A POPULATION SURVEY OF THE RING-NECKED
PHEASANT IN MICHIGAN

Thesis for the Degree of Ph. D.
MICHIGAN STATE UNIVERSITY
RALPH AUSTIN MacMULLAN
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This is to certify that the

thesis entitled
A Population Survey of the Ring-necked

Pheasant in Michigan

presented by

Ralph A. MacMullan

has been accepted towards fulfillment
of the requirements for

 

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2/17 203 Blue FORN S/DateDueForms_2017.indd — p95

A POPULATION SURVEY OF THE RING-NECKED PHEASANT IN MICHIGAN

BY

Ralph Anitin Macttullan

AN ABSTRACT
Submitted to the School for Advanced Graduate Studiea of
Michigan State Univeraity of Agriculture and
Applied Science in partial fulfillment of
the requirement. for the degree of

motor or PHILOSOPHY

Deparmnent of Zoology

1960

e 7' ; M-
Approved #:‘z—K s11) e. I /U 4(( n Cg_‘
7 ./

ABSTRACT

This study of Michigan's pheasants from the standpoint of popu-
lation dynamics had three objectives--(l) to reconstruct a history of
past populations, (2) to acquire information on current population
levels, and (3) to devise better sampling methods, when needed, for
obtaining that information. The study was made chiefly during the
years 1947-1950, but data were collected each year thereafter through
1956. The work was sponsored by Federal Aid in Wildlife Restoration
Project, Michigan 38-R.

Although a number of private releases were made beginning in
1895, pheasants were not established until after 1918 when the State
began a release program. Pheasants were well established by the early
1920's and the first pheasant open season for hunting was held in 1925.
Reports from hunters were the best source of information prior to this
study. The State's computed kill based on compulsory hunter reports
was determined to be a good index to fall populations.

Pheasant distribution is outlined, and a correlation with land
and soil formations described. Five study areas were selected. Each
had a distinctive pheasant population and land formation, and in
total comprised about three-quarters of the primary pheasant range.

Data were collected from extensive surveys made by sportsmen,

farmers, biologists, rural mail carriers, and conservation officers.

ii

Roadside surveys by the mail carriers and conservation officers were
most useful, and coaplemented each other. The approximately 500 car-
riers who regularly cooperated provided good volume of data, but
could be asked only infrequently to make surveys. The officers (about
55 in pheasant range) did not provide as large a volume of data, but
could! be asked to record observations over long periods to determine
the effect of phenology on surveys.

Surveys were made during the four seasons. Data were recorded
by county units, and examined by tabulations for study areas.

Mag-firowing-cock counts, self-adjusting for phenology, were
considered the most reliable for spring cock population estimates.
Carriers' spring surveys of both pheasant density and sex ratio were
sensitive to phenological differences. As the days progressed in mid-
April, observed density increased. The carriers' counts were cor-
related to crowing-cock counts, suggesting a method for adjusting
counts for phenology. Sex ratios obtained from observations of harems
may be more nearly true than those obtained from all observations.

Munrood density indices increased as the sunner progressed
from early June to mid-August, at a predictable rate, permitting
adjustment for timing of brood counts. Sumner brood counts by carriers
showed an excellent correlation with fall kill. Pram the former, kill
could have been predicted with an average error of 4 per cent (greatest
error 15 per cent) in an 11-year period. Brood sizes reported by

carriers did not change significantly from year to year.

iii

{gly-September extensive roadside surveys during mid-day were
valueless. Because of differential vulnerability of adults and young
cocks to hunting, I was unable to determine true cock age ratios.

Sex ratios reported by hunters were not valid. Hunter success data,
discreetly used may yield valid indices to fall populations, but com-
puted kill remains the best index.

Multoadside observations of pheasants were correlated with
snow depth. Regressions of cocks, hens, total birds and sex ratio
noted by officers each day on daily average snow depths were plotted
for two entire winters. The regression was apparently not linear; in
addition the regression differed for cocks and hens, and hence sex
ratios changed as snow depth increased. In no regressions did the
Y-intercepts and the slopes show the same relationship. Interpre-
tation of the data was hamered by a lack of a knowledge of the true
population dealt with.

Populations trends by study area from 1937 to 1956 were recon-
structed and discussed. Areas of lake-bed soil origin showed similar

patterns, although widely separated geographically.

iv

A POPULATION SURVEY OF THE RING-NECKED PHEASANT IN MICHIGAN

By

Ralph Austin MacMullan

A THESIS
Submitted to the School for Advanced Graduate Studies of
Michigan State University of Agriculture and
Applied Science in partial fulfillment of
the requirements for the degree of

DOCTOR OF PHILOSOPHY

Department of Zoology

1960

PREFACE

In 1946, faced by a pheasant depression, the Game Division of the
Michigan Department of Conservation set up a research project to survey
the ring-necked pheasant (Phasianus colchicus) population in Michigan.
Its purpose was to determine what things affect pheasant numbersnboth
in time and space. To do this it was also necessary to devise new can--
sue methods. This paper is a report on methods for estimating pheasant
numbers and a reconstruction of past populations.

The study is not from the traditional life-history standpoint,

but rather from the population dynamics standpoint.

Collection 93 115;;

The bulkof the material for this report was collected while I was
in charge of pheasant investigations for the Game Division from 1947 to
1950. This work was financed by Federal Aid in wildlife Restoration
Project W-38-R. J. P. Linduska was the first leader of this project
and conducted surveys in 1946 and early 1947. After 1950 the Game
Division continued many of the surveys that I had set up and by prior

agreement I have used the data from them when necessary.

S_t_a_§_t_s_s_ g; _O_u_r_ Knowledge 9; Pheasant Biology it; .1_9_l_r§.

Pheasants had been managed on the preserves in Europe for many
hundreds of years. Details concerning their propagation had‘besn Swell,
worked out and we knew many basic life history details. Leopold 35 5.

ii

(1943) had determined an average life span of wild pheasants from a
population turnover study. Since pheasants are polygamus, a surplus
of cocks could be hunted each fall with little prejudice to the next
spring‘s breeding effort. Shick (1947) had found that in pens, one
rooster could assure as good fertility in fifty hens as in three.
Studies of the effects of hunting on pheasant populations indicated
that hunting seasons restricted to cocks only could safely allow ex-
tremely heavy hunting pressure. Shick (1952) on the Prairie Farm had
demonstrated that 200 gun hours per acre during a 22-day season could
remove as many as 90 per cent of the cocks, leaving a sex ratio of 10
hens per cock with no apparent damage to the next year's production.
Certainly it was well proven that Michigan's hunting seasons on cocks
only were not seriously affecting pheasant populations.

Research workers had begun to work on census techniques. The habit
of cocks of crowing repeatedly in early morning hours during the breed-
ing season was being exploited to develop an index based on counting
the number of crowings heard per unit of time. (McClure, 1945; Kimball,
1949) Roadside censuses were being tried with mixed successumostly
poor. lhthods for aging pheasants as young of the year or older had

been worked out (Linduska, 1943; 1945; Kimball, 1944).

The Extensive m

In 1946, when this project started, the pheasant had been estab-
lished for only about 30 years in most of its American range. Although
some research had been started in the 1930's (and interrupted by the

war in the 1940's), to my knowledge no extensive study of state-wide
populations had been undertaken.

iii

From the outset, it was decided that this study should be extensive,
dealing with state- or area-wide pheasant populations rather than an in-
tensive survey of populations on small areas.

Most of the research on pheasants in North America had been in-
tensive. Such studies had offered some clues to the population dynamics
of pheasants. But when interpreted in terms of a state-wide pheasant
population, intensive studies had been found wanting in two particulars:

1) Truly representative study areas are difficult to find. Data
from studies in small areas are often inadequate or even mis-
leading when interpreted in terms of the entire pheasant
population of the region they are meant to represent.

2) Even in areas that may be representative, the small number of
birds involved in intensive studies allows large magnification
of error when conclusions are applied to a widespread population.

The intensive worker is also uncertain about the effect his
activities may have on the observed animals and the possibility that
factors peculiar to his study area are not common to the rest of the
pheasant range.

An exanple of the inadequacies of intensive studies as indicators
of state-wide populations is shown in Chapter 2; if one had used popu-
lation figures from Rose Lake and the Prairie Farm (two quite tlmrough
intensive studies in Michigan) as an index to population trends of
pheasants in all of Michigan, he would have been misled.

The most isportant shortcoming of intensive studies as indicators
of large populations is sanple size; even though an intensive study pro-
vided accurate information on a pheasant population, we would probably

need many dozens of such studies to represent the state adequately.

'iv

The extensive study is not meant to replace the intensive study,
but rather to complement it and to answer more accurately questions too
often improperly asked of the latter. Extensive studies may sometimes
require intensive studies for interpretation and may point out the need
for further investigation of certain life history phenomena.

Extensive surveys also have inherent shortcomdngs. They are de-
pendent upon data which are often not gathered critically. In some
cases observers are untrained and in virtually all cases data are
gathered casually, incidental to other duties and subject to the
voluntary cooperation of the observers. Despite the fact they cover
wide areas, care must be taken to assure adequate sanpls sin in ex-
tensive surveys, too.

Rsretofors, these shortcomings had discouraged the use of data
gathered extensively. The "roadside survey" developed in Iowa (Bennett
and Bhndrickson, 1938) and Pennsylvania (Randall and Bennett, 1939), in
which trained observers drove selected routes on carefully selected
dates and time of day, had been severely criticised and in some forms
has been shown to be statistically inadequate (Fisher, Biatt and Berg-
sen, 1947).

notwithstanding these objections, the extensive survey was tried
in'Michigan, and has become a useful tool. Today, extensive surveys
have become the basis for setting pheasant hunting regulations each
year, and are the Game Division's best source of information on pheas-

ant populations from season to season.

Acknowled nts
I am indebted to the Game Division and particularly to Mr. H. D.
Ruhl, Chief, for the opportunity to conduct this study, to

V

J. P. Linduska who designed and supervised the first extensive pheasant
surveys on this project and to P. H. Dale and D. w. Douglass who served
as my supervisors. R. I. Blouch and V. S. Jensen who followed me as
leaders of this project continued a number of the surveys I had con-
ducted, providing me with data over a longer span of years. I express
my appreciation to L. L. Eberhardt for his help, advice and instruction
in the statistical parts.

To professors G. J. wallace, G. A. Petrides, and W. B. Drew, the
‘mmmbers of’mw graduate committee, I offer my sincere thanks for their
patience and encouragement during the long drawn-out period this study
has taken, and for their help in the preparation of this report.

thy employees in the Conservation Department--biologists, of-
ficers, aides, and others--have contributed in advice and untold

thousands of hours of work collecting data.

vi

TABLE OF CONTENTS

Page
m FACE O O O O O O O 0 O O O O O 0 O 0 O O I O O O 0 O 0 0 O O 1 1

LIST OF Tums O O O O O O O O O O O O O O O O O O O O O O O O x
LIST OF ILLUSTRATIONS O O O O O O O O O I O O O O O O O O O O O X11

Chapter
1. THE ESTABLISHMENT OF PHEASANTS IN MICHIGAN . . . . . .

H

l 1 First Releases (1895-1917) . . . . . . . .
1 2 The State's Release Program . . . . . . .
1.3 Growth of the Pheasant Population . .

I 4

1 5

raa~e-ha

The Genetic Origin of‘Hichigan' s Pheasants
Establishment 0f Pheasants in Neighboring
States 0 O O O O O O O O O O O O O O O O O 7. 0 l3

2. VALIDITY OF ANNUAL PHEASANT KILL COHPUTATIONS . . . . . 15

In t to due t ion 0 O O O O O O O O O O O O O O

O O 15
Bird Hunters' Tally Cards . . . . . . . . . . . 15
x111 Reported on License Stubs . . . . . . . . . 18
The Compulsory Hunters' Report Card System . . . 20

Vin Coevering' s Free Press Pheasant Telly . . . 20

NNNNNNN
NGUkUNI-I'

wuyne County Sportsman' s Club Pheasant Tally. 24
Comparison Of Gemputed Kill with K111 on Sample
Areas 0 O O O O O O O O O O O O O O O O O I O O 26

2.8 Studies of Bias Of Hunters' Report Cards" . . . 33
2.9 Computing K111 by Random.Sample Mail Survey . . 36
2.10 Computing K111 by County . . . . . . . . . . . . 36
Zell Conclusions . . . . . . . . . . . . . . . . . . 39

3. DISTRIBMION or mwms . O O O O O O O O O O O O O O 42

3 1 Introduction . . . . . . . . . . . . . . . . . . 42
3 2 General Distribution of Pheasants . . . . . . . 42
3 3 Correlation of Pheasant Distribution with Soils. 43
3.4 Definition of Pheasant Range . . . . . . . . . . . 48
3 5 Selection of Study Areas . . . . . . . . . . . . 48
3 6 Conclusions . . . . . . . . . . . . . . . . . . 51

vii

Chapter
4.

TABLE OF CONTENTS

nnnwm or Ems m s 03an O O O O O O O O O 0

Int reduc t ion 0 O O O O O O O O O O O O O 0
Definition and Description of the "Extensive

Surveys by Sportsmen . . . . . . . . . .
Surveys by Rural Hhil Carriers . .
Surveys by Conservation Officers. .
Surveys by Farmer Cooperators ... .
Ctofing'cock Sumyfl e s e e s e e e
Surveys by Game Biologists . . . . .
Summary and Conclusions . . . . . . .

##4##«Fk-F ##
@OVO‘UI#U NH

8 PR m ’0’ muons O O O O O O I O O O O O O O O O

1 Introduction . . . . . . . . . . . . . . .
2 Growing-cock Surveys and Carriers' Surveys.
3SexRatios................

4 Density . . . . . . . . . . . . . . . . . .
5 Conclusions . . . . . . . . . . . . . . . .

MD PRODUCT I“ O O O O O O O O O O O O O O O I O

6 1 Introduction . . . . .

6 2 Brood Production . . .

6.3 Timing of Brood Surveys

6.4 Brood Size . . . . . . . . .
6.5

6.6

Percentage of Hens Without Broods . . . . .
cone 1 u. ion! 0 O O O O O O O O O O 0 I O 0 O

PREDICTION OF I‘LL KILL PROM SUMMER BROOD COUNTS .

sumyn O O O O O O O O O O O O O O O 0 O O

7.1 Introduction . . . . . . . . . . . . . . . .

7.2 Correlation of Carriers' Brood Counts with
Computed Kill . . . . . . . . . . . . . .

7.3 Source of Error in Correlation of Brood
Density with Computed K111 . . . . . . . .

rmumTIM'Lzeeseseeeeeeeeeee

' O 1 Int raduc t ion 0 O O O O O I O O O O O 0 O 0 O

8.2 Preseason Sex Ratio Surveys . . . . . . . .

8.3 Age Ratios in the Phll Kill . . . . . . . .
8.4 Hunter Success as a Population lisasuremsnt.
8.5 Hunter Opinion Polls . . . . . . . . . . .
8.6 Conclusions . . . . . . . . . . . . . . . .

viii

O O O O O

Page
53

53

53
56
56
62
as
66 .
67
as

70

7O
71
74
79
85

87

87
88
90
92
98
99

100
100
100
107
115
115
115
121
122

123
124

TABLE OP CONTENTS

Chapter
9. WINTER POPULATIONS . . . . . . . . . . .

9 1 Introduction . . . . . . . .

2 Carriers' Postseason Surveys
3 Officers' Winter Surveys. . .
4 Conclusions . . . . . . . . .

10. POPULATION TRENDS-nvANNUAL AND LONG TENN

10.1 Introduction . . . . . . . . . . . .
10.2 Reliable Indices to True Populations
10.3 Sex Ratios . . . . . . . . . . . . .
10.4 Meshing Seasonal Populations . . . .

10.5 Population Trends by Study Areas
SW C O O O O C C O O C C O O O C O O O O .
mu 0 O C O O O O O O C O O C O O O C C O C

B IBL 1mm 0 O O O O O O O O O O O O O O O O 0

ix

0 O O O

Page
126

126
126
129
142

144
144
146
146
149
151
156
162

166

Table
2 .1

2.2

2.3

2.4

205

2.6

2.7

2.8

3.1
3.2

4.1
5.1
5.2
5.3
5.4

LIST OP TABLES

Pheasant Hunting Data from Bird Hunters' Tally
C‘rd.,1929-1935eeeeeseeeeeeeesee

Pheasant Kill Coquted from License Stubs,
1932-19350eeeeeeeeeeeeeeeeeee

Van Coevering's Free Press Pheasant Tallies,
1931-1956eeeeeeeeeeeeeeeeeeee

Wayne County Sportsman's Club Pheasant Tallies,
1947-1949 O O O O O O O O O O O O O O O O O O O O

Frequency Distribution of Hunters According to
Huber of Cocks Shot, as Reported to HCSC and
st.t.’ 1949 O O O O O O O O O O O O O O O O O O O

Coqarison of Cocks Shot per Hunter, HCSC and
St.t.’ 1947-1949 e e e e e e e e e e e e e e e e e

Coqarison of Actual 1937-1949 Kill on Two Saqle
Areas with coquted Kill in Containing Counties .

Coqarison of Coquted Kill as Determined from
First 20,000 Returns with Final Returns . . . . .

Statistics Concerning Study Areas . . . . . . . .

Per Cent Pirst- and Second-class Land in Study
Ar.“ O O O O O O O O O O O O O O O O O O O O O O

Average Lengths of Carrier's Routes . . . . . . .
St-ary of Growing-cock Surveys . . . . . . . . .
Sun-nary of Carriers' Spring Surveys . . . . . . .
Sex Ratios Observed by Carriers in Spring Surveys.

Frequency Distributions of Harem Sizes 'as Reported
by C‘rrier. O O O O O O O O O O O O O O’ O O O ‘O O

Page

17

19

22

27

28

29

31

35
50

52
61
73
75
76

77

Table

5.5

506

6.1

7.1

7.2

7.3

704

8.1
8.2
9.1
9.2
9.3

LIST OF TABLES

Adjustment of Carriers' Density Indices to Common
St‘rtm D‘te O O O O ' O O O O O O O O O O O O - .. O

Daily Pheasant Observations by Carriers, Spring,
1950 O O O O O O O O O O O O O O O O O O O O O O

Size of Broods Reported by Carriers . . . . . . .
values of Correlation Coefficients (r) for 16

Comparisons of Computed Kill with Carriers' Brood
Den. it, Ind tea. O O O O O O O O O O O O O O O O O

Regression of Computed Kill on Logarithm.of
Carriers' Brood Density Indices . . . . . . . . .

Error in Prediction of Computed Kill from
Carriers' Brood Density Indices . . . . . . . . .

Correlations of Brood Size and Two Pepulation
m1c.‘ O O O O O O O O O O O O O O O O O O O O O

Observed Sex Ratios on Opening Days . . . . . . .
Pall Pheasant Observations by Officers . . . . .
Officers' Lste'Winter Survey - 1946 . . . . . . .
Summary of Carriers' Postseason Surveys . . . . .

Officers' Pheasant Counts on Days with a Trace
o r no snow O O O O O O O O O O O O O O O O O O O

xi

Page

81

83

96

101

105

108

113
118
119
127
128

135

Figure
1 . 1

1.2
2.1

2.2
2.3

2.4
2.5
3.1
3.2

3.3
4.1
4.24
4.3
5.1

5.2

5.3

6.1

6.2

LIST OP III-DSTIATIONS

Hap, Areas Considered Good Pheasant Ranting in 1930 . .

Hap, Hhere Pheasants Here Considered Abundant in 1934 .

Pheasant Kill Computed from hell G-e, lhnters'
Report Cards, 1937-1956 . . . . . . . . . . . . . . . .

Computed Kill Compared to Van Coevering's Tally . . . .

Regression of Computed Kill on Pheasants Seen per
Hour in Van Coevering's Tally . . . . . . . . . . . . .

Hap, Graphs of Computed Kill by County . . . . . . . .

Indices to Fall Populations. 1932-1956 . . . . . . . .

Hep, Computed Kill per Square Mile by County . . . . .

Hap, Groups of Soil Associations in Southern Hichigan

“a Study “a“ O O ,O O O O -O O O O O D O O O O O O O O

Hap, Administrative Delineation of Pheasant Range . . .

Pheasant-aging Cards Sent to Sportsmen . .. . . . . . .

Hap, Location of Carriers' Routes . .7 . . . . . . . . .
Hap, Officers' Administrative Districts . . . . . . . .
Hap, Location of Growing-cock Survey Routes . . . . . .

Frequency Distributions of Harem Sixes as Reported
by C‘rrier. O O O O O O O O O O O O O O O O O O O O O O

Relationship of Craving-cock Index to Carriers' Spring
Density Index, Adjusted to Canon Starting Date . . . .

Brood Density Indices as Reported by Carriers and
Officer., 19“ O O O O O O O O O O O O O O O O O O O O

Officers' Brood Density Indices . . . . . . . . . . . .

xii

10

21
23

25
37
40

46

49

57

60

72

78

82

89

91

Figure
6 . 3

6.4

7.1

702

7.3

90l

9.2

9.3

9.4

9.5

9.6

9.7
10.1.

