.1 meters in height it was about 50%.

Significant differences at a 10% alpha level were found
between treatments when analyzing the 0 - 1.9 cm size class.
Again, the control had the largest number of stems in this
size class, at an average of 2908 per hectare, followed by
1944, 283, and 181 stems per hectare in the 10-year, 5-year,
and 2-year treatments, respectively. Obviously, the more
frequent the burning interval, the greater number of small
stems killed, and a lower number of stems per hectare. The
kill of small hardwoods by fire will depend on species and
diameter of trees, season of burning, heat of fire, and
frequency and interval of burning (Hodgkins 1958) . The
present data indicates that younger trees are more vulnerable
to fire than older ones.

Significant differences were found between treatments at
an error level of 1% in the 2 - 5.9 cm size class (Table 9).
As expected, total stems were highest in the control and
lowest in the 2-year treatment" Results were similar for both
the 5-year and 10-year treatments, both reporting 79 stems per
hectare. Only 6 stems per hectare in this size class were
found for the 2-year burns and 1088 stems per hectare in the
control or no burn plots. Differences were found between
frequent burns and infrequent or no burns, between one burn
and no burn at all (lo-year treatment vs. the control), and

also between 2-year burns and 5-year burns. Even one burn

39

significantly affected this size class, dropping the total
number of stems from 1088 in the control to 79 in the 10-year
treatment. Obviously, fewer stems are being recruited into
this size class as a direct result of fire.

Again, significant differences in total stems per hectare
were found between treatments in the 6 - 9.9 cm size class
(Table 9) . Total stems per hectare were highest in the
control plots at 340 stems per hectare, followed by 45, 23,
and 23 stems per hectare in the 10, 5, and 2-year treatments
respectively. Significant differences could only be detected
when comparing the 2- and 5-year treatments against the 10-
year treatment and the control, and in comparing the 10-year
treatment to the control. Therefore, larger size classes were
more affected by frequent fires than by infrequent or no fires
at all. The net effect of burning has been to reduce the
total number of stems available in each size class.

In addition to significant differences observed between
treatments, differences between experimental blocks probably
affected stocking of the woody understory. Disturbance from
logging may have affected understory density of the 6 - 9.9 cm
size class in Block B, accounting for its lower values. Block
C, with less overstory than Block A, had the most stems in
this size class for the 10-year treatment and the control.
Whereas no stems were recorded in this size class for the 2-
year and 5-year treatments in Blocks B and C, 68 per hectare
were found in Block A.

Burning affects total stems per hectare as well as total

4O

stems per hectare in various size classes. Frequent burns (2
and 5-year) kill mostly young, small stems primarily in the
2.5 - 10 cm size class (1-4"); larger trees appear undamaged
except for occassional basal bark injury (Niering 1970).
Hodgkins (1958) reported. similar’ findings for“ hardwoods;
prescribed fires top killed 62% of 2.5 centimeter trees, 52%
of 5 centimeter trees (2 inch), and 38% of 7-8 centimeter
trees (3 inch). In addition, Luppino (1984) reported that
saplings in burned areas were at browse level, while saplings
in unburned areas were forming an understory canopy that
further suppressed browse level.growthu Burning in this study
also limited the number of stems recruiting into the larger
size classes. Prescribed burns have restricted the total
number of stems to smaller size classes, making them more
available to wildlife. Frequency of burns also affected stems
per hectare; 2-year and 5-year burns were relatively void of
an understory as compared to the 10-year burns and control.
Many authors report that reproduction of hardwoods is more
dense on burned vs. unburned plots. Hodgkins (1958) reported
that new hardwood growth replaced original growth up to 1.8
meters in height (6 feet) after about three growing seasons;
the net effect of burning on total hardwood cover was simply

a reduction of its average height.

41

Species Richness - Woody Understory

Significant differences between treatments were found for
species richness, the total number of different woody species
(Table 10). A separation of means test showed significant
differences existed between all means tested. Species
richness was lowest in the 2-year burns (average = 2 species)
and increased to 5 species in the 5-year treatments, almost 8
in the 10-year treatments, to a high of nearly 12 species in
the control plots. Fire, therefore, has a definite impact on
the number of different species that may be found in a certain
burning regime. Frequent burns are considerably less rich
because very few species can tolerate and resprout following
a fire every two years. .As time between burns increases, more
species are able to grow in a given area, giving species which
are not normally thought of as fire adapted (such as white ash
(Fraxinus americana) or sugar maple) a chance to establish
themselves. This has important ramifications for wildlife,
leading to a more diverse and abundant food supply with a
longer fire rotation.

