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SOME METHODS OF
WATERFOWL AND MARSH iNVENTORlES

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ABSTRACT

SOME METHODS OF WATERFOWL AND MARSH INVENTORIES

by Carl L. Bennett, Jr.

Because of the author's dissatisfaction with the more established
Techniques of marsh investigations, namely vegetation and duck inven-
tories, an outline for quickly and accurately obtaining basic data of
a more universal nature upon which marsh evaluation and/or further re-
search can be built is herein presented. The proposed methods, as put
forth, are for single marsh usage but can be adapted to marsh complexes
and even large geographic areas.

Vegetation inventories of two types are presented, each serving a
different function; plots placed at ecotones are used to determine
rates of prisere encroachment while stratified random sampling is used
for inventorying and for comparing subseres. Data are presented only
to illustrate since rates of vegetation encroachment and change are
undoubtedly marsh dependent.

Waterfowl inventory methods for nests, broods, and hunting season
kill are presented. Kill and nest inventory methods are modifications
of previous techniques while the brood inventory is a sampling proce-
dure based on the assumption that as the number of different broods
seen increases it becomes progressively more difficult to see a "new"
brood; and the rate of this decline follows a logarithmic series curve.
Data for the nest and kill inventories are again only for illustration

but substantiating data for the brood inventory method are included.

Usage of these proposed methods allows the yearly collection of
data in a relatively short period of time even by different observers
with a minimal lack of continuity. Thus, statistical treatment of data
to evaluate research findings and to predict the effects of management

practices is possible.

SOME METHODS OF WATERFOWL

AND MARSH lNVENTORlES

By

Carl L. Bennett, Jr.

A THESIS

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

MASTER OF SCIENCE

Department of Fisheries and Wildlife

I965

ACKNOWLEDGMENTS

To all those people who contributed towards this manuscript but
are not named, l humbly acknowledge your efforts.

i am deeply grateful to the Erie Shooting and Fishing Club for
the area and the funds (granted to me by the Erie Research Committee
through the Department of Fisheries and Wildlife of Michigan State
University) to conduct research.

To C. E. Kincaid (then manager-Erie Club) and his assistant and
to W. A. Matulis and D. J. Drumm a special note of thanks for aiding
me in collecting data on the Erie Club marsh.

i am also grateful to the personnel, especially Dr. C. T. Black
and Dr. J. A. Kadlec, of the Rose Lake Wildlife Research Center of
the Michigan Department of Conservation's Research and Development
Section for collecting data for my use and to Dr. P. J. Clark (until
his untimely death) and L. A. Ryel for their help with the statistical
aspects of the paper.

i wish to acknowledge the efforts of Dr. M. D. Pirnie, for whose
guidance and counciling I am deeply indebted, who helped initiate and
directed the project and who offered valuable editorial comments.

Special thanks go to Dr. D. W. Douglass for critically reviewing
and to Beatrice Byerlay for her diligence in typing the manuscript.

Lastly, to my wife, Joanne, i am ever grateful for tolerating

many inconveniences and for providing the needed impetus.

TABLE OF CONTENTS

PAGE

lNTRODUCTlON . . ........................ I
VEGETATION INVENTORY . . . . . . . . . . ....... . . . . . 4
Summary of existing techniques ........ . . . . . . . 4
Theory ........................... 7
Field use ........ . ........ . . . . . . . . . 9
Discussion . . . .......... _ ..... . ...... I6
DUCK NESTING INVENTORY . . . . ................. 22
Summary of existing techniques . . . . . . . . ....... 22
Theory ....................... . . . . 23
Field use ....... . .................. 24
Discussion . . . . . . . . ..... . . . . . . . . . . . . 25
DUCK BROOD INVENTORY ' ............ . ...... . . . 28
Summary of existing techniques .............. i. 28
Theory . .................... . ..... 3|
Field use . . . . ..... . ....... . . . . . . . . . 34
Discussion . ........................ 37
DUCK KILL INVENTORY .. . . . .................. 42

Summary of existing techniques . . . . . . . . . . . . . . . 42

Theory . .......................... 44
Field use .......................... 46
Discussion ........................ . 47
CONCLUSION AND SUMMARY ..................... 48
LITERATURE CITED ........................ 50

PAGE
APPENDIX ..... . ......................
Necessary background information . . . . . . . . . . . . . . 59

Vegetation sampling instructions for Maple River West . . . . 69

iv

TABLE

LIST OF TABLES

Vegetation inventory - Maple River West, stratum results
Vegetation inventory - Maple River West, plant Inventory
estimates . . ........ . . . . ........