1002

LIST OP ILLUSTRATIONS

Carriers' Daily Brood Counts Compared with Precipi-
t‘tim O O O O O O O O O O O O O O O O O O O O O O O

Frequency Distributions of Sizes of Half—grown
Broods Observed by Carriers . . . . . . . . . . .‘ . .

Regression of Computed Kill on Carriers' Brood
Density Indices for Study Areas, 1946-1949 . . . . .

Regression of Computed Kill on Logarithm of Carriers'
Brood Density Index for Primary Pheasant Range, 1946-

1956 O O O O O O O O O O O O O O O O O O O O O O O O

Comparison of Computed Kill with Logaritl- of
Carriers' Brood Density Index for Study Areas, 1946-
1956 O O O O O O O O O O O O O O O O O O O O O O O O

Comparison of Daily Average Snow Depth with Daily
Pheasant Observations by Officers . . . . . . . . . .

Regression of Pheasants Observed per Officer-day
mnOily AVOI’O‘O 8n" 389th e e 'e ‘e e e e e e e e s e

Regression of Cocks Observed per Officer-day on
DailyAverage SnowDepth . ... . . . . . . . . . . .

Regression of Hens Observed per Officer-day on
DailyAverage SnowDepth . . . . . . . . . . . . . .

Hodel Suggesting a Relationship of Observability of
a Pheasant Population to Snow Depth . . . . . . . . .

Model Suggesting Shift in Relative Observability
of Cocks and Hens as Snow Depth Increases . . . . . .

Increase in Sex Ratio as Snow Depth Increases . . . .
Schematic Diagrms of Census Information Needed . . .

Computed K111 in Study Areas, 1937-1958 . . . . . . .

xiii

93

97

102

104

106

131

133

136

137

138

139
141
145

152

Chapter 1

THE ESTABLISHMENT OF PNEASANTS IN MICHIGAN

1.1 gig; 11616.ne- gags-fig)

On‘Harch 27, 1895, Hr. Arthur G. Baumgartel liberated sev-
eral pairs of ring-necked pheasants on the Henry Harrington Farm
at Harlem, in Ottawa County. This was the first recorded release
in Michigan.1 A brood was observed in the vicinity on August 24,
1895.

This release was not hastily conceived. For some years
Baumgartel had considered the need for a new game bird. He and
his friends had weighed the relative meritsiof pheasants and
Hungarian partridge as suitable birds for Hichigan. In 1893 he
consulted with Emerson Hough, western representative of "Forest
and Stream” and they decided that the Mongolian Pheasant was the
best bet. He had tried to obtain wdld birds from Oregon where
they had already become established, but that State had already
forbidden exportation of pheasants. So he purchased two pairs of
pheasants from a private game farm.in New Jersey in August, 1893.

That year the‘Hichigan Legislature passed a law protecting pheas-

 

1This event is rather uniquely commemorated by a granite
memorial on the Harrington Farm to the side of 08-31, six miles
north of Holland. On it is etched the outline of a cock pheasant,
and this inscription: "'rms BOULDER comments run near /
PLANTING 0F PHEASANTS IN‘HICHIGAN. / THEY WERE RELEASED NEAR THIS
3201‘ / BY A. s. smnmL I or mLLAND, MICHIGAN, MARCH 27, 1895.

/ ERECTED BY I HOLLAND FISH AND CANE CLUB / HOLLAND POINTER AND
BETTER CLUB I NOVEMBER, 1940."

1

ants for 5 years. In 1894 Bsumgartel organized the Holland Rod
and Gun Club ma the club posted a $5.00 reward for "information
leading to the arrest and conviction of anyone shooting the
pheasants."

In the fall of 1895 more birds were liberated. No known
broods resulted from these releases, and it can be assumed that
the birds disappeared shortly thereafter.

Wilson (1948) has described this first attempt to establish
pheasants in Michigan and reports a number of other newsptper
accounts of releases by private persons in the early 1900's. He
concluded that stocking attempts were numerous with " . .4. little
more than a fraction of them succeeding." Dy "succeeding?

Wilson probably meant breeding in the wild, for there is no evi-
dence that any of these releases resulted in a permanent colony
of pheasants, although quite probably some released birds did
breed.

A search of the records of State organizations responsible
for game matters shows no reference to pheasants prior to 1913.

In 1914 the Game, Fish, and Forest Fire Department of the Public
Domain Commission issued its first biennial report, which listed
permits to keep game animals. In that 1913-14 biennial report,

2 of 158 permits were for pheasants. In 1915-16, 6 of 349 permits
were for pheasants, most for one or two pairs.

There was no official magazine reporting on Conservation
affairs inAHichigan before 1922,‘ but from 1913 to 1922 the "Michi-
gan Sportsman," a commercial magazine, did a serviceable job of

reporting on game matters. There are no references to pheasants

in the incomplete volumes of this magazine available in Michigan
libraries for the years 1913 through 1915. In the 1916 volume,
however, the sponsors of the magazine were carrying on a vigorous
campaign urging the State to establish a game farm for pheasants.
Their campaign was thorough, their arguments many and optimistic.
One of their most persuasive points was that New'York State had
only recently acquired a game farm and had succeeded in establish-
ing thriving colonies of pheasants. It is significant that in
their arguments as to why the pheasant should be able to adapt
itself here, not one reference is made to a colony already estab-
lished in Michigan. If there had been successful colonies, how-
ever small, it seems likely they would have been mentioned.

Perhaps the most revealing official statement on the status
of pheasants before the State's release program in 1918 is one by
D. R. Jones, Chief Deputy, Department of Conservation, in a
letter to Baumgartel dated December 17, 1926:

"Personally, we have no data other than that submitted by

you as to the early introduction of these fine birds in

the State. However, we do know that H. B. Hershon and

some of his associates secured and liberated somewhere

between twenty-five and fifty birds in the Saginaw valley

country during the 90's, and apparently the planting was

not successful, as no hunter or observer, so far as we

know, ever reported seeing birds in the locality up until

some time after distributions were being made from the

State Game Farm . . .

"There was also a small liberation of ring-necks made

by public spirited sportsmen of Clarkston, Oakland

County, about 1905 or 6 and it is reported that a few

of these birds survived and hung on up to the time

distribution was started from the State Game Farm . . .

"Along about 1911 or 12 some hunter from Gladwin County,

I think, sent in feathers found in the woods that were
classified as English or Chinese ring-neck . . .

1.2

1.3

He concludes by saying:

"It is safe to say that not one hunter in one thousand ever
saw a ring-necked pheasant until after the distribution of the
birds from the State Game Farm was started in 1917."

Thus, if there were any colonies of pheasants established in

Michigan prior to 1918, they must have been very small and restricted.

The State's Release Program

 

The State purchased its present game farm at Mason in the fall of
1916. About 200 birds were purchased in the spring of 1917 and a
stock of breeders was raised, but no birds were released. After a
successful breeding season on the farm in 1918, 2,396 birds were
released in the fall. Several thousand birds were released each year
thereafter.

Part of the release program begun in 1918 was distributing eggs
(and some day-old chicks) to cooperating farmers and Sportsmen to
hatch, raise, and release. While only a small percentage of these
eggs resulted in birds released, such releases undoubtedly contributed
to the stock, too. Pheasant releases were greatly reduced after 1951

and terminated in 1958.

Growth of the Pheasant Population

 

From 1918 through 1953, an average of about 24,000 eggs and chicks
were distributed to cooperators and in addition an average of 6,700 grown
pheasants were released by the State each fall (McCabe,.g§‘§l., 1956).

Unfortunately, I can find no record of pheasant releases by county
prior to about 1930. We know that most of the birds were released in
the southern third of the state, but some were also released in the

northern two-thirds.

The pheasants released in 1918 and 1919 must have done
remarkably well. These birds, plus the second-generation progeny
of the 1918 releases, produced a population in the fall of 1920
which prompted this rather remarkable observation in the preface
of the 1919-20 biennial report (gp. git.) quoting opinions
expressed by " . . . sportsmen who have gone afield during the
open season, 1920."

" . . . the introduction of the ringrnecked pheasant to

Michigan covert has proven successful to a degree exceed-

ing expectations; . . . the experimental stage has been

passed and the.species established as a permanent game

bird in the State.”

In 1923 the Department of Conservation recommended a state-
'wide season on pheasants (November 1-2 and 14-15) with bag limits
of 2 per day, 4 in possession and 8 for the season. The legis-
lature did not see fit to implement this recommendation. but the
implication is obvious--after five years, in which perhaps 45,000
birds were released, pheasants were well enough established that
game administrators recommended an Open season.

In 1925 the season was opened in the entire state for 7 days
October 25 to October 31, inclusive. There has been an open sea-
son each year since then.1

The biennial reports from 1916 to 1930 contain much discus-
sion and speculation concerning the establishment of pheasants in

Michigan. In view of what we now'know'about the distribution of

pheasants, these earlyuppinions are interesting and pertinent.

 

1Leopold (1931) reports there was a 45-day open season on
pheasants in 1910. I can find no basis for the statement in
‘Hichigan records, and conclude it is in error--possibly due to an
erroneous report which confused the meaning of the words ”par-
tridge" and "pheasant." The season on ruffed grouse ("partridge")
was open for 45 days in 1910.

Undoubtedly they represent many different viewpoints; they are
subjective, and they may even occasionally reflect the unfounded
optimism of politicians. But despite the absence of statistical
support, they are often astute and even prophetic. Following is
a chronological paraphrasing of statements in these biennials.
1917-18

John Baird, State Game, Pish,and Forest Fire Commissioner,
stated that already the release of pheasants "appears to have
solved the small game proposition for the lower counties of Michi-
gan." He felt it was doubtful that pheasants would do as well
“north of the Saginaw Valley" but intended, nevertheless, "to
make every effort to distribute the pheasant throughout the
entire area of the state."
1919-20

" . . . we have passed the experimental stage in the
matter of establishment of ringnecked pheasants in Michigan,. . ."
a remarkable statement to make after three years of releases.

"The prime purpose of the Department in bringing the

bird to Michigan was to provide a substitute for the

native ruffed grouse, now'almost exterminated in the

depleted cover of the southern counties with their

improved and sparsely wooded farming areas."

Farmers reported that pheasants were breeding prolifically
in all cleared land of southern Michigan.

For the second time it was mentioned that pheasants were not
expected to thrive in northern coverts, although administrators

thought at the time that they were doing surprisingly well in the

north. Expressions of doubt as to the suitability of pheasants

for the north were based on fear of excessive predation as well
as unsuitability of the range.
1921-221

Although there still seemed to be some argument as to whether
or not the pheasant was a "budder," observations indicated it was
not, and hence the bird would be restricted to the southern third
of the state where snow depths were not excessive.

1927-28

By 1929 it was concluded that pheasants were firmly estab-
lished, that about 30 of the southernmost counties could be con-
sidered pheasant range, and that the game farm had fulfilled its
‘main purpose of supplying

” . . . breeding stocks which, when released, proceed

to 'go wild,‘ increase of their own accord, and so

continue to make and maintain satisfactory hunting."

Since repeated plantings in the north had failed, it was
thought that further plantings would be useless unless the local
people fed the birds in the winter. There was some doubt that
even such care would maintain birds, but a large scale experi-
ment in‘Hanistee County was under way to see if such a system
would work.

Deparmment officials speculated that there might be about
100,000 pheasants in‘uichigsn in 1928. This estimate was based
on a pheasant range of 30 counties, or about 20,000 square miles,

and the assumption that there must be at least 5 birds per square

mile in this range.

 

1Biennial report of the Deparmment of Conservation, which
was created in 1921.

By 1930 pheasants were apparently still expanding. In the
fall of 1930, the State Conservation Department made the first
official statewwide survey of pheasants. Conservation Officers
throughout the state were asked to appraise their districts as
"pheasant territory" using the terms "excellent, good, fair, poor,
and hopeless." The map shown in Figure 1.1 shows the areas that
administrators considered "good hunting." This conclusion is
‘made in the 1929930 biennial report:

"A rather rolling country with tangled swales, unpastured

wood lots, and brushy fence rows alternating with grain,

clover and uncultivated fields, and where some ground is
bare during most of the winter seems most favorable.

"In most level areas, or where most of the land is cleared

or farmed intensively, or in areas containing high percent-

ages of wild woods or in deep snow districts, the pheas-

ant seems to succeed poorly, if at all."

Despite the fact that this conclusion was based on uncriti-
cal opinions of a large number of non—professional observers
spread over the entire state, usually with only one observer per
area, the conclusion they reached was probably sound. It is quite
likely more than coincidence that observers from the flat, heavy
clay soils of lake-bed origin bordering the Great Lakes in south-
eastern Michigan should rather consistently report that country
as poor pheasant range. That same lake-bed soil in southeastern
‘Michigan later became the best pheasant range in Michigan and
among the best in.North.America.

In 1934 officers were again asked to appraise their districts,
this time with terms "abundant, scarce, or suitable for pheasants

but none reported." Figure 1.2 shows the areas in which the offi-

cers said pheasants were abundant. These areas are roughly twice

A... J

 

 

“m -'~4 1.: L

 

 

 

 

 

 

 

 

 

 

 

 

Fig. l.1--Areas considered good pheasant hunting in 1930.

     

  

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Fig. l.2--Hhere pheasants were

    
 
  
   
     
       
  
  
 

considered abundant in 1934.

10

1.4

11

the acreage classed as good hunting in 1930, although the 1934 classifi-
cation is certainly more restrictive. This would indicate that pheas-
ants had increased substantially from 1930 to 1934, and the lake-bed
clay areas in southeastern Michigan apparently were beginning to produce
many more pheasants.

The original records from which these maps were prepared have been
destroyed, but the 1930 map is referred to in the 1929-30 biennial,
in which it is stated rather conclusively that

"It has become evident . . . that north of town line 20

little, if any, of the territory has proven capable of main-

taining even fair hunting except locally and as a result of

repeated and heavy plantings."

In spite of the fact that pheasant pOpulations were still building

up in the early 1930's, these two maps of pheasant distributions show
quite clearly that pheasants had about spread to the limits of their
range by that time. There are no large areas inhabited by pheasants

today that were not colonized in 1930.

The Genetic Origin_gf Michigan's Pheasants

 

Michigan's pheasants are a mixture of a number of subspecies of

the genus Phasianus. Examination of the plumage of cock pheasants picked
at random from Michigan's pheasant range would show this mixed ancestry;
rarely would one find a pheasant typical of any one subspecies.
Taxonomists and historians are not completely agreed on the deri-
vation and taxonomic status of the species and subspecies of Phasianus.
Introductions of several subspecies, freely interbreeding where their
ranges overlap, from several widespread areas in Asia, and long
confinement and artificial mixing and selection in game farms have
thoroughly confused the genetic composition of the game farm birds,

from which our wild birds come.

12

Delacour (1951) describes the pheasants brought into Europe
and America as follows:

Phasianus colchicus torquatus is one of a group of 17 sub-
species in eastern Asia. This subspecies (and presumably others
closely allied) was the stock from which perhaps most of the
introductions to England in the 18th century and America in the
19th century were made.

The so-called Mongolian Pheasant he describes as _l_’_._ _<_:_._ 20.3-
golicus, typical of the Kirghiz pheasants, a group of three sub-
species in western Asia, far removed from Mongolia. They are not
linked to the eastern Asia groups. He reports that Hasenbeck
introduced some of these birds to England in 1900, and that from
these the game fanm stocks (in America as well as England) of
Mongolian Pheasants were developed.

The game breeders' English blackeneck pheasants are pre-
sumably the result of introductions of‘gé'g; colchicus, (or one
of the other two subspecies in this group of Caucasian pheasants)
from the western edge of Asia.

Taxonomists agree that.g; versicolor. the green pheasant,
restricted to the islands of Japan, stands the test of a separate
species.

The melanistic mutant Qg;.g; mut. tenebrosus) was developed
in English game fanms about 1880.. It breeds true, with no inter-
mediate forms, and appears to be exceptionally hardy.

Michigan pheasants most nearly resemble torggatus; com-
monly, cocks show coloration indicating mongolicus ancestry.

Rarely one sees a bird that shows characteristics of versicolor.

1.5

13

Occasionally a cock is lacking the white neck ring. This
may or may not reflect colchicus influence, since the white neck
ring is a variable characteristic, and certain individuals of the
17 subspecies in the torggatus group of eastern Asia‘may lack it.

‘The Game Division receives perhaps a half a dozen reports
each year of observations of white, or partially white pheasants.
Some of these may be the result of albinism or natural mutation,
but I feel that some may result from private releases or escapes
from private holdings of the game breeders' fancy white pheasant.

There are some melanistic mutants in a small colony of pheas-
ants around Eose City, in Ogemaw County. They are descendants of
a private release in the middle 1930's. While these mutants are
not common, the strain maintained itself at least 15 years,
until the early 1950“s, when the Game Division released a few
dozen more game farm melanistic mutants in that area.

Hunt (1956) recalls that at the Mason State Game Perm in the
spring of 1918 “ . . . breeding stock of about 500 females (pre-
sumably Chinese ring-neck stock] . . . were mated to some very
fine purebred Mongolian males." The releases starting in the
fall of 1918 were undoubtedly successful, so we can assume Michi-
gan's pheasants were strongly influenced by Mongolian stock from

the first.

Establish-ant _o_f Pheasants in Neighboring _S_t_a_t_:2§

Pheasants apparently becane well established in all of the
Lake States (Wisconsin to Ohio) at about the same time. As in
Michigan, private releases were made around the turn of the cen-

tury, with but few succeeding. Indiana, Ohio, and Michigan were

14

operating State release programs in the second decade of the cen-
tury. Illinois and Wisconsin began serious release programs in
1928 and 1929, respectively, but other private releases had
already established the birds in some areas. Leopold (1931) pre-
pared a map showing the distributions of pheasants in the Lake
States in 1928-29. From the map we can say that in general
pheasants had:
1) become established and completed their major expansion
1 in Ohio, Indiana, and Illinois,
2) reached the limits of their range but were still increas-
ing in Michigan,
3) still some potential range in Wisconsin in which to
spread.
we can also conclude that the establishment of pheasants in
each of the Lake States was essentially independent of pheasant
populations in adjoining states. Probably by 1940 pheasants had
become established in all the Lake States range suitable to them.
It is unlikely that any sizable new area will be colonized by

the brand of pheasants we now have.

2.1

2.2

Chapter 2

VALIDITY OF ANNUAL PHEASANT KILL COMPUTATIONS

Introduction

When this study was begun in 1946, kill figures computed from.
small game hunters' compulsory reports were the only statistics
that showed any promise as a reliable source of information on
state-wide populations for the preceding years. This system.had
been in effect since 1937, and provided what appeared to be rea-
sonable estimates of each fall's kill. There were, however, no
other data on state-wide populations with which to evaluate this
computed kill. There were a number of other surveys of doubtful
value. One of the first objectives of the project, then, was to
try to evaluate this computed kill as a measure of fall popu-
lations, and to investigate the possible usefulness of other kill
surveys that had been made.

In the following sections, the computed kill figures and
various other hunting season surveys are discussed, more or less

in chronological order.

§i5§.8unters'_gallz Cards

In 1929, the Department started its first system for obtain-
ing specific data on pheasant hunting in Muchigan. Department
workers distributed "Bird Hunters' Tally Cards" to hunters, who re-

corded such information as the hours and days they hunted, and the

15

16

number of birds they saw and the number they shot. These cards
were returned to the Department and tabulated. Tabulations from
these tallies for the years 1929 through 1935 are summarised in
Table 2.1.

At best, only a few hundred tally cards were returned to the
Department, so the sample is extremely small. Nevertheless, the
reporters may have been a rather consistent group whose reports
could reasonably be compared from year to year.

Probably the best measure of pheasant populations from these
tally cards is in terms of success indices (birds flushed or shot
per gun hour). Any extension of kill per gun hour to total kill
through calculations involving numbers of hunters seems impractical.
In recent years (1937-1959) a 10 per cent change in numbers of
licenses sold from one year to another has been unusual. But
license sales during 1929-1935 fluctuated radically--a 55 per cent
increase in 1933, and a 32 per cent decrease in 1931! There may
well have been complicating factors not known to us today which
were responsible for these fluctuations. For example, in 1931
the Department changed vendors from county clerks to Department-
selected private dealers. Whatever the reasons for these changes
in license sales, suspicion of their validity as a source of data
on numbers g§_hunters precludes their use as a factor in esti-
mation of total kill.

If this appraisal is of any value, we might interpret the
period of 1930-1935 as one in which pheasants were increasing,

with the suggestion of a slight slump in 1935. In 1935, the last

year of this survey, publication of the tally card in newspapers

did not result in a much larger return, so the system was abandoned.

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18

2.3 gi_l_l_._ Raported 2;; License M

During this same period another kill-reporting system.was in
operation, apparently more or less experimentally. When a hunter
bought his small game license, he was asked to record on a stub the
number of pieces of game he had killed the previous year. I can
find no published reports on these results, but there are a few un-
signed memoranda in the Game Division files listing data collected
by this sample. What could be located are shown in Table 2.2.