Species richness was further broken down into the three
size classes (Table 10). Significant differences existed
between treatments for the 0-1.9 cm size class at an error
level of 1%. An expected pattern developed, with the largest
number of species found in the control and the fewest in the
2-year treatments. Only an average of one species could be
found in the 2-year treatments, followed by four, eight, and

nearly 11 in the 5-year, 10-year, and control plots

42

Table 10. Effects of Burning Interval on Average Species
Richness (no. of species) in the Woody Understory of a Mature
Red Pine Stand.*

 

Diameter Size Burn Interval (years)

Class (cm) 2 5 10 control

All classes 2 a 5.3 b 7.7 c 11.8 d
(1.15) (.89) (.67) (1.6)

0 - 1.9 .67 a 3.67 b 7.67 c 10.5 d
(.67) (1.2) (.67) (1.3)

2 - 5.9 .33 a 2.33 b 2.33 b 7.67 C
(.33) (.89) (1.33) (.67)

6 - 9.9 1.3 a 1.0 a 2.0 b 4.67 c
(1.3) (1.0) (.58) (.89)

*: Means followed by the same letter are not significantly
different (p <= 0.2) using the orthogonal test. Standard
errors shown in parentheses.

43

respectively. This would seem to rule out 2-year burns as a
treatment alternative, with fire having such a huge effect
that only Block B had stems in this size class.

Fire's effect on species richness can be seen.through all
size classes. If only a small number of species are found in
the 0-1.9 cm size class, then an even smaller number will be
recruited into the next size class, 2-5.9 cm. Blocks B and C
did not have ANY stems in this size class for the 2—year
burns, leaving an average number of species of less than one
for 2-year burns (Table 10) . Both the 5-year and 10-year
treatments had an average of just over 2 different species,
but the control had nearly 8. Again, differences between
tested means are significant.

Upon analyzing the 6 - 9.9 cm size class, a different
story emerged (Table 10). Although there were significant
differences between treatments, the average number of species
found did not differ greatly between the 2-year, 5-year, and
10-year treatments. Significant differences existed when
comparing the 2- and 5-year treatment to the 10-year treatment
and the control. There are more species found in the latter
two treatments, with significant differences also existing
between the 10 year treatment and the control. Because the
differences between the three different burning intervals are
so small, fire apparently has stem killed mostly the smaller
size classes but has had less of an effect on the 6 - 9.9 cm
size class. In addition to treatment differences, block

differences may have affected.this size class” The effects of

44

logging have probably caused the low number of species in
Block B. In addition, only Block A had stems in plots burned
at 2-year and 5-year intervals for this size class. It would
be hard to draw further conclusions from these block
differences, although overstory stocking normally has a large

impact on understory composition.

Woody Understory Composition

Fire and fire frequencies have had an effect on species
composition (Figure 6). Significant differences in black
cherry density were found.between.treatments at an error level
of nearly 10% (Table 11). 'Total stems per hectare were lowest
in the 2-year treatment at 164 stems/hectare. Black cherry
stems/hectare increased to 215 in the 5-year treatment, 595 in
the 10-year treatment and.then.decreased to 306 in the control
plot. Although differences between the control plot and the
10-year treatment were not significant, there does appear to
be a trend. Fire has had a large impact on this species,
which is particularly evident when looking at Table 12.
Although total stems per hectare are greatest in the 10-year
treatment and the control, black cherry stems are :most
important in the 2-year and 5-year treatments where they
comprise well over half of the total stems reported. Black
cherry stems are second only to red maple in the 10-year
burns, but are not nearly as important in the control plots.

This suggests that this species responds to fire and is an

45

 

 

      

 

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400

m

control

m.
m a
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We
113
w
m
.m
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@ black cherry birch

Stems per Hectare by Treatment and Species

Figure 6.

46

Table 11. Effects of Burning Intervals on Density (stems/ha)

of Various Woody Understory Species in a Mature Red Pine
Stand.*

Burn Interval (years)

 

Species 2 5 10 control
Black cherry 164 a 215 b 595 c 306 c
(164) (173) (243) (49)
Red maple 0 a 23 b 612 c 1661 c
(0) (15) (446) (1415)
Birch 28 a 51 a 17 a 28 a
(15) (29) (17) (20)
White ash 6 a 28 b 85 c 340 d
(6) (15) (45) (158)
Beech 6 a 0 b 142 c 159 c
(6) (0) (60) (99)
Aspen 6 a 6 a 57 a 45 a
(6) (6) (34.5) (37)
Choke cherry 0 a 23 b 442 c 538 c
(0) (15) (214) (253)

 

*: Means followed by the same letter are not significantly
different (p <= 0.2) using the orthogonal test. Standard
errors shown in parentheses.

47

Table 12. Ranking of Species Importance, Averaged by
Treatment

TWO YOII Burns

1.
2.
3.
4.
5.

Ten

2.
3.
4.
5.
6.
7.
8.
9.
10.
11.

Black cherry
Birch

Aspen

White ash
Beech

YOII Burns

Red maple
Black cherry
Choke cherry
Beech

White ash
Aspen
Ironwood
Sugar Maple
White oak
Red oak
Birch

Stems/ha

164
28
6

6

6

Stems/ha

612
595
442
142
85
57
40
34
28
17
17

Five Year Burns

1.
2.
3.
4.
5.
6.
7.
8.
9.
10.

Black cherry
Birch

White ash
Red maple
Choke cherry
Red pine
Aspen

Red oak
White oak
White pine

Control Plots

1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
13.
14.
15.
16.
17.