Vegetation inventory - Maple River West, stratum

comparisons ................. . . . .
Duck nesting . . ........... . ........
Brood estimates . . . ......... . .......
Observation time study ......... . . . . . . . .
Transect locations . . . ....... . . . . .Appendix

The recovery of flood-killed cattail in Potter's Cove
when water was removed ......... . .Appendix

A transition from cattail to meadow in Potter's Cove
Appendix

Calculation of total brood production ..... Appendix
Creel census data, Duck and Fine Iakes,l958 . .Appendix

Summary of use ................. Appendix

PAGE

l8

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2|
27
40
4|

63

73

74
76
77

78

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LIST OF FIGURES
FIGURE
I. Transect locations l96l, Erie Marsh, Monroe County,
Michigan . . . . . . ....... . . . Appendix
2. Maple River West . . . . . . . . . . . . . Appendix
3. Erie Shooting and Fishing Club, Potter's Cove,

Cover map of the vegetation ...... Appendix

vi

PAGE

62

68

75

INTRODUCTION

Marsh investigational techniques, especially vegetation sampling,
are many, diverse, and of varying degrees of accuracy. When Investi-
gators repeatedly and somewhat sporadically study different marshes,
results often lack continuity. Even when the same techniques are em-
ployed, because of original design, data are still not quantitatively
comparable.

A resume'of techniques now in use, with a short critique of each,
is included under each section and will not be presented here. Each
section Is designed as a complete entity to save wear and tear on the
reader's mind.

The proposed methods are based on studies conducted in Saginaw
County, Michigan, at the Shiawassee Refuge of the U. S. Fish and Wild-
life Service, where I worked as a Student Assistant; at the Erie Shoot-
ing and Fishing Club in Monroe County, Michigan, where I studied as a
research waterfowl biologist under a grant from the Erie Research Com-
mittee; at the Conservation Department's Rose Lake Wildlife Research
Center, Clinton and Shiawassee counties, Michigan; and at the Gratiot-
Saginaw and Maple River state game areas. Studies at Rose Lake and on
the game areas dealing with waterfowl and vegetation inventories were
either conducted or supervised by me in my present capacity as bio-
metrician for the Michigan Department of Conservation.

Before proceeding further, I wish to establish that these pro-

posals have arisen from the negative rather than the positive point of

view. While at both the Shiawassee Refuge and the Erie Club, I fol-
lowed previously established techniques of inventorying vegetation,
duck nesting, and duck broods. Many doubts arose in my mind as to the
actual worth of the techniques. Most of the methods proposed have had
I only weak field testing at best and are suggested because of my dis-
satisfaction with the established techniques.

Some of the vegetation inventories herein discussed l instituted
while at the Erie Club In l96l, with the assistance of Walter A. Matulis
and Dennis Drumm. These inventories have been continued since that
time. In l964 two Conservation Department aides, under my direction,
inventoried the vegetation on part of the Maple River State Game Area,
the results of which are included to exemplify a particular use.

At an impoundment on the Rose Lake area, Center personnel and l
have and still are testing my proposed method of estimating broods.
The survey utilizes an observation point placement and sampling system
devised by Robert Heath and John Kadlec.

i am not going to consider surveys of waterfowl during Spring or
fall migrations. Nor am I going to consider a "breeding pairs" survey,
the validity of which I strongly question. Also, I am not including
a method for making use estimates during the early fall shuffle. The
reason for not considering these surveys is simple: I have no method
to offer.