These data are difficult to interpret. The question of actual
hunter numbers in 1932, mentioned in the last section, applies here
too. On the other hand, the principle involved in this system--
determining total kill by applying (1) average pheasant kill re-
ported by (2) a large "random" sample (those reporting) of (3)
all hunters to (4) total license sales--was the forerunner of the
hunter report card system adopted by the Conservation Department
in 1937.

Using this system of calculation, I have prepared total kill
estimates for the three years of data I could locate. They differ
considerably from the estimates made at the time. The latter; hDWP
ever, were obviously not meant for publication, and were admittedly
subjective. At least in 1935 the estimate was based on incomplete
returns. Further, administrators at the time may have known of
good reasons, not clear to us, to suspect the accuracy of the
license sales figures.

About all we can say of these calculations is that quite
probably the legal cock pheasant kill for 1932 to 1935 was some-

where between 500,000 and 800,000 per year.

19

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20

2.4 The Compulsory Hunters' Report Card System

2.5

Starting in 1937, each hunter was required by law to report
the game he took each year to the Department of Conservation, on an
addressed card furnished with the license. These report cards re-
mained essentially unchanged from 1937 until the system was discon-
tinued in 1956.

The annual pheasant kill for the state, as computed from
these small game report cards, is compared with license sales for
the years 1937 through 1956 in Figure 2.1. These kill figures will
be referred to as the "computed kill" in the rest of this report.

The method of computing this figure is shown in the appendix.

lag Coevering's Free Press Pheasant E11

Jack Van Coevering, Outdoor Editor of the Detroit Free Press,
has conducted a "pheasant tally" each year since 1931. Shortly
after the pheasant season each year he requests hunters to fill
out a form which he publishes in the Free Press. as usually
receives about 2,000 replies, and it is reasonable to assume they
represent a fair sample of pheasant hunter performance, although
the sample is undoubtedly biased according to distribution of the
paper's circulation in the state, and by the type of hunter inter-
ested enough to submit a tally. Results of his tally are shown in
Table 2.3

I compared Van Coevering's surveys with the State's computed
kill for the 13-year period from 1937 to 1949 inclusive. This
comparison is shown graphically in Figure 2.2. In this figure,
the two graphs are equated arbitrarily at 1937, since units for

the two lines are not directly comparable. The correlation-

21

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TABLE 2.3
vm oosvsamc's ms puss PHEASANT TALLIBSI
1931-1956
' Pheasants SeenAper Hour Number of
Year Sex Ratio Counties
Hens Cocks Total (Hens/Cock) Involvadz

1931 - - 2.4 12
1932 1.5 0.8 2.3 2.0 27
.1933 1.7 0.9 2.7 2.0 23
1934 2.4 0.7 2.1 3.4 31
1935 1.3 0.8 2.1 1.6 30
1936 1.5 0.8 2.3 2.0 27
1937 1.5 0.9 2.4 1.7 34
1938 1.8 1.1 2.9 1.6 34
1939 1.7 0.9 2.6 1.9 44
1940 1.9 0.9 2.8 2.0 31
1941 3.1 1.6 4.7 1.9 27
1942 2.8 1.4 4.2 2.0 26
1943 4.3 2.0 6.3 2.2 19
1944 3.6 1.3 4.9 2.8 29
1945 1.9 0.8 2.7 2.4 2Q
1946 1.4 0.6 2.0 2.3 35
1947 1.1 0.6 1.7 1.8 34
1948 1.0 0.6 1.6 1.8 37
1949 1.5 0.7 2.2 2.1 32
1950 1.3 0.7 2.0 1.8 -
1951 1.8 1.0 2.8 1.8 -
1952 2.1 1.0 3.1 2.1 -
1953 2.1 1.2 3.3 1.8 -
1954 2.7 1.0 3.7 2.7 -
1955 2.6 1.2 3.8 2.2 -
1956 1.6 0.9 2.6 1.8 -

 

 

 

 

 

 

1 pan from Van Coevering (1949; 1950;1957).

2 Data not available 1950-1956. However, 34, 36, and 30
counties were involved in tallies made in 1957, 1958, and 1959
respectively. Number of hunters‘ reports has been between 1,900
and 2,500 most years.

Computed Kill -(Stote)

 

  

  

 

 

2,000,000 a
F ’I \
I \\
”‘v’ \
I,ooo,ooo -
— COMPUTED KILL ’
State
soo,ooo- --- BIRDS SEEN PER HR.
Von Coeverinq
l l I l l J 1 l l l 1
I937 '39 '4I '43 '45 '47 '49

Fig. 2.2--Ccnputed kill compared to Van Coevering's tally.

23

Birds Seen Per Hr.-(Von Coeverinq)

2.6

24

coefficient of birds seen per hour by hunters reporting to Van
Coevering-ea the computed kill for the 20-year period 1937 to 1956,
inclusive, as shown in Figure 2.3, was calculated at r x .876.

This is a good correlation. Whatever the differences between
the two, it seems significant that the trends shown are similar,
and that after 13 years the lines did not diverge appreciably. The
greatest concern for the reliability of the computed kill had been
that as the report card returns dropped, the dwindling sample might
represent an increasing proportion of more successful hunters.

Such a bias would progressively inflate the computed kill. Since

Van Coevering's number of reporters has stayed remarkably constant,
we can say, with reasonable confidence, that this inflation has not
resulted, unless some unknown bias has affected the two relatively

independent surveys in the same way.

Waype County Sportsman's glub Pheasant Tally
In 1947, Victor Beresford, Secretary-Editor of the Wazge

Qggptz,§pg;5ggggjg_glgp_(the "WCSC") in Detroit, sent a form to
some 7,000 members with the request that each member answer ques-
tions concerning his pheasant hunting during 1947, and the 1946
season as well. Returns were sent to the Game Division and tabu-
lated on IBM machines. The results were compared with the State's
pheasant kill computation. The 1946 data were disregarded because
of the long interim between hunting and questioning. Data ob-
tained from these tallies appeared to have merit, and so I de-
signed a form.asking for considerably more detail for the WCSC

for 1948 and 1949. This form was designed particularly to collect

25

1400 '-

1200 —

 

y e 462 + 175::
1000

800

600

Computed K111 inIhousands (y)

400 I—

200‘ .—

 

4 I I I I I J_
1 2 3 4 5 6 7

Pheasants 'Seen per Hour (2:)
(Free Press Telly)

Pig. 2.3-~Regression of computed kill on pheasants seen per
hour in Van Coevering's tally.

2.7

26

data which could be cowared to the computed kill. In addition,

I asked for hours hunted and pheasants killed each day of the sea-
son, which the Game Division didn't get on the hunter report cards.
Table 2.4 summarizes the data obtained from these WCSC pheasant tal-
lies for 1947-4849.

It would be difficult to calculate any index to total kill for
the State from these tallies. A success index fromwcsc members,
however, can be compared to a success index obtained from the Game
Division's report cards. This is done in Table 2.5. the that this
comarison is made only with hunters who reported shooting on; g;
93 birds, since unsuccessful hunters are not directly constable.
(The State's report card does not specifically ask the hunter
whether he hunted pheasants or not, and the “080 form does.)

Another cowarison of success indices is shown in Table 2.6.
Using the formula shown in the table, apparently the State success

ratio could be predicted accurately on the basis of the WCSC saqle.

Comparison 9_f_ Muted K113]; with _K_i_l_l_ 93; m 53.32

0 Both Van Coevering's tallies and the W086 tallies show good
correlation with portions of the State data. Since both eagles
are independent of the State sample, they serve as a measure of
proof of. the value of the State figures, even though the two former
are undoubtedly subject to bias because both groups are heavily
represented by the metropolitan Detroit area (e.g., more than half
the WCSC sample hunted in the counties surrounding Detroit in 1949).

However good these correlations may be, they do not offer any

information as to how real the figures are. All three tallies were

27

 

 

 

TABLE 2.4
WAYNE COUNTY SPORTSMAN'S CLUB PHEASANT TALLIES
1947-1949
1947 1948 1949

no. tallies returned 434 738 545
No. who bought small game licenses1 586
No. who reported hunting pheasants2 .321 502 469
cocks shot per pheasant hunter 1.69 1.65 2.09
Hburs hunted for the entire season 17.6 15.3 15.6
Sex ratio of birds flushed 1:2.5 1:2.3 1:2.7
Birds flushed per hour 1.2 1.1 1.4
figure to kill each Cock 10.4 9.2 7.4

 

 

 

 

1N6t asked in 1947

zThis question was specifically asked in 1948 and 1949, and
was not asked specifically in 1947

TABLE 2.5

FREQUENCY DISTRIBUTION OF HUNTERS ACCORDING 1'0 NW! 0?
COCKS SHOT, AS REPORTED TO HCSC AND STATE, 1949

 

 

 

 

 

Number Per cent Hunters

of Cocks Shooting 1, 2, 3, etc.

Shot Per Cocks

“mt“ State wcsc
1 ' 34 35
2 26 23
3 13 10
4 12 13
5 5 7
6 6 7
7 1 2
81 3 3

Total 100 100

 

 

 

1
Season limit

29

TABLE 2.6

COMPARISON OF COCKS SHOT PER HUNTER, WCSC AND STATE
1947-1949

 

 

 

 

 

Cocks Shot per Hunterl’
Year Ratio of
“(:30 8';th State to "08C
1947 . 1.69 1.76 1.04
1948 1.65 1.79 1.09
1949 2.09 2.24 1.07
Average 1.81 1.93 1.07

 

 

 

 

1
State and HCSC indices are not directly comparable.
(See text, Section 2.6)

30

obtained on a voluntary basis.1 It is possible, for exawle, that
in a voluntary system there is a tendency for the more successful
hunters to report their good luck, which would cause an inflation
of the computed kill. On the other hand, there might be a tendency
for more unsuccessful (and therefore disgruntled) hunters to report
their 22.5 met; this would deflate the computed kill. Hunters who
belong to sportsman's clubs are not likely to be an unbiased seaple
of Michigan's over one-half million small game hunters. Possibly
club members are more likely to send in their report cards than the
average small game hunter. So none of these samples is random.

To shed some light on how close these tallies are to actual
kill, we need to comare them with an actual measurement of pheas-
ants killed on sanple areas. Although such areas are rare, the
Department had two study areas where actual kill was measured--the
Rose Lake Wildlife Experiment Station near Lansing, and the Prairie
Perm in Saginaw County.

Rose Lake2 has varied in size from one to two thousand acres,
so it is relatively small. It is difficult to say how it compares
with the rest of the state's pheasant range. The station lies

astraddle the Clinton-Shiawassee County line; Table 2.7 shows how

the average number of birds killed per 100 acres for a 10-year period

 

1Despite the fact it is a misdemeanor to fail to submit the
Department's report card, the law was not enforced. Hence, in
fact, the system was voluntary.

2Thenose Lake Wildlife Emeriment Station is described by
Allen (1941). Researchers obtain careful measurements of pheasant
kill each season, as well as other pheasant population estimates
during the year.

31

 

 

 

 

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m.mm n.5w n.an h.¢m ¢.ou Henna
m.n m.~ m.n mema
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338.. , . =5: 9.3 Son

 

 

 

 

 

 

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h.~ n4n¢a

32

on Rose Lake compares with the computed kill for these two
counties.

It is to some degree coincidence that the average kill per
100 acres at Rose Lake should fit in so neatly between the averages
for the two counties. Notice that the Rose Lake kill was con-
siderably higher than either county during the first three years
. of this period, and lower during the succeeding seven years. If
any other period had been used, the averages would, of course, have
been different. In a way, this local change in Rose Lake's pheas-
ant population supports the notion that computed kill figures are
reasonably close to the actual kill. Rose Lake has been both
above and below the two counties in pheasant kill.

A similar comparison can be made between actual and computed
kill in an area of high pheasant populations. The Prairie Parm,
an 8,500-acre diked area 13 miles south of Saginaw, represents
some of Michigan's best pheasant range. Shick (1952) conducted a
pheasant research project there during the early 1940's. Hunting
on the Prairie Farm reached an almost unheard of pressure, and an
unusually high harvest of pheasants was made several years in a
row. Table 2.7 compares the actual kill on the Prairie Firm to the
computed kill for Saginaw County.

There is no way of knowing how representative Rose Lake or the
Prairie Perm is of the counties with which they are compared. NOr
do I pretend any great accuracy for computed kill figures broken
down to county. These comparisons, however, are some evidence that

the computed kill figures are probably not too far from.actual kill.

33

_——-,_

The percentsge return of small game hunters' report cards
steadily declined from about 40 per cent in 1937 to about 10 per
cent in 1950. If these returns were random, sample size would be
far more than adequate. Since they were not random, such things
as sample size, date of return, per cent return, etc., ggglg_all
introduce sizable bias.

Studies of these possibilities for bias did not warrant ex-
pensive statistical investigation, since the chief use of the com~
puted kill was to determine trends. It would necessitate great ex-
pense to check them with a personal interview system, with no
assurance of eliminating the bias. But since these computed kill
figures were to be the reference point from which to begin my
analysis of pheasant populations, I investigated biases as far as
practical. These investigations were admittedly rather superficial,
but nevertheless somewhat revealing.

Sample Size. Ceboo (1941a) reported on a study of sample size,
apparently made in 1941, in a Game Division memo. The memo is
somewhat ambiguous, but from her data it appears that even 20 per
cent of the returns for one year (apparently a net of 7.6 per cent
of the small game hunters) could be used to compute a total kill
no more than 3 per cent different from.a computation using all the

returns for that year.1

 

1Geboomade her study on computed kill of cottontail rabbits
and deer. Pheasants and rabbits are reported on the same hunter
report card--deer are reported on a separate card.

34

Relative success 9_f_ reporting 3;. non-reporting hunters.
Ceboo (1941b) also supervised a study in which 6,000 non-reporting

hunters were visited by Department workers and asked to give the
information asked for on the report card. I can find no record of
how'many were interviewed, and there appears to be some doubt about
.the randomness of the sample. But those who said they hunted
pheasants reported an average success of 2.96 cocks, compared to
2.88 cocks per hunter who reported voluntarily.

Success o_§ hunters according 53 date g_f_ m. Are either
the more successful hunters (proud of their kill) or the more un-
successful hunters (disgruntled and wishing to complain) prone to
send their reports in earlier than the other group? If either is
'more prone to report, then the shift in percentages of hunters re-
porting might represent a shift in bias over the years which would
lessen the reliability of the computed kill for determining long-
term trends.

In 1948 and 1949, I compared the returns received by mid-
January (around 20,000) with final returns (around 50,000). The
comparison is shown in Table 2.8. If the kill had been computed
on these first 20,000 or so reports (representing about 3 per cent
of the small game hunters), the final couputed kill would have been
2.2 per cent high in 1948 and 8.5 per cent high in 1949. This does

not seem to be excessive bias.1

 

1
An examination of a similar computation in 1947 (not made by

me) indicated the kill would have been estimated about 20 per
cent too high. I have no way of rechecking the original data; cal-
culations may have been in error. But it is possible that the two
years I calculated may not be representative.

35

TABLE 2.8

COMPARISON OF COMPUTED KILL AS DETERMENED PROM FIRST 20,000
RETURNS WITH PINAL RETURNS

 

 

 

 

 

 

 

 

1948 1949

Sample Final Sample Final
Estimated
License Sales 565,068 583,369 645,206 626,941
Per Cent
Difference -3% ~31
No. Report
Cards Received 20,404 52,026 21,238 51,381
Date by Which
Received Jan.19 Jan. 16
Net Par Cent
Return 3.6 8.9 3.2 8.1
No. Who Hunted ' ‘
Pheasants 13,238 31,522 13,199 31,207
Per Cent Who
Reported
Bunting Pheasants 65% 611 621 612
Total Estimated
Pheasant Hunters 367,294 352,627 400,027 391,000
Success of Those
Who Reported Hunt-
ing Pheasants 1.76 1.79 2.36 2-24
Per Cent
Difference -1.6% +5.12
Estimated Total
Pheasant Kill
for Stats 646,347 632,698 944,064 863,959
Per Cent
Difference t2.22 +8.52

 

 

 

 

 

36

2.9 My Kill by Random Sale Mail Survey

2.10

In 1954 the Game Division started a new system of coaputing
small game kill. Following the season, about 4,500 small game
hunters, picked at random, are mailed a questionnaire concerning
their kill. With several reminder letters, response of hunters has
been about 95 per cent-~about as good as can easily be obtained in
such surveys. Pram this saqle the kill is computed. The ran-
domness of the eagle avoids the criticism of the hunter report
card system that it might be biased by an atypical success of the
eagle reporting.

The results of these mail surveys for the years 1952-1955, in-
clusive, are coapared to couputed kill in Figure 2.1. Slouch (1956)
has explained how such surveys are conducted and how the computations

are made .

Cguting Kill by County
The coquted kill is calculated by county. While ssqle sise

for the state-wide figure has been shown to be adequate, it does
not necessarily follow that sample size would be adequate to com-
pute accurate kill by county-"especially in those counties with
low pheasant populations and low hunting pressure.

As the first step for examining county figures, the county
kill by year was graphed on a large map, each county's graph being
super-iqosed on the proper county on the map. These graphs are
shown in Figure 2.4. A close inspection of county graphs in this
figure suggests one flaw in them. Genesee County quite regularly
reported the largest kill for any county. Cenesee County has some

excellent pheasant range, but it is unlikely it can coapare with

37

  
    

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38

pheasant production in Huron or Tuscola counties. Wayne County has
excellent pheasant range, but a large portion of it is metropolitan,
and the Wayne County kill appears unreasonably high. This sug-
gested there was an inflation in the computed kill for some metro-
politan counties.

This inflation is probably a result of the kill computation
method. Hunters are asked to report the county in which they shot
their pheasants, but no attempt is made to distinguish if birds are
shot in more than one county. Hence, there is a tendency for hun-
ters, more numerous in metropolitan counties, to overflow into ad-
jacent counties to hunt, yet innocently report their kill as taken
in their county of residence--or if they list more than one county
for pheasant kill, to put their county of residence first. While
this does not affect the total state kill computation, it does
affect the computed kill by county. This inflation of kill is
‘mostobvious in the metropolitan counties surrounded by good
pheasant range. Thus, the cities of Detroit, Flint, Saginaw and
Grand Rapids, all near good pheasant range, appear to influence
their counties considerably. Kalamazoo, Jackson, Battle Creek,
surrounded by poorer pheasant range, do not appear to influence
their counties as much.

This is a subjective observation, and there is no practical
way to appraise the inflation, if it truly exists. The possibility
that it exists must be considered, however, when making inter-
pretations from.county kill figures.

The computed kill by county has been useful in determining

population changes in various portions of pheasant range. It is

2.11

39

an advantage the mail survey does not offer with its present

sample sise.

mm

Figure 2.5 summarises graphically all the estimates we have
of pheasant kill.

It appears that we had no good measure of the pheasant kill
until 1937 when the small game hunters' compulsory report card
system was started, from which we obtained an annual coquted
kill. Computed kill figures appear to be reasonably representative
of actual kill in the state, and to be useful to reconstruct
trends.

(1) There was no consistent divergence of population frauds
determined from Van Coevering's Tally and the coquted
kill from 1937 to 1949--a period when Van Coevering's
reports remained relatively stable, while the per-
centage of report cards returned were decreasing.

(2) Success indices of hunters reporting on small game re-
port cards were very close to those of an independent
sample of hunters (WCSC) from the Detroit area for two
years.

(3) Comparison of computed kills for three counties was rea-
sonably close to known kill on two sample areas in these
counties.

(4) Studies of the bias of computed kill figures, although
inconclusive, indicated that (a) sample size was proba-
bly sdaquate,.(b) success of non-reporting hunters was

not appreciably different from that of reporting hunters,

4O

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now. 000. new. 000. 39 on!
d n q _ _ q _ A _ _ 4 n q a _ e .

 

 

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03.80..

 

 

 

 

000.80. .

 

 

 

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41

(c) there was some question as to whether success of
hunters differed according to the date at which they sent
in their returns, although in two years studied early
reports differed from the final computed kill by only 2.2
and 8.5, respectively.
(5) Comuted kill figures did not differ greatly from those
coquted from other independent and random mail surveys .
(6) Pheasant kill computed by county and by groups of
counties offered a useful basis for comparing areas of
pheasant range, although there appeared to be an in-
flation of kill figures from some metropolitan counties.
With the exception of Van Coevering's Tally the figures prior
to 1937 are speculative. The curve is plotted to the ratio scale.
Assuming that pheasants were following Pearson's growth curve, and
were in the period of rapid expansion at least from 1925 to 1930,
the log of the population curve should follow roughly a straight
line from its origin, shortly after 1918. if. these assumptions
are correct, then we can guess that the kill in the first open sea-
son (1925) might have been around a quarter of a million cocks,
and that from 1930 to 1935 the kill may have been somewhere around
a half to three quarters of a million cocks.
The graph in Figure 2.5 smarizes the best information on
pheasant populations that we have for the time prior to 1946, when

other state-wide surveys were begun.