Red maple
Sugar maple
Choke cherry
White ash
Black cherry
White pine
Beech
Ironwood

Red pine
Amelanchier
Aspen

Birch

Red oak
Balsam fir
Basswood
White oak
Jack pine

Stems/ha

215
51
28
23
23
23

O\O\O\O\

Stems/ha

1661
675
538
340
306
232
159
156

77
65
45
28
23
17
6
6
3

48

opportunist occupying bare areas free from competition. This
species has hard-coated seeds which are capable of surviving
in the forest floor and springing up after fire.

Significant differences in red maple density were found
between treatments (Table 11), especially when plotting
frequent fires (2-year and 5- year rotations) against less
frequent fires or no fire at all. There does appear to be a
trend; red maple follows an exponential curve, starting with
a low of 0 stems per hectare in the 2-year plots and
increasing to 23, 612, and 1661 stems in the 5-year, 10-year,
and control plots respectively. Obviously, fire frequency has
a big impact on the number of red maple stems. The 2-year
interval was too frequent and, therefore, lethal to red maple
stems. However, red maple was the most important species in
the 10-year treatment, and the control (Figure 6, Table 12).
It was also one of the ten species found in the 5-year
treatments.

Red maple is a moderately tolerant species, capable of
dominance in.the absence of fire. IHowever, it is also capable
of responding to fire, provided fire frequency is not too
high. Although temporarily set back by fire, red maple comes
back strong after one or two growing seasons. Red.maple is an
example of a species capable of sprouting from roots or
portions of the stem left unkilled by the fire. Red maple’s
sprouting abilities and subsequent attractiveness as browse to
wildlife has been documented extensively in the literature.

For example, Fowells (1965) reported that fire-killed red

49

maple trees sprout vigorously, and the species may become a
more important stand component after a fire than it was
before. Red maple may also suffer when large populations of
deer are present, as it is a preferred deer food (Fowells
1965).

No significant differences were found in birch (Betula
W) stems per hectare (Table 11) . Although birch
stems were found across all treatments, they appeared to be of
much greater importance in the 2-year and 5-year treatments
(Table 12), especially in the smaller size classes. Birch is
an example of a pioneer species with light seeds which are
disseminated by wind from adjacent areas. There were also
differences between blocks, with no birch reported in Block C.
This may suggest that the composition of the post-fire stand
will depend upon the relative supply of wind-disseminated seed
for species such as birches and aspens (Populus trgmuloides
and P. grandidentata), or bird-disseminated seed as for the
cherries (Barnes and Spurr 1973).

Significant differences in white ash density were
observed between treatments at an alpha level of 5% (Table
11). Total stems per hectare rose from a low of 6 in the 2-
year treatment to 28, 85, and 340 stems per hectare in the 5-
year, 10-year and control plots, respectively. White ash
stems are much more important in the control plots, making up
a larger part of total stems per hectare than in other
treatments. This is also true of the 10-year treatment as

compared to the 2- year and 5-year treatments. White ash

50

stems were found in all three size classes in all treatments
except the 2-year burns. Only white ash stems in the 6-9.9 cm
size class were found in the 2-year treatments Thus, frequent
fires kill mostly smaller stems and have altered recruitment
and species composition of white ash. White ash is able to
increase in importance with increasing time between fires; it
is an example of a species which is killed by fire and mostly
recovers by seeding. In addition to significant differences
between treatments, differences between experimental blocks
also existed. Blocks B and C had relatively fewer stems of
white ash than did Block A. Block C had a large shrub cover,
under which the moderately tolerant ash could not establish
itself. Block B had experienced disturbance in the form of
logging which may have eliminated the white ash understory.

Beech (Fagus grangifglia) followed a similar trend as
that of white ash, except that virtually no stems were found
in the 2-year and 5-year treatments. Beech was adversely
affected by frequent fires, and unable to:re-establish itself,
although it is capable of sprouting. Given more time between
fires, this tolerant species is able to revive in importance
(Table 12).

.A huge difference between treatments existed in sugar
maple density. Sugar maple, a poor sprouter, was non-existent
in the 2-year and 5-year treatments, fairly unimportant in the
10- year treatment, and very important in the control plots.
There, it was second in total number of stems only to red

maple. The largest number of stems per hectare in the 10-year

51

treatment existed in the 6-9.9 cm size class, once again
suggesting that fire kills mostly smaller sized trees. Fire
has seriously affected the composition and abundance of this
species.

Another species adversely affected by fire in much the
same way as sugar maple was red pine. No stems of this
species were reported in either the 2-year or 10-year
treatments, and only a small number were found in the 5-year
treatments. Red pine is not recruiting from seedlings less
than 1.5 meters in height to seedlings.greater than 1.5 meters
in height except in the control areas. Fire is necessary to
promote a mineral seedbed for red pine germination, but is
destructive to the small, thin barked trees until
approximately 50 years of age.

Amelanchier was only present in the control plots and was
destroyed easily by fire of any sort or frequency. White
(1983) also reported finding Amelanchier in unburned areas
only, and that it may be adversely affected by fire.