Some proposed methods for vegetation and waterfowl inventories
are presented for consideration. Ways of estimating total waterfowl

production on an area are somewhat archaic and a better method is badly

needed. In an attempt to fill this gap I have devised a method that
seems to work on one particular type of impoundment, and through modi-
fications may work elsewhere. There are in existence good methods of
estimating duck kill; these are included. Also I include a duck nest
Inventory method that is old in design but new in philosophy.

Proposing of these methods Is in no way an attempt to create hard
and fast guidelines. I assume investigators will continue to display
individualism in type and sc0pe of research projects, but by also in-
corporating these standardized methods time can be saved and continuity
preserved.

Certain background data are necessary to form a good working base
upon which to superimpose the methods. An outline of these data and
their contributions is included in the appendix (Necessary background
information).

Throughout the paper the word "technique" will be used when the
work plan was someone else's idea. For my proposed work plan I will
use the term "method" to save confusion. Also the terms "survey,"
"census," "inventory," and "sample" will occur many times. The best
way to show their use and meaning is in the following sentence, "An
inventory is the result of a survey accomplished by either sampling or

censusing."

VEGETATION INVENTORY .

SUMMARY OF EXISTING TECHNIQUES

Most techniques of vegetation inventory have been developed for
timber and grasslands while marsh and aquatic habitats have been some-
what neglected (Loveless, I957). To try to use the techniques employed
in grasslands and in timber stands does not seem appropriate since de-
veloped techniques are based on growth habit and growth form of the
plants (Brown, I954; Hasel, I954).

Nevertheless, some investigators cognizant of the drawbacks have
tried to census marsh vegetation by applying techniques developed for
grasslands. For example, point sampling (Brown, I954; Subcommittee
on Range Research Methods, I962; Greig-Smith, I957; COUpIand, I950)
which is of questionable accuracy even in grasslands (Brown, I954;
Greig-Smith, I957; Blackman, I935; Goodall, I952) has been tried as a
technique to inventory marsh border (Sincock and Powell, I957; Berg,
I956) and aquatic vegetation (Uhler and McGiIvrey, I965).

Other investigators, who appeared aware of the necessity of a sur-
vey technique unique to marsh vegetation and flexible enough to circum—
vent differences in growth form between marsh border and aquatic plants,
devised new techniques of varying degrees of accuracy. Generosoff
(I934) first mapped the area, then traversed it estimating plant abun-
dance and graded the density per Species on a decimal system within
marsh sections. By knowing the areas involved and percentage composi-
tion of their vegetation, he calculated the approximate acreage of

stands of any plant species or group of species. He also made stem

counts on "selected" one-meter quadrats to determine "medium" density
for each species; those biased counts were used as standards for the
density ratings.

Siegler (I94l) walked segments or total shorelines listing the
number of times a particular species occurred alongside of his right
(or left) foot. He needed a list of species present before starting
and could census only two species per trip. He also felt that quad-
rats may be necessary to help analyze and correct the total picture.

Stoudt (I944) used basically the same system as Generosoff (I934)
with one important exception. After having type—mapped the vegetation,
he checked seed production of the various waterfowl food plants occur-
ring along the marsh border and computed the percent frequencies of
the purely aquatic food plants.

The bulk of the techniques for inventorying marsh vegetation have
utilized some variation of the transect method which Dorothy Brown
(I954) stated was best for vegetation which traversed a land gradient.
Transects have also been used in timber (Pielou, I962) and grasslands
(Rice, I952).

True transects (Penfound and Hathaway, I938), line transects
(Siegler, I94I; Beard, I953), line transects with systematically placed
plots (Anderson, I950; Jessen and Lound, I962; Keith, l96l), line
transects with randomly located plots (Loveless, I957), line transects
of variable direction (Swindale and Jahn, l956) and randomized tine
transects (Uhler and McGiIvrey, I965; Berg, l956) are illustrations of
a few of the variations that have been tried. Excluding the transect

work of Penfound and Hathaway (I938), the investigators used line

transects, usually with quadrats along them. Basically the use of this
technique stems from a desire for quantitative data but an unwillingness
to spend considerable time collecting it.

Some of the waterfowl refuges under the jurisdiction of the U. 5.
Fish and Wildlife Service have had repeated vegetation inventories from
staked plots placed at ecotones* along line transects (Bennett, I960;
Robert Meeks, student assistant, Seney Refuge, I960, personal communi-
cation).