3.1

Chapter 3

DISTRIBUTION OF PEBASANTS

Intr uction
The term "distribution" is defined for the purposes of this
report as relative geographical density of pheasants. It should
be understood that relative densities may change from year to
year as well as from area to area.
I have already shown that pheasants had apparently spread
to the geographical limits of their range by as early as 1930
(Figure 1.1). Inspection of the county kill figures (Figure 2.4)
shows no major changes in distribution, geographically, although
relative densities from area to area have changed over the years.
It was probably not until 1944 that pheasant numbers had built up
to the point that all of‘Michigan's pheasant range*was fully
occupied.
l) Pheasants increased rather steadily and rapidly up to
1944.
2) In the early 1930's the flat, heavy clay land of south-
eastern.nichigan was considered second-rate habitat, and
it was not until the early 1940's that this area came to

be considered the best pheasant range.

3.2 General‘gistribution.g£ Pheasants

Advariation of some of the date in Figure 2.4 is presented

42

3.3

43

in Figure 3.1. The kills in each county for a lO-year period,
1937-1946, and for one more-or-less average year, 19‘9, can be
compared geographically. The years 1937-1946 saw pheasants build
up to a peak and start down toward a low. In 1949 about 864,000
cocks were shot, which is approximately midway between the high
and low extremes in kill in 1945 and 1947, respectively.

The two maps in Figure 3.1 suggest a rather sharp demarca- I
tion between high and low pheasant densities on a line between
Arenac and Muskegon counties. Field inspection of many of the
counties on the northern edge of this line (e.g., Gladwin, Clare,
Hecosta, and Newaygo) shows further that most of their pheasant
populations are in the southern part.

It mhy be significant that the border between two great
soil groups, the podaols and the gray-brown podaolic soils as
published by the United States Department of Agriculture (1938) ,
seems to fit almost exactly as a border between Michigan's best
pheasant range and the northern marginal range.1 In many places,
pheasant populations dwindle to an occasional colony of very
limited extent within a mere 10 miles north of this line. About
98 per cent of the pheasant kill during the years 1937-1946 was

made south of this line.

Correlation of. Pheasant _Qistribution with Soils
Inspection of the maps in Figures 2.4 and 3.1 suggested that

soil might be an important determining factor, directly or indi-

 

1“Schneider and Whiteside (1954), however, place the border
between these great soil groups much farther south--on an approxi-
mately east-west line between St. Clair and Kent counties.

.5550 he 0:! season won 3.} voyage-tam .wum

hskh

hk‘d ..\ an".

(0(2‘0

I. Inga-I It! '33 i

i a»: 5‘ 3:4.

 

45

rectly, in the distribution of pheasants. So I compared distri-
bution as demonstrated by the above maps with four soils maps:

1) The United States Department of Agriculture's (1938) map
of the major soil associations of the United States.

2) Leaveret's (1924) map of the surface formations of Michi-
gan, which shows land surface formations based on their
geological occurrence.

3) Hillar's (1948) map showing the land formations pro-
duced through the action of glaciers. In effect, this
is a simplified version of Leaveret's map, and desig-
nates areas of till plain, outwash plain, moraine, and
lake bed.

4) Veatch's (1930) generalised soil and land map, which
groups soils according to such characteristics as fer-
tility, topography, texture, and drainage.

This comparison of pheasant distribution with these soils

maps showed:

1) highest pheasant densities on soils of lake-bed origin,
particularly lake-bed _c_l_a_y soils, although some _s_a_n_dy
soils appeared to support high densities m _of 21:5-
2:51 22.1m-

2) average to high densities on soils of till-plain origin.

3) low pheasant densities on areas of outwash plain origin
and on pronounced moraines.

4) marginal densities on dry, outwash plain M.

This general relationship of soils to pheasant distribution

is demonstrated in the map in Figure 3.2. The soils of southern

46

   
 

5'5. .
......
. s . .

”/1
/
I...

4/

   

  
     
   
  
   

  
 

   

"w

I7&C;%%’/¢f§
.%%%%%,Hy

/§A

      
    

Pheasant
Land 1123 ngglstion
f? Level clay soils of lake-bed origin. High
Sandy, but of lake-bed origin, level High

 

Level or gently rolling loamy till plain. Moderate

- Sandy loan or sand outwash plains. Low

Fig. 3.2--Groups of soil associations in southern Michigan and
study areas.

47

'Michigan are separated into four groupings. The boundaries of
these soil groupings are for the most part based on actual bounda-
ries of the major soil associations as determined by Schneider
and Uhiteside (1954) .1

Correlating distribution with soil is difficult. In a sub-
jective way, this correlation of pheasant density to soil appears
impressive. To state how the relationship works is another thing.
We can note certain connections without much fear of contradiction
--for example, the high pheasant densities on the lake-bed clays,
and the low densities on the sandy outwash plains. The land
could affect pheasant distribution in many and involved ways.

Such things as soil fertility, texture, origin, trace elements,
drainage, and topography could affect pheasants directly or indi-
rectly through their determination of the biota. Or they could
affect agricultural practices and other cultural features which
in turn could affect pheasant populations indirectly.

Albrecht (1944) has stated the case for the influence that
the more nutritive soils may have on wildlife populations. But
despite discussion with soils scientists, I have been unable,
from this gross comparison, to tie down pheasant density to any
single factor such as soil productivity, fertility, topography,
or type of farming. Quite probably there are a number of inter-
related factors which combine to determine pheahant abundance.

I believe, however, that the correlation demonstrated here is

sufficiently valid to justify more intensive study.

 

1Cash H.‘wonser, soils scientist for the Game Division,
assisted me in the preparation of the map shown in Figure 3.2.

48

3.4 Definition _o_§ Pheasant Range
Figure 3.3 delineates the areas I have defined as primary
and marginal pheasant range. I placed the boundaries on county

borders, since I used counties as the unit for collection of data.

3.5 §election _gf Study Areas

I designated five representative areas of primary pheasant
range as study areas (shown in Figure 3.2), on the basis of five
criteria:

1) Homogeneous populations, based on data in Figures 2.4 and

3.1.

2) Homogeneous land characteristics discussed in Section 3.3.

3) At least 3,000 square miles in area (with the exception of

3 Area 5, which was unavoidably smaller).

4) Short north-south dimension to minimise variation due to

climatic or phenological differences.

5) Free of the metropolitan bias, described in Section 2.8,

when practical.

Selection of these areas was to some degree arbitrary. This
is inevitable since I used counties as the basic unit. Thus,
statistics compiled for each of these units must not be considered
in an absolute sense, but as indices. If this rule is followed,
such arbitrariness presents no difficulty, since this selection of
study areas is a form of statistical stratification.

Table 3.1 su-arises some statistics for the study areas.

The ’areas comprise approximately 72 per cent of primary pheasant

    

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RANGE "“"*“‘
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49

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Fig. 3.3-~Administrative delineation of pheasant range.

50

 

 

 

 

 

 

 

 

 

 

 

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and: 2.2 2: 2: o Rn; H
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saunas: Sn 8:: 5 no no «one
eon—Jed anaconda dogmas—5n nongz _ and":
no: engage“? season

 

 

«<3 raga 6253828 mOHHmHHRHm

fin Hugh

3.6

51

range and provided 74 per cent of the pheasant kill in primary
pheasant range during the lO-year period 1937-1946.

Table 3.2 shows the percentage of first- and second-class
land in each of the study areas. Comparison of these land
classes would be more significant if it could be made on the
basis of soil types rather than on county units. It is perhaps
noteworthy that Area 4, with the lowest pheasant density, has a
low'percentage of first-class land. Area 5 has a high pheasant
density, but has the lowest percentage of first-class land of any
of the areas. This may be explained by the fact that Area 5 has
high densities, indeed, but they are restricted to portions of

the area, and the remainder of the area resembles Area 4.

Conclusions

Relative pheasant densities appear to be correlated with
soil groupings. The factors responsible for this correlation are
unknown. They may be direct influences of soil on pheasants or
indirect influences of soil on other phenomena such as cover or
cultural features which, in turn, influence pheasants. Despite
the obscurity of these factors, the correlation seems definite
enough that the subject should be pursued. I recommend further
study of pheasant populations in comparison with the character-

istics of each of the soils groupings in Figure 3.2.

PER CERT FIRST- AND SECOND-CLASS LAND IN STUDY ABBA81

TABLE 3.2

52

 

 

 

 

 

 

 

 

 

 

 

Area Total
1 2 3 4 5 Arias
Per Cent First-
Class Land 56.9 52.4 60.5 33.2 23.7 47.1
Per Cent Second« .
Class Land 32.0 29.1 32.3 41.9 29.6 33.8
Total IL 88.9 81.5 . 92.8 75.1 53.3 80.9

 

j,

1Taken from Veatch(194l).

Chapter 4

DEVELOPMENT OF rmsm SURVEYS

4.1 Introduction

we now have a hypothetical curve showing annual fall popu-
lations (Chapter 2) and a gross analysis of pheasant distribution
(Chapter 3). I have selected study areas on the basis of this
information. These data are all from.ons time of the year, and
all from one family of sources-~hunting season data. They might
have some co-on biases.

The next step is to obtain population data for each study
area, for each season of the year, and for each year of the
study. If we can do that, we can compare data on a single popu-
lation from independent sources. If this leads to valid measure-
ments of populations, we will have the basis for determining what
factors affect pheasants-~in two dimensions, time and space.

The bulk of the data in the rest of this report was obtained
from.extensive surveys. This chapter is a discussion of how
these extensive surveys-ware conducted. For the benefit of those
who might wish to use such surveys, some space is devoted to their
organisation, and to surveys which were tried, but abandoned as

iqractical .

4.2 Definition and Description 2f the; ”Extensive SurveY"

For our purposes an extensive survey can be defined as the

53

54

collection of pheasant observations through a system.of sampling,

usually interpreted in terms of indices to certain populations. It

is to be distinguished from.the intensive survey which.implies a

study of smaller areas involving total pheasant populations rather

than indices based on samples. Following is a list of character-

istics of the extensive surveys I have used:

I)
2)

3)

4)

5)

They cover large areas -- as much as one half the state.
They are reported in indices rather than absolute figures.
While indices can in some cases be converted to absolute
figures, extensive surveys customarily describe pheasants
in terms of birds observed per unit of time or distance
rather than birds per unit of area.

They are based to a large degree on sampling techniques.
Sample size, distribution, and consistency of the
observing group (i.e.,turnover and uniformity of habits
of observers) are iaportant. To some degree the use of
the five study areas is a form of stratification of the
sample.

Extensive surveys may be made by groups of untrained ob-
servers, so long as the groups are consistent.

They usually require large numbers of observers.

There were five sources for manpower to run extensive surveys:

1)

Sportsmen, who have a vested interest in pheasants, might
cooperate at other times of the year as well as during
hunting seasons. There are more than a third of a mil-

lion pheasant hunters in the state.

55

2) Lugs; m_ai_._l_ carriers, who had been used as observers in
other states.

3) Department 9; Conservation personnel other than game
biologists might be asked to help survey pheasants.

4) Farmers might be canvassed for their observations of
pheasants.

5) game biolo ists, although few in ntaaber, might obtain
extensive data of some sorts (e.g., hunter-performance
data from personal interview with hunters, crowing-cock
counts, etc.).

Data were needed for four seasons of the year.

1) Information on the number of breeders present each spring.

2) Data on production of broods in the sumer.

3) Data from hunting that was not available from kill
reports (e.g., age ratios of cocks, hatching dates,
hunter success).

4) In winter, population data, measures of winter loss, post-
season sex ratios, etc.

In the following paragraphs, the various types of extensive
surveys we developed are described. In later sections the data
obtained from them are discussed and analyzed.

The forms used for polling cooperators are important. It is
essential that they be simple, easily understood, and of convenient
size. Provisions should be made for mailing reports back. Simli-
fication of the forms is worth considerable thought. A seemingly
trivial mistake, such as a form that is too large for the return

envelope, might well result in fewer returns. As is true of all

56

such surveys, instructions must be explicit. Any ambiguity
in the questions asked or forms supplied might result in

questionable data.

4.3 Surveys by Sportsmen
In the fall of 1946, when this project was started, Linduska

asked sportsmen to report pheasant observations made in the field
during the winter of 1946-47. They were furnished with compre-
hensive forms asking for a good many types of information, but so
designed that almost any observation which might be of value could
be reported. Over 15,000 of these forms were distributed to mem-
bers of Michigan United Conservation Clubs. Only a few dozen
were returned and no usable data accumlated from them, so this
type of survey was abandoned.

In the fall hunting season of 1946, Linduska also distributed
about 15,000 pheasant-aging forms, illustrated in Figure 4.1, to
sportsmen's clubs, through license dealers, hardware stores,
biologists and officers. Only about 500 were returned. During
the seasons of 1947, '48, and '49, smaller numbers were distri-
buted. About 300 or more were returned each season, recording
ages on four to six hundred birds. These data are discussed in
Chapter 8, with other age ratio data, but their value is question-
able. Despite the instructions, sportsmen were obviously not

aging birds correctly.

4.4 Surveys by Rural Hail Carriers
Bennett and Hendrickson (1938) reported on the "roadside,

census” technique of estimating pheasant populations in Iowa.

57

PHEASANTS are an annual crop, and the number available to hunters in the fall
is largely dependent upon the number produced in the spring and surviving until
Autumn. A comparison of the number of young and old birds shot by hunters is a
valuable means of measuring the survival rate of young from year to year and in one
locality as compared with others. Simple methods for distinguishing young and old
birds are shown below and hunters are urged to report the age of their kill on the

attached postage paid card.

INSTRUCIIONS

Pick up your bird by the lower jaw, inserting
your thumb inside the mouth as shown in the
drawin . If the lower jaw breaks or bands
when a bird is lifted, the cock is this year's
young and the lag spurs will be found to be
short and blunt. S ow the number of this type
killed in column (I) on the attached card.
If the bird can be lifted by the lower yaw
and shaken without the jaw breaking or bend-
ing, the bird is an old one and generally has
long sharp spurs. Tally any birds killed having
these characteristics in column (2).

 

 

Numba’ Of Cocks Killed

 

Thbfonnlnaybeussd (nYoungCocks

for a party record.

Have your partners
record their kin.

 

Birds were Where

Data Counts

Killed Killed

 

(2) Old Cocks

lower jars ed
weight if

  

\’

Spurslsmgamdshslp

 

 

 

 

 

 

 

 

 

Your name and address is
solicited. but not required

#

 

Name:.....-..........

Street or RFD

City '

 

........

 

 

 

IICOII YOU. KILL III I‘ll. TNIO Glifl TODAY

Fig. 4.1--Pheasant-aging cards sent to sportsmen.

58

Later Randall and Bennett (1939) reported on the use of the same
technique in Pennsylvania. In the 1940's several other states
experimented with roadside censuses by rural mail carriers
(hereafter referred to as carriers). In the spring of 1946,

712 carriers in the Lower Peninsula of lflchigan were asked if they
would be willing to make a sinner cormt. Nearly two-thirds (466)
expressed their willingness to do so.

During the summer and fall of 1946, the carriers were asked
to conduct four surveys. Between 250 and 361 of the 466 cooperated.
Again in 1947, summer and fall surveys yielded good returns.

Inspection of the two years' returns from carriers showed two
encouraging things:

1) The relative number of broods they saw from area to area
and year to year was fairly well correlated with the
relative number of pheasants reported shot by hunters
on their hunter report cards. Here, perhaps, was a
potential method of predicting fall kill!

2) The percentage who responded was remarkably high for a
supposedly disinterested group. inoreover, for the most
part, the same carriers were responding for each survey.
The carriers are somewhat more professional than might
be supposed--their turnover is low, they are a con-
scientious group, and in the words of one of them,

"being government employees, we are used to making sur-
veys. we make a lot of surveys even sillier than your

pheasant survey. That's part of our job."

59

So once again we invited the more than 900 carriers in pheas-
ant range to help us. The Rural Letter Carriers' Association, to
which most of them belonged, encouraged their members to assist,
which helped i-easurably.

Beginning in 1948, the carriers were asked to make three sur-
veys annually--a spring survey in April, a brood survey in July,
and a postseason survey in early December or late November.

Close to 500 carriers have helped regularly in these surveys.

Figure 4.2 shows the distribution of carriers in pheasat
range. Since pheasants are restricted principally to farm land,
and since virtually every farm is visited each weekday by a
carrier, a large percentage of Michigan pheasant range is covered.

Carriers' observations are measured in this paper in terms
of "10 carrier-day" periods. Use of the carrier-day rather than
miles of travel as the unit saves a prohibitive mount of. clerical
work. The "10 carrier-day" unit can be converted and interchanged
with a “per mile" unit with no appreciable error. A comparison
between the two units "birds seen per 10 carrier-days” and "birds
seen per mile of travel" is shown in Table 4.1. As a rule of
thumb, the 10 carrier-day period can be equated to 500 miles of
travel. The rural mail carrier surveys carried on in many other
states are conducted in many different ways, and so comparison in
any but a general way mat be done carefully.

The mileage of a carrier's route does not change from day to
day. Carriers' routes average very nearly 50 miles each in all
counties. So, for the size of. the sample (around 500 carriers),

the average mileage or time spent on his route would change but

ARENAC

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Fig. 4.2--Location of carriers' routes.

61

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4.5

62

little from survey to survey. Further, results of surveys are al-
ways comared to other surveys by carriers; so the unit, whether
it be time or linear distance, is i-aterial. Finally, even
though routes might vary 2 miles (4 per cent), we have no reason
to believe that time (hours on the route) is any less valid as a
unit than miles traveled. For nearly 30 years the unit of
‘measurement of’deer counts made by Department personnel has been

"time spent in deer territory" rather than miles traveled.

Surveys [:1 Conservation Officers

Michigan conservation officers (hereafter referred to as of-
ficers) are carefully selected and well trained. Thy are inter-
ested in their work and are. cooperative, which makes them valuable
observers. The nature of their duties and their daily routine
provide a consistency of observations. The fact that they are
Department eqloyees made it easy to arrange for them to record
pheasant observations in any fashion and period required. In
some years, officers have recorded daily pheasant observations
for nine months of the year.

In many instances, officer counts coqlement the carrier
surveys-~each supplying what the other lacked. With only one
or two officers per county, data for small units were often lack-
ing in sane size-which the carriers' surveys made up for. On
the other hand, carriers could not be asked to make counts for
long periods of time, or during the Christmas rush, for examle;
the officers could be.

The number of officers in pheasant range has varied from

year to year. In 1946 their numbers were low due to post-war

63

adjustments. In 1950, however, there were about 55 officers
in the 34 counties of the Department of Conservation's Region
III. Region III is composed of three districts. Since reports
of officers were handled through administrative channels, their
data were tabulated by these districts. Figure 4.3 compares
Region III, including these three districts, with the 38 coun-
ties that have been designated as primary pheasant range. Pour
counties on the northern edge of pheasant range in another ad-
ministrative region were covered by carriers and not covered by
officers.

As in the case of the carriers' tabulations, daily pheas-
ant observations have been tallied in terms of units of time,
rather than linear mdleage. This was a necessity, since officers
record mileage semddmonthly, usually by reading their car speed-
ometers. Asking (as we have tried) for daily mileage resulted in
unsatisfactory tabulation. Many neglected to mention it, and many
others had to estimate it. Since it was not part of their official
routine, it was neglected. In interpreting observations by two-
week periods, however, mdleage may be used, since that figure can
be assumed to be reasonably accurate. Even so, there is consider-
able evidence that officers' observations of birds per unit of
mileage is not so useful as observations per unit of time (i.e.,
observer-day). Officers' duties are seasonal, and at certain
times they may be checking for fishermen on lakes or walking trap-
lines in completely different habitat--so car mileage would be

meaningless.

 

  
  
   
 

 

 

 

 

 

 

 

 

 

 

 

 

 

64

 

 

 

 

 

 

 

 

 

 

 

 

  

 

 

 

 

 

 

 

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Fig. 4.3--Officers' administrative districts.

4.6

65

Surveys by Farmer Gosperetors
In the spring of 1948, the names of over 600 farmers who were

interested in conservation were obtained from county agents, of-
ficers, or district game managers who knew them personally. In
the spring of 1948, 1949, and 1950 the farmers were asked for in-
formation on nests and broods discovered during spring work,
particularly while plowing sod or mowing hay. They have been a
good source of information which in the past was difficult to ob-
tain. For examle, studies of clutch size, to be statistically
valid, must be determined from a large number of observations. In
Michigan, Rose Lake and the Prairie Farm combined had recorded
clutch sizes on less than 100 nests during the 13 years the station
had been in existence, and the 4 years the Prairie Farm had been a
study area. Yet in each of the 3 years the farmers cooperated,
they reported more than 100 clutches.

The number of nests in hay and sod are thought by some workers
to be indicative of net pheasant production for any year. Finding
pheasant nests is extremely difficult. Farmer cooperators have
given us good information on numbers of nests they found per acre--
data that would otherwise have been difficult to get on an exten-
sive basis.