Aspen seemed to be effected by frequent fires (Table 11) .
However, the differences between treatments were
insignificant. While adversely affected by frequent fires,
aspen responded to fires of longer rotation. Aspen is a
pioneer species, which readily occupies bare land. In
addition, it suckers profusely and is known to increase after
fire (Fowells 1965). However, differences between
experimental blocks may have masked the expected response in

this case. iBlock.B, recently logged, contained no aspen stems

52

at all and Block C only had aspen stems in the 10-year and
control plots.

Differences between treatments in choke cherry (Eggggg
Virginiana) density were significant at the 5% error
level (Table 11). Stems per hectare went from a low of 0 in
the 2-year treatments to 23, 442, and 538 in the 5-year, 10-
year, and control plots, respectively. Frequent fires,
especially at 2—year intervals, have diminished the abundance
of this species. Choke cherry responded.to fire at longer burn
intervals, increasing in importance from the 5-year to the 10-
year treatment. It is one of the few species which is fairly
important in the burning treatments and in the control plots.
It represents a large percentage of total stems per hectare of
the control plots (Table 12). It comes in after fire as seen
by its representation in the smaller size classes. Choke
cherry is an example of a species which reproduces
vegetatively and sexually. It is also known to be well
adapted to disturbance by fire. It is thought to be
moderately resistant to fire mortality, and although easily
top killed, plants resprout vigorously following most burning
(as cited by FEIS).

Species have adaptations to different fire frequencies.
In general, the distribution of plants on burned and unburned
land is dependent on. the type of :reproduction, whether
vegetative or by seed, the extent to which vegetative parts
are heat tolerant, and the extent to which the species are

able to compete.in the opening created.by fire (Ahlgren 1964).

53

Ahlgren (1964) found that vegetatively reproduced species were
more frequently dominant components of burned lands. The
dominant species of more frequently burned associations
recover by sprouting or resist fire. Dominants of less
frequently burned areas that are killed by fire can also
recover by seeding.

Fire kills most or all of the plant above the soil
surface; succeeding vegetation tends to be made up of light-
seeded species that can move in from outside the burned areas,
species with perennial root systems capable of sending up new
sprouts, and species with dormant seeds buried in the forest
floor that are stimulated by heat (Barnes and Spurr 1973) .
Species sprout quickly after losing their above ground parts
to fire, recovering their pre-burn dominance levels in 2-3
years (Abrahamson 1984) . Plants that survive fire and
regenerate vegetatively have a root system ready to utilize
nutrient flushes from fire (Trabaud 1987). New shoots grow
fast with an established root system to nourish them.
Individual species responses vary considerably, but the
majority of woody species, such as aspen, red oak (Qu_e_r_gy_s_
Ma) , and red maple, are sprouters rather than seeders.
Other species exhibit a sit-and-wait strategy and can be
released by fire when dead litter and grasses are consumed.
Others, such as black cherry, will utilize a buried seed
strategy. Vegetative reproduction is an important recovery
mechanism when fires are too frequent to permit seed

production. Repeated fires not only kill back the woody

54

understory, but they also cause shifts in its composition.
Sprouting varies by species with, for example, red maple
intermediate and sugar maple low in this sense (Dickmann
1991). Stem kill of certain smaller trees and shrubs is
limited.to the more fire sensitive tree species (Niering et al
1970).

Fire frequency has a large impact on species composition
and abundance, with fewer species present in more frequently
burned areas“ Trabaud (1987) found that in.plots burned every
other year, the amount of seed buried in the soil
progressively decreased, resulting in fewer individuals
present. Where fires occur too frequently, species disappear.
Fox (1986) found that of species present only on single-fire
(12-year fire rotation) plots, all were obligate seedling
regenerators, while the larger number of species found only on
twice burned plots were mostly vegetative regenerators.

The results have implications for vegetation managers;
areas burned too frequently may lose obligate seedling
regenerators, while an area remaining unburnt for too long may
lose some vegetative regenerating species, as well as short-
lived obligate seedling regenerators (Fox 1986). The
inference is that some species require longer than 6 years to
establish an adequate seed reserve either on the plant or in
the soil seed bank. Fox (1986) found that fires every 6 years
were too frequent, while fires. every' 12 years 'were :not
frequent enough.

The data indicates that the frequency of prescribed

55
burning has a marked effect on the lower vegetation layers.
However, there is not a uniform reduction in all species. A
shift in the relative importance of species can be found with
increased burning frequency, also leading to shifts in species
dominance.

A good summary was provided by Hodgkins (1958) of
prescribed burning effects in loblolly pine stands:

1. Thin-barked species are more susceptible to fire
killing and damage than are thick-barked species.

2. Late spring or early summer fires have the greatest
weakening effect on understory hardwoods.

3. Hotter fires top-kill the larger hardwoods.

4. Any reduction of hardwoods with a single fire is
usually temporary, and the net result after a few years is
often an increased coverage of hardwoods. The burning
influence appeared to last about 3 years.

5. After 6 years, the amount of hardwood cover in the
0.3 - 1.2 meter (1 - 4 feet) height class was greater on the
burn than on the control.

6. Species, such as red maple, may receive a temporary
setback as the result of fires, but will again show greater

stimulation after one or two growing seasons.