Subjective inventories based on relative frequencies are biased
and not suitable for yearly comparisons; actual measurements of both
expanse and composition of plant communities are needed. Therefore,
cover maps should be the result and not the agent of marsh inventories.

Penfound (I945) presents evidence suggesting that frequency is
the most artificial and least important manner of inventorying vegeta-
tion compared to cover (measurements on the amount of ground area
shaded by each species) and density (stem counts). Also the relation
of density did not change with quadrat size, number of species present,
or the total plant cover, which suggests that density is a true quanti-
tative condition and hence more reliable than frequency or cover.

The use of permanent transects with systematically placed plots
has three possible drawbacks: first, the validity of calculated con—
fidence limits is questionable; second, the accuracy of the sample var-
Ies Inversely with the number of vegetative communities within the
marsh; and third, the transects are usually not randomly picked. This

means that the accuracy of such a vegetation inventory is neigher

*As used by Clarke, I954.

calculable nor independent of the marsh. However, a systematic sample
can serve a useful function when used as a subsampling technique with-
in a particular vegetative community (where the assumption can be met
that the variability between samples is greater than the variability
within subsamples which allows pooling data collected from subsamples
(Cochran, I953) and treating them as a single sample).

Even the use of randomly located transects, regardless of how the
quadrats are placed on them, does not seem highly efficient to me.

The sampling unit is still the transect; the quadrats are subsampling
units. Thus variability measurements are between transects and not
between quadrats over all transects.

Establishment of permanent transect lines with staked plots at
ecotones has two possible drawbacks: The first is merely mechanical--
stakes are hard to keep placed and hard to find; the second is statis-
ticaI--plots are not representative of the marsh because they are not
randomly selected and sample only transition zones. "Ecotone Transects"
(as I choose to call them) can serve a useful function but will not

stand alone as an adequate marsh vegetation inventory.

war.
When I attempted to devise an adequate sampling scheme calling for
minimum effort expenditure, it came to mind that two greatly different
situations are likely to occur in any given marsh--prisere* (primary
succession) and subsere** (secondary succession) areas.
*As used by Clarke, I954.

**As defined by Hanson, I962.

The rate of change in plant composition within and the rate of
edge movement outward for a prisere area is markedly different (usually)
slower in vegetative change and faster in edge movement) from those
same rates in a subsere. Therefore, maybe priseres should be studied
with emphasis on rate of encroachment while subseres should have the
emphasis upon vegetative changes, albeit much of the rate of change
with respect to time depends upon the amount and duration of Inundation.

I think an "Ecotone Transect" technique will yield enough desir-
able information to compensate for the hardships encountered when uti-
lizing permanently located stakes.

Two different uses are, I believe, possible. When the transition
zone is extremely narrow (emergent vegetation and open water as an ex-
treme example), measurements from stake to edge for several years should
yield data that can be used to calculate the rate of edge migration
with respect to time and corrected for differential water depths by us-
ing a multiple regression. The second use stems from the occurrence
of wider and more complex ecotones. Possibly by sampling within the
transition zones the changes in species composition over several years
will provide data which can also be used to determine rates of en-
croachment through either inverse relations projected with regressions
or through ratios projected by an appropriate mathematical series to
the zero point.

A side benefit of using "Ecotone Transects," assuming they are
laid out with transit and tape, is that measurements across homogeneous

vegetative types are available for scaling air photos.

It has been my observation that most subsere areas (most experi-
mental plots are in this category) change rapidly in vegetative compo-
sition, with reciprocating encroachment that is of little consequence
in determining the time of reversion back to the vegetation present
before disturbance. This being the case, I feel the most important
aspect to be considered is the rate of change in plant composition. A
form of stratified random sampling (Cochran, I953) then becomes the
most logical tool to use. The sampling plan can be devised for deter-
mining the change in the gross number of Species, for an inventory of
the major species, for an inventory of total duck food available, and/
or for determining a rate change of primary species to secondary Species
over time.