The farmer cooperators appear to be an unusually interested
and responsive group. So far they have been canvassed only for
performance data (e.g., actual number of nests found per definite
number of acres plowed or mowed), which can be used objectively.
The group may be large enough, however, that they could be asked

for more subjective information, such as number of broads they see

4.7

66

on their farms each winter. I atteqted this, but was not satisfied
that I could convert their returns into usable information. Never-

theless, I feel this possibility should be explored further.

mm m

Kimball (1949) reported on a technique for extensive analysis
of the cock pheasant population in the spring by use of a crowing-
cock survey. Basically, this consists of running a 20-mile route
starting one-half hour before sunrise. Bach mile a stop is made
and all pheasant crows heard during a two-minute period are re-
corded. At the conclusion of each route the total or average nus-
ber of calls is calculated, and constitutes an index to the
abundance of cock pheasants along that route.

In 1948 I experimented with the.technique of the crowing-cock
survey in sale areas, and in 1949 set up a system of routes
covering the 38 counties in primary pheasant range.

These routes were not picked at random. Rather, they were
set up geographically to cover pheasant range. An attespt was
made to put one route in most counties in pheasant range. Where
one county obviously represented two types of range (Lenawee
County, for exaqle), we tried to set up two routes, one in each
type of range. This was not always possible, due to manpower
limitations.

We tried to run each route at least three times during the
spring. If weather conditions prevented accurate counts they were
repeated up to four or five times. This usually resulted in at
least one good count on each_ronte. We selected the maximum

figure for each separate survey as the value for that route.

4.8

67

Routes were run by biologists and wildlife student aides.
Considerable care was taken to train and select these men. In-
sofar as it was practical, a different person was used on each
of the three runs on each route each spring to minimise individual
differences in hearing. Individuals whose hearing was not well
tuned to the frequency of a pheasant cock's crow were not used.

Since geographical coverage was good, yg_a_r_ to may; cowarisons
of crowing-cock averages should be reasonably valid as an index to
the state-wide cock population. Since routes were not randomly
selected, however, coqarisons from £53 to ge_a must be made with

caut ion .

Surveys by Game Biologists
Came biologists and part-time student assistants on the

project helped in many ways, although there were so few of them
that their surveys could rarely be called extensive. In some
cases, however, (e.g., crowing-cock counts) we relied heavily

on them. At other times biologists could collect data at the
same time that other extensive surveys were being run, to add to,
or appraise, the extensive-survey data.

Biologists and students provided all the manpower for con-
tacts of sportsmen for hunter-performance data during the hunting
seasons.

There were many other instances where biologists were
responsible for collection of data extensively. Aging of pheas-
ants and counting of crowing-cocks, for exaqle, had to be done

by trained people, and only through the use of all available

biologists could we get enough data over large enough areas to be

4.9

68

meaningful.

Finally, we depended heavily on biologists for advice on the
type of information we should be gathering, the timing of surveys
based on the phenology of their districts, and on unusual circum-
stances that might be a clue to what was happening to pheasant

populations as a whole.

Smagy g; Conclusions

Linduska (1947) described the objectives of the extensive
survey, and the first carrier and officer surveys run in 1947.

Surveys by sportsmen proved valueless and were abandoned.

Per cent returns were low and they could not, as a whole, be re-
lied on to age pheasants accurately. The carriers proved to be a
willing group, and were used for three surveys a year--spring,
sinner and late fall. Officers could be used for longer periods
(all stnaer or winter) and their data were numerous enough to

be valid for several indices.

The carrier and officer surveys nicely coqlement one another.
Officers cooperated over long periods of time, but their operations
lacked bulk. Carriers furnished large eagles of data that the
officers could not match, but their surveys were infrequent and
for short periods.

Farmers were very cooperative and provided extensive data on
clutch size, brood sire, hatching dates, timing of certain agri-
cultural practices, and nest and brood density data.

Biologists were used for crowing cock counts, hunting season
contacts of hunters and for examinations of birds for biological

data. They also made some counts simultaneously with other

69

extensive surveys .

During the five years (1946-1950), about 60 extensive surveys
exclusive of hunter kill reports were made. They involved close
to 10,000 individual reports, involving many million miles of
driving and observations of close to a million pheasants.

Such extensive surveys are inexpensive to run, and involve
very little cash outlay. When the limitations of extensive sur-
veys are recognised, they are an excellent source of data at a

minimum of expense.

Chapter 5

SPRING POPULAIIONS

5.1 Introduction

The crowing-cock survey offers biologists a good method for
censusing cock pheasants. But estimates of spring breeding popu-
lations from the crowing cock count are dependent upon the sex
ratio of the spring population. Moreover, crowing-cock surveys
are limited by the availability of biologists. So there was a
need to attempt to develop other spring surveys-~to try to
determine breeding season sex ratios, and to try to find an
easier method for censusing cocks and hens alike.

In the spring the habits of cocks and hens differ. Cocks
display, and hens become progressively more secretive as they
begin to nest and become broody. So the relative observability
of the two sexes differs, and probably shifts as the spring
progresses. Determining true sex ratios, then, promised to be
a difficult problem. But a relative sex ratio from spring to
spring‘might have some use, if we could find a way to time the
counts so they could be made at the same time (phenologically)
each spring.

To get this spring population data, I set up an extensive
crowing-cock survey system and a system of extensive roadside

censuses to be run by the carriers.

70

71

5.2 growing-cock Surveys‘ggg Carriers' Surveys

The crowing-cock survey as it is used in Michigan was described
in Section 4.7. The location of crowing-cock routes is shown in
Figure 5.1, and results of the counts are shown in Table 5.1.

The latter are tabulated by study area. Relative abundance of
pheasants from area to area roughly follows our other data on
pheasant numbers (e.g. Area 1 high, Area 4 low'populations).
flhile sample size of data by area is rather small, this appraisal
of the spring cock population might offer a partial basis for
determining unusual winter mortality in an area, and for gaining
insight into relative rearing success for the areas.

In April, 1948 I asked the carriers to make an experimental
one-week survey. They recorded the number of pheasants seen
while driving their routes for a six-day period.

I attempted to time the survey so it would come at the
height of breeding activity. At the time it appeared to be a
good choice; crowing activity was good and breeding seemed to be
in full swing. But there was no method for timing the count since
no state-wide crowing-cock survey was run that year. The carriers
reported about 1,700 pheasants. Analyzing the data by study area
showed fair correlation with what we knew'of pheasant populations,
so the survey showed some promise.

Officers were not asked to make an April survey. Judging
from their winter counts, the officers were too few'in number to
gather an adequate sample. The April count had to be relatively
short, since pheasant observability was shifting rapidly. More-

over, the officers were making daily observations for the entire

 

 
 
  
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

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mm LAKE OSCLOLA CLAnc GLADVHN 9’ A 2
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Fig. 5.l--Location of crowing-cock survey routes.

73

 

 

 

 

 

 

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5.3

74

winter, and I did not want to wear out my welcome with them.
For the seven-year period 1949-1955, we have spring data
from crowing-cock surveys, and from two-week April surveys by the

carriers.

§2 2.9.9.2.:

The carriers recorded observations of cocks and hens sepa-
rately. For three years they also recorded observations of harems
separately from the other observations.1

Table 5.2 summarizes the carriers' observations, and Table
5.3 summarises the sex ratio observations, by area, distinguishing
the harem observations from all other observations for the three
years. Of course, these sex ratios are not necessarily true sex
ratios--quite likely they are not. However, they may represent
trends. These Observed sex ratios vary between what seems to be
narrow limits--1.3 and 1.8. Shick (1952) had observed "true"
sex ratios on the Prairie Farm as high as ten hens per cock
during years of high pheasant populations.

Observations on harems varied even less--between 2.1 and
2.4 for the three years! Also the frequency distribution of the
harem sizes was very similar for the three years (Table 5.4 and
Figure 5.2).

If our data onharem sizes is valid, there are two logical

interpretations we might make:

 

1A harem was defined as any hens seen in the neighborhood
of a cock. If no cock was seen in the vicinity, hens were not
considered to be a harem.

75

 

 

 

 

 

 

 

 

 

 

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77

 

 

 

 

 

 

 

 

 

 

 

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Per Cent Distribution

78

 

50
----- 1950 266 observations
1949 394 observations
—— 1948 155 observations
40 P'
30 P

20 f

 

 

_O
_-

l L 1 L

L 2 ‘3 4 S

. “r r
Harem Size 0 mo e

Fig. 5.2--Frequency distributions of harem sizes as reported
by carriers.

1) Size of harems may reflect true sex ratio while random
observations do not. If so, then it would mean the sex
ratio did not change significantly during the three-year
period.

2) It may be that the true sex ratio has little influence on
harem size, but that harem size is an "internal life '
history constant" determined by the biology of the bird
itself. In other words, cocks may select a certain number
of hens for their harems, little influenced by the number
of hens. Some pheasant workers have suggested that there
'may be a segment of bachelor cocks (without hens) in a
population.

The available evidence suggests that harem size may be a
‘more reasonable measure of the change in sex ratio from year to
year than the total sex ratio observations. However, sex ratios
based on harem Observations must still be regarded only as, -
observed sex ratios rather than'gygg sex ratios. I have no means

to convert the observed to true sex ratios.

57.4 Density

The crowing-cock counts should offer a good index to cock
pheasant numbers. They are more or less self-adjusting for
phenological timing. Routes are run several times during the
height of crowing activityb-which can be easily detemmined. 0n
the other hand, the carriers' count is set up well ahead of time
and is run at a predetermined time--which may not be phenologi-
cally identical to other years. So the crowing-cock survey must

be considered the more likély index to true spring numbers.

80

Table 5.5 compares the two indices for the seven-year period
during which they ran concurrently. They do not appear well corre-
lated. The inconsistencies between the two are very likely due,
then, to differences in _t_i_m_i_x_1_g of the carrier counts from year to
year. We can postulate that if a count is run a week later
(phenologically) one year than another, one would expect, at this
time of the year, that the later count would report relatively
more birds.

Let us assume for the moment that the crowing cock index is
a valid measure of the cock pheasant population, since the counts
are self-adjusting for phenology. He can assume that the two sur-
veys are both estimating the density of essentially the sane popu-_
lation of birds. Let us also assume for the moment that sex
ratios are somewhat the same for the years involved, and thus the
crowing cock index is measuring not only cocks but, to a large
degree, total birds.

We can plot the regression of the carriers' index on the
crowing-cock index (Figure 5.3) . Inspection of the points shows
that in four years (1951, 1952, 1954, 1955), the carriers' index
appears high. Three of these four counts were run at least two
weeks later than the others! If there was an expected acceler-
ation in birds seen as the season progressed at this time of the
year, we would expect these counts to be inflated.

If this expected acceleration could be measured, then adjust-
ments could be made for the different dates the surveys were run.
In 1950 I had asked the carriers to record their observations by

day. These are su-aarized in Table 5.6. The mean of the second

TABLE 5 .5

ADJUSTMENT 0F CARRIERSo DENSITY INDICES

T0 COMMON STARTING DATE

81

 

 

Deviation
From Adjusted
Year 1);: 52:11: April 5 Growing Carriers ' Carriers '
7 (days) Cock Index Index1
(d) Index (c) (x)
1950 3 - 2 9.7 7.87 8.55
1951 16 +11 11.8 16.81 11.67
1952 14 + 9 12.7 18.53 13.63
1953 6 + 1 11.2 12.91 12.41
1954 5 0 11.4 20.75 20.75
1955 18 +13 12.5 26.04 17.13

 

 

 

 

 

 

1
Adjusted by the formula x = ITE'W , on the basis that values
of c are inflated by 4 per cent per day after April 5 (see text).

Crowing Cock Index (y)

82

 

 

— Phenology ,/ p
14 —n‘ . 5 days late/ 9da l
ya 52
— / . / 13 days '55
12 — l a 8'
_ ‘454
'50 A $1...
10 _ ’ 2 days/ _./ '53
- /
s _ / ,
_ / - '49
6 " /, /\ 1 day
4 _ / / Phenology 5 days early
_ //
2 — //
)—
l I l l l I l 1 l l l l l I l l l l
0 2 ' 4 6 8 1o 12 14 16 18 zoJ—LLzz "L24" 1‘6

Pheasants Seen per 10 Carrier-days (x)

Fig. 5.3--Relationship of crowing-cock index to carriers'
spring density index, adjusted to common starting date (April 5).

83

TABLE 5.6

DAILY PREASANT OBSERVATIONS BY CARRIERS
SPRING, 1950

 

 

 

‘.
April Cock! Rena Daily Total Birds
Observed Observed Sex Ratio Observed
' 3 136 227 1.67 363
4 99 176 1.78 275
5 110 206 1.87 Av. 316 Av.
6 118 186 1.58 1.74 304 327.0
7 134 243 1.81 377
8 120 207 1.73 327
26:61 717 1,245
10 155 301 1.94 456
11 122 235 1.93 357 Av.
12 149 213 1.43 Av. 362 419.5
13 144 240 1.67 1.59 384
14 173 253 1.46 426
15 229 303 1.32 532
Tbtal 972 1,545
26:61 1,689 2,790 1.68 4,479
Average ' ' ' 373.25

 

 

 

 

 

week's observation of birds was 28 per cent higher than the first
week's--an average increase of 4 per cent per day.

I then arbitrarily assumed a ratio of 1.0 of crowing-cock
index to carriers' index. Using this arbitrary regression line
of y I x and the crowing cock index intersect for the mean, I
adjusted this mean by 4 per cent for each day the counts were
started after (or before) April 5. The points were all adjusted
then, as if the counts had all started on the fifth of April--
assuming, of course, this 4 per cent daily expected increase was
legitimate. This brought the points for 1951 and 1952 well
within the grouping of the others: but left the 1955 point still
considerably out, as well as the 1954 point, which received no
adjustment.

If this relationship of the two indices was real, we could
expect them, that phenological differences might be the most
likely reason for the points for 1954 and 1955 to be non-conform-
ing. For these points to be high on the carriers' index side
would mean that phenology was early those years, the breeding
cycle was more advanced, and hence the carriers saw proportion-
ally more of the population.

' Inspection of the weather records showed that, indeed, these
springs _w_e_r_e early.

In 1954 the Michigan average temperature was 2.6° F. above
normal in April, l.l° F. below normal in March. But February was
9.90 above normal-9.95 warmest Februagy g M! April, 1955,
was 7.6° above normal, the warmest April. _o_n 3553351! Thus,

phenology may be largely responsible for this inflated carrier

5.5

'85

index in 1954 and 1955. And it may well be that a good corre-
lation exists between the carriers' and the crowing-cock indices.

This comparison is necessarily crude and cannot be the basis
for prediction. One might determine the relationship by multiple
regression of (1) carriers' index on (2) day (chronology) of the
count (or deviation from.a mean day) on (3) crowing-cock index.
But another unmeasurable unknown remains--the effect of phenology.

Limits allowing for 5 day's variation in phenological timing
of counts (shown as dotted lines on each side of the regression
line) include all the points except 1954 and 1955. Counts those
years would be about two weeks early phenologically if the 4 per
cent daily increase were valid at all population levels and at
any period of April: which is extremely unlikely.

- While the case for this relationship borders on the emperi-
cal, it seems to be rational. No further study of it seems worth-
while until we are able to obtain more data by which we can
determine more certainly how this daily expected increase in
observations may work. In addition, the assumption that sizable

sex ratio changes are not occurring must be supported.

gonclus ions

The crowing-cock index is considered the best measure of
spring cock populations, since crowing-cock counts are self-
adjusting for phenology.

Observability of pheasants increases (apparently at a-rate

of about 4 per cent per day) during early April. Carriers' spring

86

pheasant density indices correlated well‘with crowing-cock
indices when adjusted phenologically.

Harem size as observed by carriers is more stable than sex
ratios based on all observations. Frequency distributions of
harem sizes were very similar for the three years they were
determined. Harem size may be a better measure of sex ratios

than all observations.

Chapter 6

BIOOD PRODUCTION

6.1 introduction

Perhaps the most important and most profitable aim of the
game manager is to encourage brood production. Pheasants are
essentially an annual crop, and the success of a fall hunting
season depends largely on broods produced in the summer.

Decreased brood production appears to be the principal rea-
son for the pheasant depression in the mid-forties. Starting in
1945, in three years Michigan's pheasant population dropped to a
third of a previous level it had taken 8 to 10 years to reach.
No unusual mortality to adults was noted. Even the abrupt
removal of perhaps a third of the population during a three-
week hunting season has no appreciable effect on pheasant popu-
lation trends (Allen, 1947) .

Since the ultimate determination of a fall population is
essentially by broods produced the smmser before, an accurate
measurement of brood production is perhaps the most important
statistic to the guns manager who must set fall hunting regula-
tions in the tuner. Intonation on the number of broods, the
number of chicks in the brands, and the survival of these chicks

to the fall hunting season is needed. Ultimately we are looking

87

88

for a method for predicting from.summer populations the number of

pheasants available for the fall harvest.

6.2 .ggggg Production

In the summer of 1946, Linduska made the first exploratory
extensive brood counts. Carriers and officers in pheasant range
‘made semi~monthly counts in June, July and August. The counts
were alternated so that the officers counted the first half and
the carriers the second half of each month. The brood density
indices for these surveys are shown in Figure 6.1. Although we
have no way of knowing the relation of these density indices to
each other, there is an obvious increase in number of broods
seen as the summer progresses. It can be assumed from this
graph that broods will probably be seen in greatest numbers from
the middle of July to the middle of August. In June, many broods
are still hatching and not so readily seen at that stage. 0n the
other hand, broods begin to break up in late August.

In 1947 both officers and carriers made only one count--in
the last half of July. After a thorough study of the 1946 and
1947 data, I decided to ask the carriers for only one count, in
late July, and to have the officers count by semi-monthly periods
during the months of June, July and August. The count made by
the carriers would provide a large sample. (In late July, 1949,
for example, carriers saw nearly 2,000 broods during the same
period the officers reported 183.) The officers' counts, covering

the entire summer, might provide a.timetab1e for brood observa-

89

10 -
A Broods per 1,000 miles seen by officers.

9 - O Broods per 10 carrier-days seen by
; carriers.
h A
'§ 8r-
9
o
v. 0
E 7 r
o
53 ‘0
u 6 '—
o
8
:1 5 —
s
§. 4 r ‘
F!
u
3. 3 L-
'3
:5 2 P A .

1 L-
L, l l I l I

 

 

1-15 16-30 l-lS 16-31 1-15 16-31
June July August

Fig. 6.l--Brood density indices as reported by carriers and
officers,’l946.

90

bility. If so, then carriers' counts might be more accurately

compared from year to year.

6.3 Timing _o_f Brood Surveys
Figure 6.2 shows the brood density indices determined by

officers for four years. In l948,the number of broods observed
in the last half of August increased. In 1949 and 1950, the
number of broods observed in the last half of August dropped,
which may be a reflection of the scattering of broods as the
chicks mature.

Aside from the drop in late August, brood observations seem
to follow a very consistent pattern from year to year. The
regression of these brood density indices on periods of the
summer up to August 15th is also shown in Figure 6.2. The slope
of the regression line represents the rate of increase in number
of broods seen as the season progresses. From this slope (or
perhaps a similar slope for a shorter period of time) one could
predict the expected daily increase in brood observability. A
one-week difference in timing of brood counts might mean a
difference of perhaps 10 per cent in the counts.

In 1949 and 1950, the carriers' tally forms were designed so
that each day's observations were recorded during their count.
The counts followed a pattern of daily increase in broods similar
to the regression line of the officers' counts in Figure 6.2.

The mean daily broods observed each week’increased from the first
week to the second week by 1.83 per cent and 1.48 per cent per

day, in 1949 and 1950. respectively, with coefficients of varia-

Broads Seen per 1000 Miles of Travel (y)

91

f

. ' /

/ y I 0.71+1.34x

\

 

 

l l I l I
1-15 16-30 1-15 16-31 1-15 16-31
(1) June (2) (3) July (4) (5) August (6) (X)

 

Fig. 6.2--0fficers' brood density indices.

6.4

92

tion of 10.1 per cent and 1225 per cent respectively. This rate
is about what one would expect from the regression line in
Figure 6.2. Examination of data in 1958 and 1959, collected in
the same manner, showed no such increase, however. Average
broods observed each day during the first week were almost the
same as averages for the second week, in both years. Apparently
a two-week count is too short to show this increase in all years.

Klonglan (1955) and others (Bennett and Hendrickson, 1938;
Randall and Bennet, 1939; Koaiky ‘gt‘gl;, 1952) have reported
that precipitation may have a strong influence on early morning
roadside counts. Klonglan states that even rainfall the night
before a count caused wide variation. I made a gross comparison
of daily rainfall during the carriers' late July brood counts
and could see no consistent relationship between rainfall and
number of broods observed.