CONCLUSIONS AND RECOMMENDATIONS

The specific objectives addressed in this study were 1)
the quantification of the herbaceous and woody understory
composition in once thinned red pine stands, 2) the assessment
of the effects of spring' prescribed fires on overstory
conditions and understory composition and development, and 3)
the assessment of the effects of repeated prescribed burns at
2, 5, and 10-year intervals on understory composition and
development as compared to no burning at all. The feasibility
of burning will depend on various factors, including weather
conditions, public opinion, and experienced personnel.
Conclusions and recommendations regarding wildlife and
recreation were based upon.personal observations, as specific
effects on these values were not quantified.

Results of this study affirmed several of the hypotheses
stated in the introduction of this report. Thinning red pine
stands on good soils stimulated the development of a diverse
and extensive woody and herbaceous understory. This was
evident in the control plots, in which a rich and extensive
understory developed. in. response: to the opening of the
overstory canopy. Few adverse effects were observed on the
pine overstory, but the effects of burning on the herbaceous
and woody understory varied with fire frequencies.

Repeated burns at short intervals, as in the 2-year and
5-year treatments, did not significantly affect herbaceous

cover or specieszrichness, but.did.affect.species composition.

56

57

Frequent fires did significantly affect the extent and
diversity of the woody understory, which was virtually
eliminated. Most species were eliminated because they had
insufficient time in which to recover and respond to the fire
before another burn was set. Those species which did respond
exhibited different survival characteristics, including
sprouting and buried seed strategies.

Burning at long intervals, as in the 10-year treatments,
also had no effect on herbaceous cover or species richness.
Only species composition was altered in this stratum. A
longer fire rotation temporarily set back the development of
the woody understory, immediately following the burn.
However, with increased growing time between fires, a vigorous
and extensive understory developed which could be used by
wildlife. Burning at longer intervals resulted in an
increasingly rich and abundant food supply as compared to the
frequent burning intervals. Species composition was altered,
with sprouters most prominent. In addition, stems reached a
greater size and, thus, become better parents for sprouting.
Given a longer time between.burns, more species had sufficient
time to re—establish themselves.

Prescribed burning, at longer intervals, can be used to
benefit wildlife by stimulating herbaceous and woody species
useful in wildlife management. The 10-year treatments in this
study provided a diverse and extensive understory which could
be utilized by wildlife. Accessibility for humans and

wildlife, in my opinion, were also better on the 10-year plots

58

as compared to the controls. Burning at longer intervals,
between five and 10 years, was most appropriate for meeting
timber, wildlife, and recreation objectives in this study.
The Lake States are rich with red pine plantations.
Management of the many hectares of mature red pine which
already exist could include wildlife, recreation, and timber
objectives, depending on what the values of society dictate.
These data indicate that heavy thinning, combined with
burning, controls the density and composition of the
understory resulting in improved access and an abundant food
supply for wildlife. In addition, large diameter trees were
produced in an aesthetically' pleasing stand. Fire can
continue to be used as a management tool when its effects are
known to be beneficial. With successful results in
experimental areas and elsewhere, this practice can become

operational in the Lake State forests, too.

APPENDIX

APPENDIX

Completed ANOVA's for Entire Study

Table 13. Total Percent Cover of Herbaceous Vegetation by
Burning Interval and Block.

Burning Interval

 

2 years 5 years 10 years control
Block I"??? """" I???” 69.5 " _ 34.0 "'
Block B 35.0 19.7 29.2 24.0
Block C 51.3 60.4 69.0 47.8
Average};§"§;;"'"'"ZSTZ"""“"EZB """""" 3' 5'3""
Std. error 8.7 12.0 13.4 6.8

ANOVA of arcsin transformed data

Source d.f. S.S. M.S. F.
Total 11 1252.49

Block 2 641.76 320.88

Tmt. 3 290.55 96.85 1.82-NS
Error 6 320.18 53.36

I
2
U)

ll

Not Significant

59

60

Table 14. Species Richness of Herbaceous Vegetation by
Burning Interval and Block

Burning Interval

2 years 5 years 10 years control
Block A 16 26 22 26
Block B 24 12 19 15
Block C 23 19 28 25
Average 21 19 23 22
Standard Err. 2.52 4.04 2.65 3.51
ANOVA
Source d.f. S.S. M.S. F.
Total 11 278.25
Block 2 87.50 43.75
Tmt. 3 26.25 8.75 .32-NS
Error 6 164.50 27.42

61

Table 15. Total Percent Ground Cover of Mosses and Lichens by

Burning Interval and Block

Burning Interval

10 years

control

2 years 5 years
Block A 1.4 3.6
Block B 3.0 0.3
Block C 2.3 2.2
Average(%) 2.2 2.0
Std. error .46 .96

Source d.f. 8.8.