The latter possibility can be used for evaluating a management
technique In terms of money Spent to length of time it is useful. The
duck food production inventory, I think, is useful when one wishes to
compare two different subsere areas (test areas primarily), if differ-
ences in species composition pg£_§§_cause no hardship in making the

contrast.

FIELD USE

I think a combination of both "Ecotone Transects" and stratified
random sampling should be employed in a marsh subjected to frequent
study, especially if research continuity over time Is desired. When
only single or Sporadic vegetation censuses are needed, the usefulness

of the "Ecotone Transect" is lost and is not worth the time and effort.

l0

Plot Size for emergent and marsh border vegetation should be l/4
milacre. Milacre quadrats would mean fewer plots and less "edge ef-
fect," but because of the tendencies of clumping and dispersion, a
greater number of plots of smaller areas, I believe, are more suited
to my purpose. Cochran (I953) believes that large sample units are
nearly always cheaper but often less precise.

For sampling submerged vegetation a larger quadrat seems appro-
priate (Curtis and McIntosh, I950). I have used I milacre quadrats
for this purpose.

Several attempts at obtaining quantitative data from submerged
sampling units are described in the literature (Swindale and Jahn,
I956; Swindale and Curtis, I957; Tryon, I954; Jessen and Lound, I962;
Anderson, I950; Keith, I96l; Loveless, I957) but seem to fall into two
categories of deficiency: too time-consuming or too Inefficient for
good quantitative data. I have no tested technique to submit; only one
to suggest. Possibly density calculated from frequency using the
Poisson distribution as outlined by Blackman (I935) IS not altogether
erroneous for areas having haphazard water fluctuations or in newly
created areas. I suspect from my field experience that the distribu-
tion of plants immediately following a major habitat disturbance is
closer to being random than In established communities.

The question as to how many plots Should be taken will need answer-
ing each time a survey is to be conducted. The burden of such a de-
cision rests solely with the investigator. The ideal situation is to

have time and money to run a "thumb-nail" investigation (take a few

samples to determine amount of variability), the data from which can
be used to roughly estimate desired sample sizes (Cochran, I953). If
this is not possible, either use data from elsewhere if available as
a basis for selecting the number of plots, or use your own knowledge
of the area.

Cain (I937) suggested a method for determining the break (point
where a IO percent sample gives a I0 percent increase in species) in
the species-area curve. Penfound (I945) suggested that a sample at
least ten times the number of quadrats obtained from the break in the
species-area curve is necessary for a proper quantitative sample in
plant community analysis.

The locations of randomly picked plots can be determined by com-
pass and pacing at time of survey. Jolly (in Brown, I954) and Greig-
Smith (I957) both state that randomly picked plots need not be accu-
rately located and that pacing is quite adequate.

Data collected at each l/4 milacre quadrat should include the
density, height, and seed production for each species and possibly the
percent of cover per layer. Sampling just percent cover per layer of
each Species has too many possible year-to-year discrepancies regard-
less of consistency among observers. These stem from differences in
temperatures, solar radiation reaching the ground, time and duration
of inundation, etc., from one year to the next. Also the usefulness
of purely cover percentages is quite limited even when the afore-

mentioned inconsistencies are non-existent.

I2

Suggested outline for "EcotonelTransect" sampling

Ecotone Transects are picked; not random. The Idea is to place
the transect so that both beginning and ending stakes are easily found
and are not likely to be lost due to ice or some other factor, and so
that the line crosses several major ecotones. The number of transects
varies with the marsh but relatively few are necessary. At the Erie
Shooting and Fishing Club, I established ten transects (five of which
were extremely short and measured a single vegetation-open water eco-
tone in which I had a greater interest) which contained a total of 54
quadrat stakes (Appendix, Figure I and Table 7).

Each transect should be laid out by a transit and tape to aid in
subsequent locating of stakes. Each quadrat stake should be placed at
an ecotone in a systematic manner, i.e., at the point where each eco-
tone is first encountered, then the quadrat itself should be positioned
in a predetermined relation to stake and transect line.

The data obtained from the quadrat inventory can then be used to
determine edge migration through the use of regressions on the inverse
relationship between the two adjacent vegetative communities. The
slower the rate of edge migration the more useful this technique.