Daily brood observations by carriers, for two representative
years, are graphed in Figure 6.3. The population was about
average in 1949, high in 1958. A synopsis of precipitation each

day across southern Michigan is included.

mete
It has been a common suspicion that one reason for differ-
ences in pheasant production from year to year might be a differ-
ence in the average number of chicks in each brood brought to
maturity.
I As a result of this study, based on reports of over 15,000

broods by carriers and officers, I conclude that this suspicion

93

 

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Ann
ensue N . swam h>uo=
ensue n n swam unwwu
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mound e . anon h>uom
I
hue
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mun
mun
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/ .05
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mmouo n u :«o& .uq
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0 0 0 0 0 0 0
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2
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mm
Va
71
In
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B
1
1

Fig. 6.3-~Carriers' daily brood counts compared with

precipitation.

94

is not well founded. I could find no evidence from these
extensive counts that annual changes in brood size had any
appreciable effect on total pheasant production.

Since brood size would be expected to vary with age of the
brood, and since broods are produced later (or earlier) some
years than others, carriers and officers were asked to estimate
the approximate age of the broods they observed.

This posed a technical problem in instructing large numbers
of untrained cooperators by correspondence. This was done by
specific instructions and comparisons with other birds, such as
robins, quail and crows, and by the use of visual aids. I do
not know the actual average age of l/4-grown chicks, for example,
as they are recorded by carriers and officers. But one can
expect that with the large bulk of observations and about the
same group of cooperators each year this actual age, whatever it
is, should be the same from year to year.

In addition to separating broods by age, I felt it was also
necessary to compare brood sizes which were determined during a
rather short period of time. Even though the chicks are aged
correctly, brood sizes obtained by lumping data from the three
months of June, July, and August, must be used discriminately.
For example, in 1946 carriers observed 357 1/4-grown broods in
the first half of June, for an average reported brood size of 8.4.
In the first half of July that year, they observed 525 l/4-grown
broods for an average reported size of 6.7, a difference of 1.7
chicks! This difference may be real, or it may be in part due

to differences in cover conditions and hence visibility of the

broods.

95

Finally, I felt that any study of brood sizes should
involve large numbers of observations. With an average which
could be expected to be somewhere around 6 to 8 chicks, with
sizes varying from 1 to 20, the variation might be expected to
be large.

The sizes of 8,787 broods observed by carriers in late July
are shown in Table 6.1. Brood size does not appear to shift
appreciably from year to year. The differences the table does
show could be largely a reflection of sampling variation. The
larger spread shown by 3/4-grown broods is suspect because
phenology from year to year might cause a differential due to
chicks maturing and leaving the brood. Ignoring 1946, the spread
is only .41 chick, comparable to the l/Z-chick variation in
quarter and half-grown broods.

There is one obvious reservation to the conclusion that
brood size does not change significantly--there is no way of know-
ing how accurate the carriers' counts are. The final proof of
their accuracy'must lie in performance. This is discussed in the
next chapter. Some insight into the reliability of the carriers'
brood sizes might be provided, however, by inspection of the
frequency distribution of their observations.

In Figure 6.4, the frequency distribution of observations of
1/2-grown broods for four years is graphed. With no attempt at
this point to evaluate this distribution statistically, there is
evidence that the carriers are not just guessing at observations.
The curves are roughly similar from year to year. There is not

much evidence that they are prone to lump observations in the

TABLE 6.1

SIZE OF BROODS REPORTED BY CARRIERS

96

 

 

 

 

 

Year 1f4 Grown 1/2 Grown 3/4 Grown All Broads
1946 6.23 1 6.21 5.97 6.14
(497) (899) (654) (2050)
1947 6.65 6.48 5.38 6.36
(286) (335) (128) (749)
1948 6.45 6.38 5.08 6.12
(565) (804) (379) (1748)
1949 6.22 6.10 5.08 5.88
(568) (957) (509) (2034)
1950 6.67 6.63 4.97 6.34
(774) (1031) (401) (2206)
5 Year Av. 6.44 6.35 5.36 6.14
.45 .53 1.00 .48

Tot . Spreafl

 

 

 

 

1Figures in parenthesis are number of broods on which

each brood size is based.

Number of Broods Observed

 

~\ ,.
$1 I! 4

60- I ,’ \ \

 

[I ‘~
F \
.8 I ’1 \
I \
\
s.s '. . \
.0 s. .' .. \

e. .0 ' 5's, s

. '.’.9!?-' ~.,...--..\'/\

'0. V "O.‘.‘\
‘\

O. O
s' a.“ ‘
a..\\ is : _\

 

O. \
0' he).

has 1 1 e1. e11. 1 14, l Alleelle l "'.4,' J. _ ’ c

0 5 10 15
Number of Chicks in Broods

e
I

Fig. 6.3--Frequency distributions of sizes of half-grown-
broods observed by carriers.

97

6.5

98

"5" or "10” categories, as so often happens (although there is a
slight tendency for even numbers to be higher than odd).

Further analysis of brood size could be pursued; logically,
brood size should be compared by study area. That is not in the
province of this study, however, since we are interested in
brood size principally for its effect on estimates of total popu-
lations. L. L. Eberhardt analyzed brood sizes based on the data
in Table 6.1, as well as similar data from later years, and
concluded that brood size appeared to have no significant differ-
ence from year to year, but did have significant variation from
area to area.1 Even so, there is still no way of knowing whether.
these differences are real life history phenomenon, or merely
differences in simple observability of pheasants. There are
obviously rea1_differences in cover conditions between the flat
open land types of the lake-bed clay country and the rolling,

brushy types in southwestern‘nichigan.

Percentage _9_f. fling Without M

There has been a suspicion in Michigan that loss of pro-
duction has been fewer broods produced for some reason or
another, rather than differences in the degree of attrition of
chicks from broods. The studies of brood size in the previous
section support this suspicion.

During these July brood counts carriers were asked to record

the hens they saw which apparently had no broods. Those hens

 

IUnpublished data in one Division files.

99

which have not hatched a brood by late July are extremely
unlikely to contribute many young birds to the shootable fall
population. A cock hatched on the first of August would hardly
be colored enough by mid-October to be easily recognizable in
the field as a cock.

Data were tabulated as percentage of hens seen that had no
visible broods. For the five years of this study, this

percentage was as follows:

1946 411
1947 471
1948 372
1949 351
1950 371

For the two years with poorest pheasant production, 1946 and
1947, these percentages were highest, so this percentage may
reflect production in a general inverse way. Its specific use as
an indicator of production, however, is doubtful at this time.
Observability of hens with or without broods may vary, so this
percentage may be an index rather than absolute. The best evalu-
ation of this percentage must wait until we have a reliable index

to true productivity based on true fall age (and sex) ratios.

6 . 6 gonclusions
Brood counts increase at a predictable rate during the summer
period. Counts are apparently not appreciably affected by rain-
fall. On the basis of nearly 9,000 observations of broods by
carriers, no significant difference in brood size from year to
year could be detected in a five-year period. The percentage of
hens without broods observed may reflect good or poor production

years, but is probably not usable to calculate specific productivity.

7.1

7.2

Chapter 7
PREDICTION OF FALL KILL FRON.SUHMER.BEOOD COUNTS

Introduction

The principal reason for the search for an accurate measure
of pheasant populations in mid-su-er was to find a method for
predicting fall populations, as a basis for setting hunting season
regulations. During the first fewryears of the summer brood
counts, there appeared to be general correlation between increase
and decrease of the brood counts, and increase and decrease of the
kill during the corresponding fall. This general correlation
seemed to exist for the study areas as well as for the entire
stltO.

In 1949, with four years of data to work'with, a series of 16
different correlation coefficients were calculated, analyzing the
data on the basis of county, area, and year, and weighting the
areas on the basis of size. values of ”r" for these correlations
are shown in Table 7.1. These values are not particularly per-
tinent not useful, except to show that excellent correlations
existed, even on the individual county level; none was below .65

and 9 of the 16 were above .90.

Correlation of Carriers' Brood Counts with Cogputed Kill

The regression of computed kill on broods seen by carriers by

study areas for the four years 1946-49 is shown in Figure 7.1.

100

101

TABLE 7.1

VALUES 0! CORRELATION «EFFICIENTS (1') FOR 16 COMPARISONS 0F
COMPUTED KILL WITH CARRIER EROOD DENSITY INDICES

 

 

 

 

 

 

D‘t‘ L‘V‘I 60:3:1:ted 23ingf Velzes
County 1946 27 .99
1947 28 .95

1948 38 .65

1949 37 .85

1946-49_ 130 .79

Year Area 1 4 .98
Area 2 4 .65

Area 3 4 .97

Area 4 4 .99

Area 5 4 .74

Area 1946 5 .97
1947 5 .88

1948 5 .93

1949 5 .90

1946-49 20 .91

Area

(weighed) 1946-49 20 .93

 

 

 

 

Computed 'Cock Pheasant Kill
per Square Mile (y)

102

70

y . 3030 * 7.328

 

 

1 I l 1 1 l 1 l J_
1 2' 3 4 s 6 7 8 9

Broads Seen per 10 Carrier-days“)

Fig. 7.1-~Regression of computed kill an carriers' brood
density indices for study areas, 1946-49.

103

This regression line could obviously be used to predict fall kill
from the carriers' brood counts.

The four years used in these correlations represented rela-
tively low pheasant populations, however, and assumed a straight-
line relationship. The regression formula shown in Figure 7.1
might not necessarily be valid for predicting kill an the basis of
carriers' brood counts during years of higher pheasant populations.
Following 1949, carriers' counts in July were continued each year
in the same fashion, and at the same time the pheasant kill was
coquted from hunter report cards through 1956, when the system
was discontinued and replaced by a sampling system.

On the basis of 11 years of data, the relationship between
carriers' brood observations and computed kill the following fall
can best be shown by the regression illustrated in Figure 7.2,
where computed kill is plotted against the logarithm.of broods
seen per lO-carrier days. The correlation coefficient is .978--
an extremely close correlation. Since there is an unknown
saqling error in each of the measures involved in this correlation,
this "r" value may be less than the true correlation. Neverthe-
less, its usefulness in predicting fall kill from sus-er brood
counts is obvious. Table 7.2 shows the detail in support of
Figure 7.2.

Figure 7 .3 coqares the coquted kill with broad density by
area for the 11 years. There is, of course, more spread since the
areas involved are smaller. Because of the likelihood of dif-
ferences between areas (such as broad size mentioned in Chapter 6

and discussed in the next section), it is iqractical to calculate

104

1400 "

1200 '-

   

1000 y = 44 + 1275:

  
  

800

600

400

Cosputed Kill in Thousands (y)

 

200

  

l 1 1 g l A L 1 1 J
.100 .200 .300 .400 .500 .600 .700 .800 .900

Logarithm of Broads per 10 Carrier-days (1:)

Fig. 7.2--Regression of computed kill an logarittm of carriers'
brood density index for primary pheasant range, 1946-1956

mm: 7.2_

RECRESSION 0F CONFUTED RILL 0N LOGARITEH 0F CARRIERB'
EROOD DENSITY INDICES

 

 

 

 

 

 

Broads per Log Broads Kill
Year 10 C. D per 10 C. D. In Thousands
“ (X) (Y)
1946 5.04 .7024 904.4
1947 2 . 25 . 3522 452 .9
1948 2.97 .4728 632.7
1949 3.61 .5575 864.0
1950 3 .60 .5563 797 .5
1951 5.74 .7589 943.7
1952 5 .49 .7396 947 .9
1953 7.27 .8615 1,144.9
1954 7 .68 .8854 l ,178 .4
1955 7.86 .8954 1,230.7
1956 6.74 .8287 1,101.0
Sins 7.6107 10,198.1
Means . 69188 927 .1 00
Y s 927.100 - 882.348 + 1275.29! r .-. .978

 

 

 

105

106

 

 

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Fig. 7.3--Coqarison of computed kill with logaritlm: of carriers'
brood density index for study areas, 1946-1956. -

7.3

107

the regression on the basis of these points; rather, regressions
should be calculated separately for separate areas, or groups of
similar areas, when enough data have been accumulated.

To illustrate this likelihood of differences in regression
between areas, the points for the two most diverse areas--2 and 4--
are identified in Figure 7 .3. Regression formulae calculated for
each would be quite different.

On ths basis of the regression shown in Figure 7.2, and with
the benefit of hindsight, one can calculate how accurately the kill
might have been predicted from carriers' brood counts for the 11
years involved in the regression. Table 7.3 shows the deviation

from the regression for the individual years .

This method of predicting fall kill may appear disarmingly
siqle. It by-passes s amber of factors or considerations, or
makes a nmsber of assmtions which are not particularly proven.
The proof of the system is in its performance.

Six of these factors are discussed briefly below. It must be
remembered that the siqle fact that the system works is not proof
of any of these assulqtions. I do not know to what extent errors
introduced by one factor might be cmensated for by another.
Nevertheless, the fact that none of these considerations has
seriously skewed the regression curve in the 11 years involved lends
support to tentative conclusions regarding them.

In essence, one must assume a consistent relationship between
the broods present in late July and the October population from

year to year. If the following factors are not cogenssting, then

TABLE 7.3

108

ERROR.IR PREDICTION OF’COHPUTED KILL FROM CARRIERS' EROOD

DENSITY'IRDICES

 

L A

 

 

 

Kill in Thousands Approx. Error in

Year Per Cent of

Predicted Computed Computed Kill
1946 935 904.4 32
1947 495 452.9 81
1948 645 632.7 22
1949 750 864.0 152
1950 750 797.5 61
1951 1,010 943.7 62
1952 985 947.9 41
1953 1,140 1,144.9 01
1954 1,175 1,178.4 02
1955 1,180 1,230.7 42
1956 1,095 1,101.0 1%
Av. 42

 

 

 

 

109

each, in turn, must be quite consistent from year to year.

1) Let; m1; mortality. Following grain harvest in mid-
July, when most chicks are at least half-grown, mortality to young
caused by weather or food shortage should be at a minim. Bar-
ring an epizootic or similar catastrophe, mortality would logi-
cally be expected to be consistent from year to year.- This is in
sharp contrast to the preceding period, from the breeding season
through hatching, when weather and even food conditions could con-
ceivably alter mortality radically from year to year.

The fact that the size of l/2-grown broods observed by car-
riers does not change appreciably from year to year would suggest
that mortality to chicks in the early smr, when chicks are
small, must operate principally on whole broods rather than indi-
vidual chicks. Thus, our conclusion that loss of pheasant pro-
duction seems to operate on the entire brood or the hen before she
brings off a broad rather than attrition to individual chicks.
Small game hunting license sales and resulting hunting pressure
in Michigan are high enough that pheasants are probably hunted
to the point where a 10 per cent change in hunting pressure would
not greatly change total kill. License sales changed less than 5
per cent each year in 6 of the 11 years, and in 2 other years the
change was less than 8 per cent (see Figure 2.1). The year 1946
was a striking exception; sales were 25 per cent higher than in
1945 and 22 per cent higher than in 1947. This increase is
generally credited to the interest of returning servicemen in 1946,

many of whom may have had a particular interest in hunting that

110

year which dissipated in following years. In many ways, the
1946 data were more at variance with the ”average" than other
years. Season length and bag limit were reduced in 1947, 1948
and 1949 (see Figure 2.1).

About 70 per cent of the present 22-day season's total kill
usually occurs during the first two days and the first weekend.
So even the lz-day season in 1947 and 1948 was probably enough to
harvest the pheasant crop, and the total kill was probably but
little less than it would have been had the season been 22 days
long those years. This is especially true since during these
three years of restricted seasons pheasant populations were low.

Regulations have specified various opening hours, particu-
larly on the first day or two of hunting. This has apparently
affected total kill but little. Analysis of the Bass Lake data,
where data from previous years were available for coqarison, did
not show any change in total season kill traceable to a change in
opening hours (Black, 1950).

Hunting conditions are popularly supposed to have consider-
able influencs on the harvest of cocks. The conditions most
regularly mentioned are weather (principally rain, temperature,
moisture conditions on the ground, snow cover and wind) and cover
(amount of standing or unharvested corn, lushnsss of the season's
growth, and whether or not there have been frosts heavy enough to
knock down some herbaceous growth). Although hunters may fancy
that these things affect their individual success, I was not able
to detect any measurable affect these conditions have on total

state kill for any season. Quite probably these conditions are

111

less influential than the average hunter supposes, and quite
probably the conditions vary nuch less than he supposes.

3) £59. r_a_§_i._9_s_ 2; 9935 gill. Deter-ninetions of ages in the,
fall kill show a shift as the season progresses (see Chapter 8).
True age ratios of the fall cock population are unknown. Yet a
year of good brood production will ordinarily have a higher per-
centage of young birds in the fall than will a year of poor pro-
duction. Since the fall kill is so dependent upon the young cocks
of the year, one night suppose that changes from year to year in
the percentage of young cocks in the Isle seg-ent of the popu-
lation will upset this correlation.

The effect of a change in age ratio need not be as influ-
ential as one night suppose, however. It is con-on to have very
disparate observed age ratios in the kill--perhaps as high as
1 adult to 15 or even 20 young. In these instances, adults would
coqose fron 5 to 7 per cent of the kill. Thus, though a chang-
ing nuaber of adults caused a shift of age ratio from 1:15 to
l:20--a 33 per cent change in nmbers of adults--the net change
in the kill would be only 2 per cent. If, of course, the number
of adult cocks stayed the seas and the shift was caused by a dif-
ferent nuaber of young, this would be a net change of about 33
per cent-~but that would be measured in the carriers' brood
density index. It may well be that the net percentage gain or
loss of the adult proportion of the kill is not large in any one
year, and hence does not greatly influence the correlation.

4) §_i_._r_e_ o_f_ gm. Brood size apparently does not change

appreciably fran year to year in Hichigan.($ection 6.4).

112

As a further check against the influence brood sise night have,
correlations of brood size with carriers' brood density indices and
with coquted kill for eleven years were calculated (Table 7.4).

No significant correlation was found.

5) Precision and accuracy of M surveys _an_d coguted ki_l_._l_.
There is no clear-cut neasure of the precision of each of these
population neasurenents now available. Each is a saqling systen--
each has a seqling error. Again, we lust fall back on the per-
foraance of the systen to deteraine its usefulness. The likelihood
that the coquted kill is a useful index to actual kill was dis-
cussed in Chapter 2. The accuracy of the brood density index is,
in turn, deterained by how accurately we can predict the kill fro-
it.

6) gi_a_ing g_f_ 52; E229. survey. The isportance of tining
brood surveys was discussed in Section 6.3. Deter-lining the pheno-'
logical status of pheasant brood production is extra-sly difficult.
The dates in July that I picked for the carriers' surveys each
year were carefully weighed in the light of that spring's phenology.
we do not know precisely how phenology affects pheasant breeding. '
But if the peak of cock crowing, for exane, appears to be a week
later one year than another, it would be reasonable to try to run
the nail carrier counts one week later.

The opening of the pheasant season was changed fro- October 15
to October 20 in 1952. The population is undoubtedly a trifle *
lower on October 20 than on October 15.

issuing the 1.65 per cent daily expected increase in broods

seen by nail carriers (Section 6.3) is valid, the 15 per cent

TAIL! 7.4

COIIILAIIOIS O! BROOD SIZE AND THO POPULAIION INDICIS

113

 

 

 

 

 

 

 

Broads Seen
Kill in per lObCarrier Average
Year Thousands Days Brood Size
(*1) (x2) up
1946 904 5.04 6.4
1947 453 2.17 6.3
1948 633 2.85 6.2
1949 864 3.63 5.9
1950 793 3.60 6.3
1951 944 5.74 6.2
1952 948 5.49 5.9
1953 1,145 7.27 6.1
1954 1,173 7.63 6.1
1955 1,231 7.36 5.9
1956 1,101 6.74 5.8
13,133 g -.546 r05 . .602
l3|:2x3 a -.474 1'05 3 .602

114

maximum error in our predictions (Table 7.3) could have been ac-
counted for by a lO-day timing error in mail carrier counts.

All of these seven variables are capable of introducing error.
Some, such as hunting regulations, may vary with population levels
and be automatically coqensated for; others may cogensate each
other. The sum total of these errors, however, must be contained
within the error shown by the regression in Figure 7.2. Cor-
rection of the possible errors mentioned above can only refine
this regression which. as it now is, appears to offer good in-
formation.

In the final analysis, one strong proof of both the kill
figures and the carriers' brood surveys is their consistently
small deviation from the regression. It would quite likely be re-
warding to try to coqensate for some of tlmse errors--particularly
timing of the counts. But to be able to predict fall kill from a
su-er count with an error averaging 4 per cent is a rare and

satisfying experience for the game manager.

8.1

Chapter 8

FALL POPULATIOUS

Introduction

In Chapter 2 the computed kill figures were appraised, and
in Chapter 7 it was shown that there was an extremely close
relationship between the number of broods present in the summer
and the fall kill. This demonstrated that the fall kill is
almost directly dependent upon the brood production the previous
summer. Adult birds contributed either so nmall or else so 4
consistent a proportion of the kill that they did not seriously
affect this relationship.

It follows then, that total kill, accurately determined, is
a good index to the fall population. If we knew’the fall sex
ratio, and if we knew what percentage of the fall cock population
was harvested, it would be possible to calculate the fall popu-
lation.

This chapter deals with other indices to the fall kill,
attempts to determine.pheasant numbers by other than total fall
kill computations, and attempts to determine fall sex and age

ratios.