Total 11 253.61
Block 2 .62
Tmt. 3 178.80
Error 6 74.19

* = significant at 5%

SEPARATION OF MEANS TEST

1. 2,5 vs. 10,control
3.2 Significant at .02

2. 10 vs. control
t= 2.01 Significant at .10

3. 2 vs. 5
t= .39 Not Significant

62

Table 16. Total Percent Ground Cover of Grasses by Burning

Interval and Block

Burning Interval

 

 

2 years 5 years 10 years control
Block A 0.8 6.5 34.3 4.3
Block B 2.9 7.7 5.4 1.4
Block C 9.4 23.8 10.9 5.6
Average(%) 4.4 12.7 16.9 3.8
Std. error 2.6 5.6 8.9 1.2 4
ANOVA of arcsin transformed data
Source d.f. S.S. M.S. F.
Total 11 852.9
Block 2 146.9 73.44
Tmt. 3 346.99 115.66 1.93-NS
Error 6 359 59.83

 

63

Table 17. Total Percent Ground Cover of Black Cherry by

Burning Interval and Block

Burning Interval

2 years 5 years 10 years
Block A """STS""""ZS’""""BTE""
Block B 1.8 1.1 0.1
Block C 0.83 1.4 0.17
Aver...(41"'17?""""ITE"""'”"32""
Std. error .41 .26 .12

ANOVA of arcsin transformed data

Source d.f. S.S. M.S.
Total 11 61.69

Block 2 4.44 2.22
Tmt. 3 44.64 14.88
Error 6 12.61 2.10

* = significant at 5%

SEPARATION OF MEANS TEST

1. 2,5 vs. 10,control

t= 4.52 Significant at .01
2. 10 vs. control

t= .9 Not significant

3. 2 vs. 5

t= .12 Not Significant

control

mu—w-'

64

Table 18. Total Percent Ground Cover of Rubus Spp. by Burning

Interval and Block

Burning Interval

control

2 years
Block A 1.3
Block B 13.1
Block C 7.8
Average(%) 7.4
Std. error 3.4

5 years 10 years
5.5 19.4
3.3 3.6
9.2 5.5

6 9.5
1.7 5.0
SOS. M.S.

355.88

.34 .17
83.50 27.8
272.00 45.0

I
2
U)

ll

not significant

65

Table 19. Total Percent.Ground.Cover of Brackenfern.by Burning
Interval and Block

Burning Interval

2 years 5 years 10 years control
Block A '"'1'32""""‘ISTS""""'IT§""""mITS """"
Block B 0 0 4.2 0
Block C 19.2 7.5 36.7 13.8
Average(a.i"'133""""ETE""""IZTI"""m"; """""
Std. error 5.7 3.8 11.3 4.4

ANOVA of arcsin transformed values

Source d.f. S.S. M.S. F.
Total 11 1562.43

Block 2 993.53 496.77

Tmt. 3 142.81 47.60 .67-NS
Error 6 426.09 71.02

-NS = not significant

66

Table 20. Total Percent Ground Cover of Red Pine by Burning

Interval and Block

Burning Interval

 

 

2 years 5 years 10 years control
Block A 0.1 0.6 0.9 1.0
Block B 1.6 4.4 3.4 3.2
Block C 0 0.3 0.75 0.6
Average(%) .6 1.8 1.7 1.6
Std. error .5 1.3 .86 .8
ANOVA of arcsin transformed data
Source d.f. S.S. M.S. F.
Total 11 146.75
Block 2 110.02 55.01
Tmt. 3 32.32 10.77 14.55*
Error 6 4.41 .74

* = significant at 1%

SEPARATION OF MEANS TEST

1. 2,5 vs. 10,control
t=4.28 Significant at .01

2. 10 vs. control

t= .20 Not significant
3. 2 vs. 5

t=5 Significant at .01

67

Table 21. Total Stems per Hectare by Burning Interval and
Block.

Burn Interval

2 years 5 years 10 years control
Block A ’"’"EE""""'2§3"""'§I§3'" ""2225 """"
Block B 544 714 578 1343
Block C 0 187 2500 7022
Average “"35"”"“;;;"‘““;;;; """" Z352 """""
Std. error 169 165.5 767 1646.5

ANOVA of transformed data

Source d.f. S.S. M.S. F.
Total 11 62.15

Block 2 3.44 1.72

Tmt. 3 37.00 12.33 3.41*
Error 6 21.71 3.62

* Significant at 10%

SEPARATION OF MEANS

1. 2 year, 5 year vs. 10 year, control treatments
t = 2.83
Significant at .05

2. 10 year vs. control treatment
t = .49
Not significant

3. 2 year vs. 5 year treatment
t = 1.42
Significant at .20

68

Table 22. Total Stems per Hectare by Burning Interval and
Block, 0 - 1.9 cm

Burning Interval

2 years 5 years 10 years control
Block A ""3""""‘SZ"""""SSEI"""'"SZEETE""
Block B 544 663 544 884
Block C 0 153 2227 4370
Average "'IEI"""";§§ """""" I §Z4""""'3339T3""
Std. error 181 193 740 1044.7

ANOVA of transformed data

Source d.f. S.S. M.S. F.
Total 11 94.97

Block 2 5.20 2.6

Tmt. 3 61.02 20.34 4.25*
Error 6 28.75 4.79

*significant at 10%

SEPARATION OF MEANS

1. 2 year, 5 year vs. 10 year, control treatments
t = 3.16
Significant at .02

2. 10 year vs. control treatment
t = .24
Not significant

3 2 year vs. 5 year treatment
t = 1.64
Significant at .20

69

Table 23. Total Stems per Hectare by Burning Interval and
Block, 2 - 5.9 cm.

Burn Interval

2 years 5 years 10 years control
Black A '“""1;"“““‘;;;““““";;"““';'a'; """
Block B 0 51 17 391
Block C o 34 187 2108.6
Average "”33 """"" §§"""""§3“""§3§£ """
Std. error 5.7 37 54 521.5

Source d.f. S.S. M.S. F.
Total 11 61.61

Block 2 3.70 1.85

Tmt. 3 50.51 16.84 13.7*
Error 6 7.40 1.23

*significant at 1%

SEPARATION OF MEANS

1. 2 year, 5 year vs. 10 year, control treatments
t = 16.51
Significant at .01

2. 10 year vs. control treatment
t = 3.15
Significant at .02

3. 2 year vs. 5 year treatment
t = 3.56
Significant at .02

70

Table 24. Total Stems per Hectare by Burning Interval and
Block, 6 - 9.9 cm

Burning Interval

 

2 years 5 years 10 years control
Block A ""23"""""23"""""§Z""""""ZS§ """
Block B 0 0 17 68
Block C 0 0 85 544
Average "23""""""3§'= ’ 45 340
Std. error 23 23 20 142

ANOVA of transformed data

Source d.f. S.S. M.S. F.
Total 11 62.92

Block 2 15.43 7.72

Tmt. 3 35.32 11.77 5.8**
Error 6 12.17 2.03

**Significant at 5%

SEPARATION OF MEANS TEST

1. 2 year, 5 year vs. 10 year, control treatments
t = 3.84
Significant at .01

2. 10 year vs. control treatment
t = 1.62
Significant at .20

3. 2 year vs. 5 year treatment
t = 0
Not significant

71

Table 25. Species Richness in the Woody Understory by Burning
Interval and Block

Burning Interval

2 year 5 year 10 year Control
Block A 4 5 9 15
Block B 2 7 7 10
Block C O 4 7 10.5
Average 2 5.3 7.7 11.8
Std. error 1.2 .90 .70 1.6
ANOVA
Source d.f SS MS F
Total 11 184.25
Block 2 16.8 8.4
Treatment 3 153.75 51.25 22.48**
Error 6 13.7 2.28

**Significant at 1%

SEPARATION OF MEANS

1. 2 year,5 year vs. 10 year, control treatments
t = 6.97
Significant at .01

2. 10 year vs. control treatment
t = 3.38
Significant at .02

3. 2 year vs. 5 year treatment
t = 2.7
Significant at .05

72

Table 26. Species Richness in the Woody Understory by Burning
Interval and Block, 0-1.9cm

Burning Interval

2 year 5 year 10 year Control
Block A 0 2 9 13
Block B 2 6 7 9
Block C 0 3 7 9.5
Average .7 3.7 7.7 10.5
Std. error .7 1.2 .7 1.3
ANOVA
Source d.f SS MS F
Total 11 192.56
Block 2 3.37 1.69
Treatment 3 169.06 56.35 16.77 *
Error 6 20.13 3.36

**Significant at 1%

SEPARATION OF MEANS

1. 2 year,5 year vs. 10 year, control treatments
t = 6.54
Significant at .01

2. 10 year vs. control treatment
t = 1.89
Significant at .20

3. 2 year vs. 5 year treatment
t = 2.0
Significant at .10

 

 

73

Table 27. Species Richness in the Woody Understory by Burning
Interval and Block, 2-5.9 cm

Burning Interval

2 year 5 year 10 year Control
Block A 1 4 1 9
Block B 0 1 1 7
Block C o 2 5 7
Average .33 2.33 2.33 7.67
Std. error .33 .89 1.33 .67
ANOVA
Source d.f SS MS F
Total 11 107.7
Block 2 5.2 2.6
Treatment 3 89.03 29.68 13.19 *
Error 6 13.47 2.25

*Significant at 1%

SEPARATION OF MEANS

1. 2 year,5 year vs. 10 year, control treatments
t = 4.23
Significant at .01

2. 10 year vs. control treatment
t = 4.35
Significant at .01

3. 2 year vs. 5 year treatment
t = 1.63
Significant at .20

74

Table 28. Species Richness in the Woody Understory by Burning
Interval and Block, 6-9.9cm

Burning Interval

2 year 5 year 10 year Control
Block A 4 3 2 6
Block B 0 0 1 3
Block C 0 0 3 5
Average 1.3 1 2 4.7
Std. error 1.3 1 .6 .9
ANOVA
Source d.f SS MS F
Total 11 48.25
Block 2 15.5 7.75
Treatment 3 24.92 8.31 6.34*
Error 6 7.83 1.31

*significant at 5%

SEPARATION OF MEANS

1. 2 year,5 year vs. 10 year, control treatments
t = 3.28
Significant at .02

2. 10 year vs. control treatment
t = 2.85
Significant at .05

3. 2 year vs. 5 year treatment
t = .36
Not Significant

75

Table 29. Total Stems per Hectare of Black Cherry by Burning
Interval and Block

Burning Interval

2 year 5 year 10 year Control
Black A ""3"""m32 """" ZZS'mméEl' "
Block B 493 561 272 391
Block C 0 51 1071 306
Average "'12; """"" 213""""333""'"§32""
Std. error 164 173 243 49