Preseason Sex Ratio Surveys

In the fall, just prior to the hunting season, the sex ratio

of a pheasant population is usually close to 1:1. Despite the

115

116

fact that pheasants are polygamous, and that in a hunted popu-
lation a sisable percentage of the cocks are removed each fall,
young of the year about equally divided as to sex are the pre-
ponderant part of the fall population. ‘Horeover, the disparate
sex ratio of adults in the winter is probably brought closer to
1:1 during the sus-er by a higher mortality of hens, due to the
increased hazards of nesting (mowing machines, increased v’ulnere-
bility to predators, etc.) .

£95 3.33.3 observations _og gyening _d_gy _o_f hunting _s_e_g_s_o_n.
The most couon attempt to get a preseason sex ratio has been
from sight observations of pheasants by hunters on the opening
day or days of hunting seasons. Allen (1942) devised a system
for calculating preseason populations, in which opening day sex
ratio observations played a part. while such observations have
some merit, they have two drawbacks. (1) Observations col-
lected from a large number of hunters are not particularly
accurate, especially when large numbers of pheasants are observed
in a day. (2) The removal of cocks by legal hunting during the
observation period, even though it be for a period as short as
one day, prejudices the ratio in favor of hens. This is a
serious handicap when opening day pressure is heavy, as it is
each year in almost all of Michigan's primary pheasant range.
It has been a common occurrence for one-third of the total pheas-
ant kill to be taken on an opening day. On the Prairie Farm, for

example, the percentage of the total kill that was taken opening

117

day for a number of years was as follows:
(Shick, 1952)

1937 1938 1939 1940 1941 1942
192 381 501 33% 351 302

Similarly, during the eight-year period 1951-1958 at the
Rose Lake‘flildlife Experiment Station, an average of 34 per cent
of the total season pheasant kill was taken on the opening day.

- In Table 8.1 observed sex ratios on opening days at the
Prairie Farm and Rose Lake are compared to the calculated preseason
population for a number of years-~some of high pheasant popu-
lations, some of low. There does not appear to be a correlation
between relative abundance of birds and the disparity of the sex
ratios.

It is likely that there is a considerable error in these
opening day observations.

Preseason roadside counts. In 1948 officers were asked to
keep track of the pheasants they saw from September 15 to October
15 when the pheasant season opened.

Since there were certain to be many birds in broods too
young to be sexed, observations of these young were recorded
separately. Half of these young birds could be assumed to be
cocks, half hens. The total of such observations was halved, and
half added to the cock tally, half to the hen. Results are shown
in Table 8.2.

These results are implausible. The total number of birds
' observed per mile of travel dropped far below the July brood

counts, indicating that the birds were relatively more difficult

TABLE 8.1

OBSERVED SEX RATIOS ON OPENING DAYS

 

 

 

 

Prairie P'arm1 Rose Lake2
Calculated Calculated
Year Opening "Preseason Opening FPresaason
Day Cock Day Cock
Sex Ratio Population Sex Ratio Population
(Hens/Cock) per 100 A. (Hens/Cock) per 100 A.
1937 1.2 13.7
1938 1.4 21.4
1939 2.0 20.4
1940 1.6 17.5 .9 18.0
1941 1.0 22.9 1.3 31.7
1942 1.4 19.9 1.3 16.7
1943 1.3 11.6
1944 1.0 1536
1945 .7 7.3
1946 1.3 5.2
1947 1.2 4.4
1948 1.4 6.2
1949 .9 6.5
1950 .S_ 5.2

 

 

lsma (1952) .

2Rose Lake files.

 

 

 

118

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120

to see at this time of the year. Even at this date, pheasants
appear to be segregating by sex, to some degree. In many broods
so young that the cocks were only partly colored, it would
obviously be very easy to mistake a young cock for a hen.

Shick (1952) was unable to obtain a satisfactory preseason
sex ratio from field observations on the Prairie Pena. Stokes
(1954) attempted to obtain a preseason sex ratio on Pelee Island
in the late 40's. Three different types of sampling he tried
resulted in three widely differing sex ratios, none of which
seemed plausible. He laid part of the difficulty to the fact
that cocks were engaging in fall sexual display at this time of
the year, and hence were disproportionately obvious to the road-
side counter.

This type of survey was abandoned. It does not seem to
warrant further study.

_§_e_x 59533325333 _o_n_ 35335! M. It has been suggested .
that a sex ratio might be obtained from the July brood counts
by assuming equal division of the chicks as to sex, and adding
those data to the counts of hens and the estimated cock popu-
lation. 'He have no way of knowing whether survival of broods
is similar to survival of adults from.1ate July to the hunting
season, nor do we have valid data on the adult sex ratio at that
time of the year, nor can we be confident that the observability
of hens with broods is at all stellar to that of hens without
broods. Hence, I dismissed the possibility of determining a

sex ratio at this time of year from brood counts.

121

During the 1948, 1949, and 1950 hinting season, biologists
and student aides interviewed hunters for bag checks, and aged
several hundred cock pheasants in the bag each year. Bursa
measurements, supported by the mandible test, were used (Linduska,
1945; Figure 4.1) . Although ages were recorded for several
hundred birds each year, the ratios of these cocks exained is
of questionable worth.

Kimball (1948) found that in 'South Dakota in 1947, exmaina-
tion of nearly 12,000 birds (a more than adequate sample!)
resulted in a progressive shift of the youngzadult ratio from
5.0 to 1.2 over a six-week period. Allen (1941), Stokes (1954),
and others have noted similar decreases in proportion of young
in the cock kill as the season progresses.

In the 1949 season, biologists and aides measured the bursae
of about 775 cock pheasants. There was considerable overlap in
the measurements, with no clear-cut distinction between adults
and juveniles. I

Petrides (1949) has succinctly pointed out the difficulty of
obtaining rearing success from age ratios determined by examina-
tion of cocks:

1) ”small" errors in aging may cause large errors in

interpretation, even though misidentification of
adults and young are somewhat compensating

2) extent of adult mortality must be known

3) the adult sex ratio met be known

4) s-ples must be carefully taken

8.4

122

Despite the care taken to obtain good age ratios of cocks
shot, I do not consider that the ratios were reliable indicators
of pheasant rearing success; spring sex ratios for the period were
not reliable, the samples (areas covered) were not similar from
year to year, and.there is some question about the accuracy of
the examinations.1 This does not preclude the possibility that
a careful sample taken each year might yield an approximate idea
of relative rearing success in a poor production year compared
to a good production year.

As a result of my somewhat negative conclusions as to the
value of our observed age ratios, Eberhardt and Slouch (1955) made
a more thorough study of this shift in sex ratios by day of the
season for the years 1950-1953. They also concluded that age
ratim'com'parison might be _made from examination of first day age
ratios where hunting effort in the areas to be compared is
comparable. This will still not provide a method for converting

age ratios to true rearing success.

Hunter Success _ a Populatiojn Measurement

Hunter success is a much misunderstood and often misused
statistic. The layman is prone to use it as an index to total

pheasant populations. hunter success can be a good index to

 

1For administrative reasons, emphasis on bag checks varied
from year to year and from area to area each year. Thus, combina-
tion of these unweighted samples was not practical for direct
comparisons from year to year.

8.5

123

total populations, so long as it is used as a comparative figure
under similar conditions, most important of which is hunting
pressure. The harvestable surplus of pheasants for any given
area may be taken by varying numbers of hunters (Allen, 1947),
'with inversely varying success. Thus, total kill figures for any
area are likely to be more nearly an index to actual populations
than the success of the hunters who harvested that total kill.
During the years of this study, hunter success samples
obtained from hunter bag checks were not strictly comparable as
to effort expended and the location in which the samples were
taken, so they are not easily comparable. A hunter success
factor enters into the tabulation of hunters' report cards to
determine total kill, however, (Section 2.4). In this instance,
the success factor (birds shot per hunter reporting) is used
legitimately, since the system assumes a comparable sample from
year to year, and hunter success is not used as a statistic on
its own, but rather as a step in a computation which considers

total hunters as well as their success.

Hunter Opinion Polls

As they were checking hunters' bags, biologists asked hunters
whether they had seen more, the same, or fewer pheasants than the
previous year. The several thousand hunters interviewed each year
responded as follows:

1946 M1 }_9_4_§ 1949
More 561 52 501 70%

Same 251 802 302 161
Fewer 191 151 201 141

124

This summary of hunter opinion does not offer any apparent
index to pheasant populations, although the percentage reporting
'more birds‘may indicate, very grossly, sizable increases or
decreases in pheasants from year to year. Unaccountably, about
the same percentage of hunters reported fewer pheasants--in good
years and bad--in .pite of extremes from 5 per cent to 70 per cent
reporting more birds.

Surprisingly, the percentages of hunters reporting the three
classifications of abundance remained relatively constant through-
out the season. In 1949, for example, the percentage of hunters
who reported seeing more pheasants than in the 1948 hunting season

was as follows:

Percentage Reporting Number of Hunters

 

 

gays of Season More Pheasants Interviewed
October 15 651 1 1,053
October 16 772 ' 790
October 17-23 77% 556
October 24-30 751 380

8.6 Conclusions

Attempts to determine density and sex ratio indices from
roadside surveys in the fall were unsuccessful.

Sex ratios observed by hunters on the opening day of pheas-
ant seasons were unreliable as preeeason sex ratios, due to unre-
liability of hunters' observations and the removal of as much as
one third of the cocks shot in the season during the one day of
observation.

Age ratios determined by biologists from bursa and mandible

examinations were not clear-cut. Moreover, age ratios shifted

125

during the season because of differences in vulnerability of
adults and juveniles to hunting.

Because of this uncertainty of sex ratios and age ratios,

I could not determine any indices to true productivity (rearing
success).

Hunter success should be used as an index to populations
only when compared to hunter success indices obtained under
similar conditions, especially with regard to hunting pressure.

I conclude that the computed kill remains the best index to

fall populations.

9.1

9.2

Chapter 9

WINTER POPULATIONS

Iatroduction

Changes in the habits and observability of pheasants in win-
ter and spring cause extreme variation in observed pheasant sex
ratios and density indices. For example, Linduska had the of-
ficers record the pheasants they saw while driving during the
first months of 1946 (Table 9.1). Obviously, observed sex ratio
and density shifted radically. The variability continued into
April (Chapter 5). It has been commonly suspected that snow cover
might have an influence on observability of pheasants; and indeed,
the data in Table 9.1 would support that suspicion to some de-

gree--but in no particularly obvious pattern.

gagriers' {gstseason Surveys

Results of carriers' surveys made following the hunting sea-

 

sons in 1946-1949 are shown in Table 9.2. On some days counts

were more than double counts on other days. It was apparent that
short one or two week surveys with such large daily variation could
not be expected to yield accurate indices to densities or sex
ratios. Examination of the data further supported the earlier sus-
picion that amount of snow cover might have considerable influence
on the number of pheasants observed each day. It was not practi-

cal to ask the carriers to count for protractewl periods of time.

126

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129

9.3 Officers' My; Surveys

During the winters of 1948-49 and 1949-50, I had the officers'
record daily observations of pheasants for the entire winter
period, and I compared their observations to depth of snow on the
ground.

The "officer-day" was used as the unit of observation; it was
impractical to obtain the daily mileage of officers. But as in
the case of the carriers, the routineness of their duties permits
an interchange of units-~miles or days--with no appreciable error.
(Interchangeability of units is discussed in Section 4.4).

weather records were obtained frmm the U. S. Department of
Comrce, East Lansing Weather Bureau Office, or from the Monthly
Climatological Summaries published by that office. With the help
of A. H. Bichmeyer, in charge of the East Lansing office, I

selected one reliable1

weather station as near the center as pos-
sible of each of the five study areas.

Tb obtain a daily average snow depth measurement that was
representative of the 38 counties in the southern third of
‘Hichigan, I averaged the snow depth recorded at each of the five
stations for each day.

Beginning in the winter of 1949-50, snow depth was recorded

at‘Hichigan stations as a "trace" (.4 of an inch or less) or to

the nearest whole inch. For statistical purposes, a trace was

 

1Caremust be used in selecting weather stations because the
reliability of the weather bureau cooperators, the adequacy of
their equipment, and the location of each station in relation to
factors that might affect snow readings, varies from station to
station.

130

valued arbitrarily as .2 of an inch, an average of from .0 to .4
of an inch of snow. Since .2 is close to zero, no appreciable
error fro-.this arbitrary selection was anticipated.

The officers' daily observations for the two winters, 1948-49
and 1949-50 are graphed and compared with daily average snow depth
in Figure 9.1. Observations were smoothed. After trying one
month's data on a 3-day, S-day, and 7-day moving average, I decided
to use the 3-day moving average, since it seemed to smooth without
obliterating peaks, and yet made comparison much easier. The snow
depth curves were not smoothed since there was little reason to
suppose that observability of pheasants was affected by a given
snow depth for more than a day before or after the day of obser-
vation. Thus in effect, I assumed that the effects of snow
cover on observability of pheasants was essentially mechanical;
that snow cover makes the birds easier to see, rather than seri-
ously affecting the habits of birds.

This is probably not strictly correct. Atmospheric condi-
tions may affect the habits of pheasants, and storms certainly do.
Of course, excessive snow depth may affect habits of birds.
Nevertheless, for the purpose of this study, the reasons for
changes in observed density, whether due to behavior of the birds
or simple observability or both, are of incidental importance--
‘major concern heresfls in the observability of pheasants, pg; gs,

From Figure 9.1 it can be seen that pheasant observations,
smoothed by a 3-day moving average, followed snow depth remark-
ably well. It appeared frmm these graphs that snow depth had an

important effect on the observability of pheasants. It should hex

131

WINTER l948-49

INCHES OFSNOVI
N b a O

 

    

BIRDS OBSERVED
N b 0!

l5 3| l5 .
DECEMBER-i948 JANUARY—I949 FEBRUARY

WINTER l949-50

 

 

   

 

 

IO r
3 l—
2 8 ~
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u. 6 ~
0 _

w
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Fig. 9.1--Comparison of daily average snow depth with daily
pheasant observations by officers. ("Birds observed" smoothed
by 3-day moving averages)

132

pointed out that the graphs in Figure 9.1 are for the purposes of
inspection only, since observations are smoothed. For the
statistical studies, the original data were used.

No allowance was made for mortality over the winter. Any
mortality that occurred would probably weaken these correlations;
hence, if mortality could be considered, the correlations would
probably be even better.

The regression of birds seen on snow depth was calculated
for the two winters. The formulas and graphs of this regression
are shown in Figure 9.2.

If the effect of snow depth on observability of pheasants is
a constant factor from year to year, then the difference between
these two lines should be due to differences in population size.
In other words, if the difference between the years lies only in
pheasant population densities (and not in observability), then the
ratio of the numbers of pheasants seen in the two years at the
same snow depths should be constant, and that constant ratio would
be the ratio of the two population densities. Whether the two
lines do hold the same ratio may be appraised by comparing the
constant terms, the "y-intercept" (a) and the "slope" (b). The
ratio of the y-intercepts is 2.22 and that of the slopes is 1.63,
so it seems that the lines do not hold a constant relationship,
suggesting that observability changed as snow depth increased.

If snow depth has such an effect on observability of birds,
quite possibly observations made only on days when there was no
snow on the ground might offer a better comparison of density

from one year to another. Comparing the officers' observations

133

1949-50 y = 1.803 + .676x

    

1948-49 y s .810 + .414x

 

Pheasants per officer-day (y)

 

l l l l I
o 2 4 6 8 10

Average snow depth in inches (x)

Fig. 9.2--Regression of pheasants observed per officer-day on
daily average snow depth.

134

for only days with.no snow'cover or a trace of snow'present

(Table 9.3), we find that they saw 60 per cent more birds in
1949-50 than they did in 1948-49, on days with no snow. This is
not consistent with the 122 per cent increase suggested by y-inter-
cepts in the regression lines in Figure 9.2.

Differences in the total population would, of course, reflect
differences in the cock and hen component of each year's popu-
lation. Regression lines for cocks and hens separately are
shown in Figures 9.3 and 9.4.

To analyze this further, let us assume the model shown in
Figure 9.5. If P is the observability of pheasants (or the
proportion of a population seen) then we may see a certain number
when there is no snow on the ground (a) and increasingly more at
the rate (b) as snow depth increases. Of course, this may not be
a straight line regression. It may be a curve or there may be a
decided jump as soon as some snow falls, etc.

This change in visibility as snow depth increases is compli-
cated by the probability that observability of cocks and hens be-
haves something like the model in Figure 9.6; cocks are probably
always more visible than hens in winter, but the visibility of
hens, with some snow cover, may increase faster than visibility of
cocks.

Referring back to Figure 9.5, we can say that y = pN;birds
seen (y) = visibility (p) times the true population (N). using
the regression formula from Figure 9.5, we can state the same
thing by the formula:

y = (a + bX)N

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136

U
r

Cocks per officer-day (y)
N

H

 

 

 

Average snow depth in inches (x)

Fig. 9.3--Regression of cocks observed per officer-day on
daily average snow depth.

137

1949-50 y a 1.046 + .748x '

 

 

1948-49 y = .530 + .334x

 

Hens per officer-day (y)
b
l

I I g I _J
o 2 4 6 a 10

Average snow depth in inches (x)

 

Fig. 9.4--Regression of hens observed per officer-day on
daily average snow depth.

138

(y)

(observability)

P

 

 

 

Snow Depth (X)

Fig. 9.5-€Hodel suggesting a relationship of observability
of a pheasant population to snow depth.

139

Observability

 

 

Snow Depth

Fig. 9.6-duodsl suggesting shift in relative observability
of cocks and hens as snow depth increases.

140

The a and b coefficients of this formmla have been calculated
for cocks and for hens for each of two winters. Comparing these

coefficients from year to year yields these ratios:

z-intercept 310 e
(a) 75%-
. an - b N - '
Cocks- _Lflio. -.- 9.7.11 :1.35 $32.22 gfl =2.14
(a2,b2) 82N43-49 .280 b2N4g-49 .080
Rena: ‘1"49-50 . 1.046 : 1.97 b1%9-50 - 748 - 2 24
(.1331) ‘11'48-49 .530 bate-49 ' .334 '

With the exception of the y-intercept for cocks, all ratios
are fairly close together. One might thus speculate that the 1949-
50 population was about twice as large as that of 1948-49.

using the same ratios between "a" values and between "b"

values for the two years for sex ratios, gives values as follows:

z-intercept Slope
‘

1949-50 hens 1.046 : 2.77 .748 : 4.37
cocks .378 .171
hens .530 - 1.89 .334
1 - -———- -———- - .———— :
948 49 cocks .280 .080 4'18

This is but one more demonstration that observed sex ratios
also increase as snow depth increases. The increase (slope) in
this instance, however, was not consistent with the y-intercept.

In Figure 9.7 the curves for this increase in sex ratio for
the two years are plotted.

There is no easy way of determining sampling error in these
studies. Despite a bulk of data we have no way of referring it

to true density or sex ratios. Very large sampling errors are

Sex Ratio (hens per cock)

141

- 1949-59

1948 4‘9

i

 

 

0L + 7: ' 4% 5 1'0

Average snow depth in inches

Fig. 9.7--Increase in sex ratio as snow depth increases.

9.4

142

probably present. One of the 55 officers reporting may, in one
day, report more than half the total observations. The duties of
one officer may carry him past a large concentration of birds one
day, not the next. Quite possibly, however, we could devise ways
to improve the sampling.

In addition, I am.basing this speculation on two years' data.
It may happen that these two years are not representative of
other years. For example, data on the two winters presented here
almost certainly indicate more birds and more hens per cock in
1949-50 than in 1948-49. But elsewhere in this paper we have
shown evidence that sex ratios may not ordinarily change appreci-
ably from year to year (Chapters 5 and 7). In Table 7.3, however,
we can note that the carriers' prediction of fall kill in 1949
showed the greatest error recorded--15 per cent low! This could
be explained by saying that for some as yet undisclosed reason,
a much greater than normal percentage of the cock population was
harvested in the 1949 hunting season. This, in turn, would have
to mean a greater number than normal of hens per cock in the win-

ter of 1949-50!

Conclusions

Observability of cocks and hens differs due to physical ap-
pearance as well as differences in habits. Observability changes,
at different rates for the two sexes,.as snow depth increases, so
observed sex ratios change. Hence, any indices to winter popu-
lations are likely to be only relative, and far removed from

direct indices of true populations.

143

On the other hand, there is a thread of consistency running
through the pattern of observations which may have a potential
for determining changes in density and sex ratio which will be

of value.

I recon-end further investigation of the relationships of
observability of pheasants to snow cover after the collection of
more data over a greater span of years, along with attempts to

inrove the collection of the sales.

Chapter 10

POPULATION TRENDS--ANNUAL AND LONG TERM

10.1 Introduction

‘Host of our seasonal measures of populations are expressed
as indices whose relation to true populations is unknown. These
indices, then, must be used only for comparison with similar
indices obtained in other areas or other years. For example,
sex ratios obtained from hunter observations on the one hand and
carriers' spring counts on the other hand might be compared with
their counterparts in other areas or other years, but could not
necessarily be compared with each other to determine shifts in
sex ratio from one season to another.