ANOVA of transformed data

Source d.f SS MS F
Total 11 61.96

Block 2 11.56 5.78

Treatment 3 30.78 10.26 3.14 *
Error 6 19.62 3.27

**Significant at almost 10%

SEPARATION OF MEANS

1. 2 year,5 year vs. 10 year, control treatments
t = 2.52
Significant at .05

2. 10 year vs. control treatment
t = .36
Not Significant

3. 2 year vs. 5 year treatment
t = 1.72
Significant at .20

76

Table 30. Total Stems per Hectare of Red Maple by Burning
Interval and Block

Burning Interval

2 year 5 year 10 year Control
Alger A "'3"""""§I"""IZ§2T§"""15""
Block B 0 17 68 340
Block C 0 0 272 4489.5
Average ""3"”""’;§""""'EIS""'"IEEI"'
Std. error 0 15 446 1415

ANOVA of transformed data

Source d.f SS MS F
Total 11 100.56

Block 2 1.50 .75
Treatment 3 81.14 27.05 9.04 *
Error 6 17.92 2.99

**Significant at 5%

SEPARATION OF MEANS

1. 2 year,5 year vs. 10 year, control treatments
t = 4093
Significant at .01

2. 10 year vs. control treatment
t = .51
Not Significant

3. 2 year vs. 5 year treatment
t = 1.61
Significant at .20

77

Table 31. Total Stems per Hectare of.Birch.by Burning Interval
and Block

Burning Interval

2 year 5 year 10 year Control
Alger A '""3Z"'"'"ZSE""""§I’""""17"
Block B 51 51 0 68
Block C 0 o 0 0
Average ----28----------5I--------I7----------28---
Std. error 15 29 17 20

ANOVA of transformed data

Source d.f SS MS F
Total 11 45.66

Block 2 31.75 15.88

Treatment 3 3.96 1.32 .80 NS
Error 6 9.95 1.66

NS = Not Significant

78

Table 32. Total Stems per Hectare of White Ash by Burning
Interval and Block

Burning Interval

2 year 5 year 10 year Control
Block A ""I;""""'§I“"""Z§B'"""EZE
Block B 0 34 17 119
Block C 0 0 68 255
Average '""5"""'"SE""""§E""""318 """
Std. error 5.7 15 45 158

ANOVA of transformed data

Source d.f SS MS F
Total 11 55.07

Block 2 10.78 5.39

Treatment 3 36.07 12.02 8.77*
Error 6 8.22 1.37

*significant at 5%

SEPARATION OF MEANS

1. 2 year,5 year vs. 10 year, control treatments
t = 4.61
Significant at .01

2. 10 year vs. control treatment
t = 1.59
Significant at .20

3. 2 year vs. 5 year treatment
t = 1061
Significant at .20

79

Table 33. Total Stems per Hectare of Beech by Burning Interval
and Block
Burning Interval

2 year 5 year 10 year Control
Block A '"’1'?""""3’""""ZZE""""§§?"
Block B 0 0 51 51
Block C 0 0 255 68
Average '"1'77"m""3"""'"IZE""""IE3""
Std. error 5.7 0 60 99

ANOVA of transformed data

Source d.f SS MS F
Total 11 64.44

Block 2 4.15 2.08

Treatment 3 55.42 18.47 22.50 *
Error 6 4.87 .82

* Significant at 1%

SEPARATION OF MEANS

1. 2 year,5 year vs. 10 year, control treatments
t = 8.12
Significant at .01

2. 10 year vs. control treatment
t = .10
Not Significant

3. 2 year vs. 5 year treatment
t = 2.56
Significant at .05

80

Table 34. Total Stems per Hectare of Aspen by Burning Interval
and Block

Burning Interval

2 year 5 year 10 year Control
araer A "'17""""I§""""'EI""""IIE'"
Block B 0 0 0 0
Block C 0 0 119 17
Average "'3T;"'""";T§"""";§ """"" 4'3""
Std. error 5.7 5.7 34.5 37

Source d.f 88 MS F
Total 11 45.48

Block 2 26.38 13.19

Treatment 3 9.62 3.21 2.03 NS
Error 6 9.48 1.58

NS = Not Significant

81

Table 35. Total Stems per Hectare of Choke Cherry by Burning
Interval and Block

Burning Interval

2 year 5 year 10 year Control
Block A ""3"”""""3"""'23§"""'22§""
Block B 0 17 17 51
Block C 0 51 612 901
Average ----0-----------23-------442-------538 -----
Std. error 0 15 214 253

ANOVA of transformed data

Source d.f SS MS F
Total 11 87.52

Block 2 6.95 3.48

Treatment 3 65.63 21.88 8.78 *
Error 6 14.94 2.49

* Significant at 5%

SEPARATION OF MEANS

1. 2 year,5 year vs. 10 year, control treatments
t = 4.81
Significant at .01

2. 10 year vs. control treatment
t = .36
Not Significant

3. 2 year vs. 5 year treatment
t = 1.77
Significant at .20

LI ST OF REFERENCES

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84

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