Figure 10.1 is a schematic diagram of the type of population
data we would ideally like to have. If we had accurate informa-
tion on all the items listed in the diagram, we would be a long
step toward knowing quite precisely what is happening to pheas-
ants throughout the year. In the foregoing chapters we have
discussed the collection of data for a large share of these
items. In the following sections I will summarise what com-
parisons can be made between these seasonal indices, and conclude
with a review’of long-term trends of pheasant populations on the

study areas.

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10.2

10.3

146

Reliable Indicesigg.zggg ngulations

In Chapter 7, I demonstrated a close correlation between
brood density indices in July and computed hunting season kill
in October-November. The close correlation over a long span of
years (Table 7.3) permits us to state that each of these two
indices is a reasonably accurate reflection of true populations
at the time they are taken, despite a long list of assumed and.
perhaps self-compensating factors which are not supported (or
negated) by other independent data (Section 7.3).

There is one other good index to true populations. The
crowing-cock count can be considered a reasonably accurate
measure of the cock population.

Thus, we have three seasonal references to true popula-
tions to which we can relate our other indices. In only one--
the computed kill--do we have data in terms of birds per unit

“2‘.

ex Ratios

 

Since sex ratios are commonly widely disparate in a pheas-
ant population where a sizable segment of the cock component is
abruptly removed each fall, indices to total populations must be
‘modified by the sex ratio, when one wishes to deal with such
things as productivity. I have demonstrated in other sections
that observability of pheasants differs by sex. Petrides (1949)
discusses this involvement, and more recently Dale (1952) has
published a comprehensive review of the importance of sex ratios.

Allen (1942) reported upon an inventory method which utilized

147

sex ratios in determining such items as percentage of cocks
removed by hunting. These and other authors have done much to
take the confusion of sex ratio differences out of calculations.
There have been few contributions, however, toward taking the
confusion out of determining true sex ratios from observed. The
complications one gets into by ignoring even relatively small
changes in.ssx ratios in calculations point out the necessity,
in turn, of using'gggg sex ratios rather than ratios which may
bebiased by the observations that obtained them.

Horkers on intensive study areas such as loss Lake (Section
2.7) and the Prairie Farm (Shick, 1952) have obtained reasonably
valid sex ratios by actually censusing pheasants on relatively
small areas. But I feel that despite the care and precision with
which we may obtain indices to sex ratios from extensive surveys,
we are still far short of tying these indices to true sex ratios.

In Chapter 9, I suggested a dystmm which might allow
removal of one bias-~snow cover--from sex ratio observations.
In Chapter 5, I suggested that by careful attention to phenology
one might obtain a "better" sex ratio. Rut in both these instances,
the information is improved only to the point that the comparison
of indices is improved. we are closer to, but still far from
knowing‘gggg sex ratios. It is the nature of pheasants to show
behavior patterns that differ by sex for almost all seasons of
the year. This trait distinguishes pheasants from less polyga-
‘mously inclined birds such as ruffed grouse and quail.

I would caution then that, as Dale (1952) admonishes, we

carefully determine sex ratios, that we apply standard tests to

148

determine such things as sampling error probabilities, and that

we not neglect sex ratios when they should be considered in our
calculations. But I would further caution that we should beware
of a false senpe of security by this regard for sex ratios. No
amount of care and precision can make up for the fundamental bias
resulting from the relative observability of hens and cocks, which
I feel is inherent in virtually all our extensive surveys.

He must make one important speculation on the broad subject
of pheasant sex ratios. The extremely good correlation between
the carriers' summer brood counts and the hunting season computed
kill implies a more or less consistent percentage removal of the
cock pheasant component of each fall's population! This, in turn,
suggests that postseason sex ratios may not vary greatly from
year to year!

4 There is one very obvious exception to this statement.
Although the discussion in Chapter 9 of the officers' daily
counts during the two winters of 1948-49 and 1949-50 still does
not permit us to determine accurately the difference in sex ratios
between the two winters, it is almost indisputable that there were
considerably more hens per cock in 1949-50 than there were in
1948-49. In other words, almost certainly sex ratio'gig change
appreciably. But the hunting season kill in 1949 was 15 per cent
greater than predicted from carriers' surveys--the largest error
by far in the ll-year correlation! If the percentage of cocks
killed in 1949‘!!! unusually high, a more disparate sex ratio in
the‘winter of 1949-50 would inevitably follow. This exception in

1949 may be one which helps prove the rule.

149

This hypothesis that sex ratios ordinarily should not
change greatly from year to year may or may not be supported
by spring sex ratio surveys. The carriers reported rather
uniform harem sises for the three springs 1948, 1949, 1950 (2.3,
2.1, 2.5, respectively, Table 5.4).

This is speculation. There may be compensating factors that
we cannot appraise. But we cannot overlook the fact that this
system of predicting fall kill with an ll-year average error of
prediction of only 4 per cent demands a fairly constant percentage

removal of cocks-~or some unknown compensating factors.

10.4 Meshing Seasonal leation Indices
We have excellent information on pheasant density at least
three times a year--spring, sun, and fall. We have some infor-
mation on sex ratios. now can we tie these various pieces of
information together? Since we are dealing with different indices,
a system of conversion factors will probably have to be devised.
We would be premature to try to devise such a system now, but in
time I think it can be done. Following is- a synopsis of the
possibilities for bringing seasonal population data together:
.5222 _t_o _f_a_l_1_. In Chapter 7, I have discussed the relation-
ship between suamer and fall population density measurements.
This is a precise alignment of aux-er to fall density. Sex ratio
of chicks in July can be assumed to be very near 1:1. We. have
no measure of adult sex ratios in mid-sumaer, nor in the fall
just before the hunting season. But since ordinarily young of

the year, evenly divided as to sex, are the preponderant part of

150

the fall population, we can' assume the preseason sex ratio of all
pheasants (adult and young together) is; fairly close to 1:1--
precisely how close, we cannot say.

La}; 53 119553. fle have a good measure of the fall kill.
If we knew the postseason sex ratio, these two sources of data
would provide us with the means for estimating remaining cocks
and the hen population. A valid age ratio of cocks shot would
allow us to go one step further to determine rearing success.
Our determinations of sex and age ratios are imperfect, but there
is promise they can be improved. In the meantime age ratios,
carefully obtained, may be compared for relative (not true)
rearing success, if or‘when it is true that sex ratios do not
change appreciably. We may find, with practice, that sex ratios
(relative, but probably not true) may be obtainable in winter by
the use of a factor to minimize or eliminate the effect of snow
cover on observability of the birds.

flit—93- _t_g m. Changes in sex ratio from early winter
to spring would give us differential winter mortality. Changes
in density for the same period would give us total mortality. I
do not feel that either the density or sex ratio measurements we
now have are directly comparable. But if the total fall cock popu-
lation can be determined,an index to cock mortality from fall to
spring will be available, since the crowing-cock count is a good
index to true populations, and may soon be convertable to cocks
per unit area. I doubt, however, if we will be able to convert
observed sex ratios in winter or spring to true sex ratios.

Spring _t_o sun-oer. If sex ratios could be asmmed to be

151

constant from spring to spring, then the crowing-cock counts
compared to suI-er brood counts would give us a usable measure

of relative productivity (not true productivity).

10.5 ngulation Trends‘by Study Areas
Figure 10.2 shows the trend of populations by study area for

the ZO-year period 1937 to 1956, inclusive. The computed kill
per square mile (Chapter 2) in each of the study areas is used
as the unit for comparison. we have already concluded that
computed kill can be considered an index to the fall population,
on the strength of its excellent correlation with summer brood
production.

Since study areas are based on political (county) rather
than biological boundaries, the relation of the areas to one
another is only a general one.

The graph in Figure 10.2 is on a semi-logarithm scale. we
are dealing with areas with widely differing population densities.
Comparison of the logarithm of the kill per square mile permits
us to compare population trends in the areas by comparing slopes
of the curves, regardless of the population level.

The chief value of this comparison of the trends of pheas-
ant populations in the study areas will be comparison of these
trends, in turn, with the many factors suspected of affecting
pheasant populations as those factors have changed over the years
in the study areas. Study of these factors is outside the scope
of this paper. But this analysis should provide the basis for
such study.

I have casually compared the trends of Michigan's pheasant

152

 

 

 

 

 

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153

populations with trends in other states. They have much in
common. Figure 10.2 represents a build-up to a peak in the
‘middle 40's and a serious depression in 1947. In general, pheas-

ants followed this pattern across the continent. The exact date

of the peak varies, generally between 1942 and 1945. The
depression was generally considered to be at its lowest in 1947,
although in some states the low'point was considered to be in

-l946 or even 1948.

More specific comparison is difficult. Kill figures are
regarded‘with more skepticism in most other states and provinces
than in‘uichigan. I would suggest that pheasant kill figures in
other states might be re-examined in the light of our evaluation
given in Chapter 2, and that other states' population data be
compared with‘nichigan's. (For example, our Study Area 2 is
contiguous with Ohio's good pheasant range, Study Area 4 is

contiguous with Indiana's pheasant range, etc.)

The rank of the study areas as producers of pheasants has

changed over the years:

_Aggg g (southwest; type locale-"Kalaasoo County) has
consistently been the poorest. It represents the poorest part
of primary pheasant range.

.érga‘g (central; type locale--Ingham County) can be
considered moderately good, but not quite top-notch pheasant range.
It can be considered the most stable of the better areas.

.5535“; (west central; type locale--0ttawa County) was in
fourth place before the depression. It competed for first place

by the middle 50's.

Area.g (southeast; type locale--Lenawee County) was usually

156

second best before the depression. rrom 1947 through 1952, in
and following the depression, it*was the best area. Since 1952
it has dropped back to second or third place.

.4323 l (the "Thumb”; type locale--Tuscola County) is famous
as‘uichigan's best.pheasant range. With the exception of 1947-
1952, it has been at or very near the top.

It is noteworthy that the peak varied among study areas
within the state of Michigan. Arsa'h quite certainly (and
possibly Area 3) reached a peak in 1941.. Areas 1, 2, and S
quite definitely reached a peak in 1944. Thus, the poorer areas
peaked in 1941, the better three years later in 1944 (considering
Area 5 as one of the better areas). 1 I 1

Referring back to Tigure 3.5, we can see that Areas 1 and 2
differ geographically only in latitude. The highest pheasant

populations of each are on lake-bed clay soils. Their population
. curves follow each other most nearly of any of the areas. They
reached a peak together. Now compare their curves to Area 5's.
If Area 5's curve prior to the 1947 depression were about
doubled, it would very closely resemble the curves for Areas 1
and 2. But Area 5 is more distant, geographically, from Areas 1
and 2 than any other area.

The only fundamental characteristic I can determine that
Areas 1, 2, and 5 share in common to the exclusion of Areas 3 and
4, is a large amount of lake-bed plains. Thus, Areas 1, 2, and 5
are distinguished as Michigan's heat pheasant range-~a distinction
they share with sheilar areas of lake-bed plains which support

the highest populations in neighboring states--Ohio (Leedy and

155

Hendershot, 1947), New'York (Brown and Robeson, 1959) and

Ontario, especially as typified by Pelee Island (Stokes, 1954).

SUMMARY

This study of Muchigan's pheasants from.the standpoint of popu-
lation dynamics, had three objectives--(l) to reconstruct a history
of past populations, (2) to acquire information on current population
levels, and (3) to devise necessary new sampling methods for obtaining
that information. The study was made during the years 1947-1950 when
data were obtained from a large number of extensive surveys, and from
certain of these surveys repeated annually from.l951 through 1956.
Other data in the Game Division files covering the period 1895-1946
were analyzed.

Pheasants were first introduced into Mflchigan by a release of
several birds in Ottawa County in 1895. At least one brood was pro-
duced. Despite a number of other releases by private citizens in the
ensuing years, pheasants were not established anywhere in Michigan
prior to 1918 when the State began a release program. 'The State re-
leased grown birds in the fall and gave eggs (and in some cases day-
old chicks) to private citizens who requested them, From 5,000 to
10,000 birds were released each year. By 1921 pheasants were estab-
lished in much of southern Muchigan. In 1923, five years after the
beginning of the release program, authorities recomended a pheasant
season; in 1925 the Legislature opened the first season on pheasants.
By the late 1920's, pheasants had probably spread to the limits of
their range, although the relative distribution was considerably dif-

ferent than it is today.

156

157

Records of hunter-performance during the fall hunting seasons
were the best source of information on pheasant numbers prior to this
studyu‘ From.l929 through 1935, a few hundred hunters reported on
their pheasant hunting each year on "Bird Hunters' Tally Cards" fur-
nished by the Game Division. From.l933 through 1936, license vendors
quizzed small game license purchasers about their previous year's
pheasant hunting and recorded the data on a special stub of the license.
Computations from.these tally cards and license stubs provided only
fragmentary and dubious information on pheasant kill.

Beginning in 1937, hunters were compelled by law to return to the
Game Division "Small Game Hunter Report Cards" issued to them with
their license. The pheasant kill was computed by county each year
from these report cards. I concluded this kill computation to be
relatively accurate. I based this judgment on a comparison of the
computed kill to hunting data concerning two large groups of Detroit
sportsmen, measured kill on two study areas and examination of three
possibilities for bias or error in these computations: (l) inadequate
sample size, (2) dates of the returns (early vs. late), and (3) dif-
ferential success of those hunters who reported compared to those who
were delinquent.) ane of these biases appeared to be excessive.

Michigan's prhmary pheasant range was designated as the 38 coun-
ties south of a line running roughly from Saginaw Bay to Muskegon. The
balance of the Lower Peninsula end the south half of Menominee County
in the Upper Peninsula were designated as marginal pheasant range.

The remainder of the Upper Peninsula has only an occasional pheasant.

Pheasant distribution appears well correlated to soil and land

types. Five study areas, totaling about three-quarters of the primary

158

pheasant range, were picked on the basis of soil and pheasant dis-
tribution.

The extensive survey is defined as a collection of observations
by sampling, yielding indices to populations. Useful extensive road-
side surveys were made principally by rural mail carriers and conserva-
tion officers. The carriers provided a large volume of data on each
survey, but could be asked to make only short counts a few times a
year. With only one or two-officers per county, their extensive sur-
veys did not provide as much data but they could be asked to make
surveys over protracted periods. Surveys of and by sportsmen did not
provide usable data. Farmer cooperators provided some data on nest-
ing. Biologists made crowing-cock counts and‘interviewed hunters.

Measurements of pheasant populations for each of the four seasons
are discussed.

Spring_pqpulatiggg, I set up crowing-cock routes in most of the
38 counties of primary pheasant range. Growing-cock counts offered
the best index to spring cock.popu1ations, since they were self-
adjusting for phenology. Habits of pheasants differ radically between
sexes as the days progress in spring, making roadside surveys extremely
sensitive to errors in timing. Seven years of carriers' April road-
side surveys, adjusted to a common starting date, showed good cor-
relation to crowing-cock counts, with the exception of two years when
the springs were early and the carriers' counts were correspondingly
inflated.

Observations on pheasant harems may provide a better index to sex
ratios than observations of all birds. I was unable to convert spring

sex ratio indices into true sex ratios.

159

§ggggg_populations. Officers made roadside counts of broods
during June, July and August. Carriers made similar counts in late
July. For four years the number of broods seen by officers in each
consecutive semi-monthly period increased from June to mid-August at
a shmilar rate. The regression of broods seen by officers on period
of the summer was plotted, offering an opportunity to adjust brood
counts for phenological differences. Rainfall did not appear to have
a direct bearing on observability of broods by carriers. Brood sizes
reported by carriers did not change significantly from year to year-6
half-grown broods varied only from 6.10 to 6.53 chicks during a five-
year period when the population went down and began to recover. Fre-
quency distribution of brood sizes was also relatively consistent
during these years. The percentage of hens without broods seen by
carriers was greatest during years of poor pheasant brood production,
but this index appears inadequate by itself as a true‘measure of
productivity.

Carriers' July brood counts provided an accurate method for pre-
dicting fall kill. The regression of the computed cock kill on the
logarithm of the brood density observed by carriers in primary pheas-
ant range yielded an "r" value of .978 for the eleven years 1946-1956.
Using this regression as a method for predicting fall kill, the error
of prediction for the eleven years averaged 4 per cent--with a maximum
of 15 per cent error. This good correlation is somewhat unexpected,
since it asstnnes .‘ consistency from year to year of seven contributing
factors-~some of which heretofor often have been considered variable.
These seven factors are discussed: (1) late summer mortality, (2) per-

centage of the fall population harvested, (3) age ratios of cock kill,

160

(4) brood size, (5) accuracy and precision of kill computations and
brood surveys, and (6) timing of brood surveys. Some variation in
these factors from year to year undoubtedly occurs, but it may be in
part compensatory. ’

Fall populations. The computed kill is judged to be the best in-
formation on fall populations. Preseason roadside surveys by officers
did not yield plausible sex ratios or usable density indices. I do
not consider that sex ratio observations by hunters on opening day of
pheasant season are reliable. Because of a difference in vulnerability
between young and adult cocks, age ratios of cocks killed shifted as
the hunting season progressed. Hunter success must be used with
discretion as an index to populations. Field interviews with hunters
yielded little usable biological data, and polls of hunters' opinions
on abundance of pheasants were not useful.

Winter populatiogg, The number of pheasants observed by car-
riers and officers on winter roadside surveys correlates well with
depth of snow on the ground. I plotted the regression of the daily
observations by officers of cocks, hens, total pheasants, and sex
ratio on the daily average snow depth in the five study areas, for
two entire winters. Observability changes at different rates for
the two sexes as snow depth changes. Hence, winter observations yield
only relative density and sex ratio indices, with an unknown relation
to true populations. Differences in observability of the two sexes
are probably due to differences in visibility of the colored cocks
and drab hens, as well as differences in habits of the two sexes.
Sample size of the observations is probably less than adequate to

determine accurately the relationship between the sexes, but the

161

indisputable correlation between snow depth and total birds observed
suggests that this‘matter is worth further study. Possibly observa-
tions of pheasants on days with no snow may be most nearly indicative
of truepopulations.

Population trends--both annual and long-termr-are discussed.
Three annual surveys provide an index to true populations--the crowing-
cock index, the carriers' summer brood survey, and the computed kill.
The difficulties of determining true sex ratios. from observations are
discussed. I conclude we have no good.maasure of true sex ratios at
any season of the year. The possibilities for juxtaposing indices to
populations for adjacent seasons are discussed. The only indices to
populations for adjacent seasons that can be directly linked are sum-
mer brood density index and coquted kill .

The trend of populations for the five study areas, as determined
by conputed kill, is graphed for the 22-year period 1937 -1958. All
areas were at their lowest point in 1947, but the three best pheasant
areas peaked in 1944, the two poorer areas in 1941. The three best
areas exhibit similar population trends as distinguished from the two
poorer areas, although the former are widely separated geographically.
The only obvious factor co-son to the three best areas and lacking in

the poorer areas is large acreages of soil of lake-bed origin.

APPENDIX

METHOD POR.GOHPUTING KILL
PROHISMMLL GAME HUNTER REPORT CARDS

The method for counting pheasant kill from small game hunters'

report cards can be illustrated by the cowutations for a typical year.

A portion of the work sheet used to counts the 1948 pheasant kill is

shown in Appendix Table l. The capital letters in parenthesis below

refer to their counterparts in the table.

1)

2)

3)

Data from the 52,026 report cards received (It) were punched
on IBM punch cards, sorted, and recorded by county (A) on
the work sheet.

The 31,522 hunters (J) who reported that they hunted pheas-
ants and the number of pheasants they reported shooting were
distributed by counties as shown in columns (B) and (C).
Only one county of hunt was recorded for each hunter, al-
though he may have hunted in more than one county.

The 2,417 hunters listed as "Incospletes" (I) shot 5,560
pheasants but neglected to state in what county they hunted.
These hunters and the pheasants they shot were spread among
all the counties in proportion to the hunters and kill re-
corded for each county by using the formulae (1.) and (M).
Thus, the umber of hunters (B) in each county was multi-
plied by 1.083044150 and the product entered in column (D).
The masher of pheasants reported shot in each county was

multiplied by 1.109023883 (M) and the product entered in

163

4)

5)

164

column B.
At the time the coqutations were made, 1948 small game

license sales were estimated to be 582,000. The 52,026 re-

__1.__
11.18671433

nmsber of hunters, and the number of pheasants they reported

port cards received were of that total. The
shooting in colms (D) and (B), respectively, were thus
multiplied by the denominator of this fraction (II) which is
called the "Constant for Coquting." The estimates for each
county were entered in columns (F) and (C), respectively.
Colum: (C) then, shows the "Comuted Kill" for each county.
Coluln (1!) lists the average number of pheasants reported
shot per hunter reporting. This is not a true hunter suc-
cess figure, since *soms hunters who hunted pheasants but shot

none may have neglected to indicate that they hunted pheasants.

165

 

 

 

 

 

 

 

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