When edge migration is fairly rapid, then measurements from stake
to edge for successive years is probably the most useful for rate
(either positive or negative) determination through regression analysis.
It is theoretically possible to determine the rate of closing of Shel-
low open water areas with these data plus water depths and inundation

data using a multiple regression.

I3

As noted previously, these transects seem to fit prisere areas
better because the rate of change in vegetation composition is rather
slow and often one community is pushed out by another. Water levels
that differ from year to year in depth, period of inundation, and time
of inundation increase the complexity of the analysis but do not rule
out the possibility of rate determinations. Rates are then predictable
under particular sets of conditions. When data of this nature are
available, results of management techniques based on water control are
predictable in terms of edge migration.

I am well aware of several situations that can and do arise to
confound transect results. As an example, muskrats may over-utilize
the vegetation at times of high water preceded by low water that pro-
duced lush growth; but in this case muskrats are one of the factors of
a particular management technique that can be accounted for in predict-
lng the rate of edge migration.

Rates of edge migration undoubtedly follow curves other than line-
ar and are probably governed by conditions in the particular marsh.
Hence, the particular curve for such rates in each marsh must be deter-
mined using data from that marsh.

Stratified random sampling should be used to determine the actual
abundance of species. Results can then be used for several different

analyses.

Suggested outline for random sampling
Stratify the area in question into a series of fairly homogeneous

vegetative types. Indirect stratifications may be done according to

I4

elevations and/or water levels, soil series, or from air photos.

Determine the number of plots necessary for prisere areas. The
number necessary and the uses of the data are few. Usually these areas
are fairly homogeneous within a particular community with relatively
few species. Therefore, only a very small number of plots are neces-
sary and the only use is strictly as an inventory. For subsere areas,
succession is much more rapid and some stages may either be skipped or
present Simultaneously. This means the number of different species is
extremely large at any given time and the composition changes tremen-
dously with respect to time. Therefore, a greater number of plots are
needed than for a prisere.

Pick a series of random samples for each stratum, the plot size
and the data collected to be as previously described. Use a reference
point for each stratum (post, tree, etc.) so that stratum boundaries
and sample plots can be determined by compass and pacing.

Three uses for these data besides Inventory come to mind, and all
point towards obtaining a measurement of usefulness for two purposes--
for management to balance against cost and for research to compare with
other subseres.

First, it might be possible to form a ratio of the primary succes-
sion plants to the secondary ones and to project this over time until
the ratio is zero.

The second suggestion is a variation of the first. Instead of us-
ing succession stages as criteria, use a ratio of useful to unuseful

plants over years where usefulness of a species is gauged by its value

as a duck food.

IS

The third suggestion is to use these data for comparisons between
subseres or yearly changes in Single areas. Hence, some method for
comparing totally different species and communities must be devised.

I think the following method has some merit:

Each duck food producing species found within a sample plot is to
be rated on average seed production as to excellent, good, fair, poor,
or none. These indices then get an arbitrary scaling from 5 to I re-
Spectively. A plant may produce seed in, say, "excellent" quantities
for its species, but it is not directly comparable in seed production
with another species of "excellent" rating. This can be corrected by

choosing as a base a plant such as Polygonum Iapathifolium. Now each

 

species can be compared to the chosen base, i.e., the "excellent" for
Species A may be equal In total seed production to a "fair" E, Iapathif-
gfllugy Thereby the ultimate rating for Species A is 3 and not 5.
Summation of the products of this ultimate rating times plot density

for all duck food producing species within the plot, then extending

this procedure over all plots, yields comparable seed production figures
for all plots within and between strata.

The plot Index figures have ordinal scaling which will allow test-
ing within stratum segments, between strata, or conceivably between
marshes with the Mann-Whitney "U" test (Siegel, l956). To test adja-
cent experimental plots, the Friedman 2-way analysis of variance
(Siegel, l956), also a non-parametric test, could be used but requires

related samples. It also needs at least ordinal scaling.

I6

I have neglected to put any calendar dates or time limits on the
vegetation inventories. These have been conscious omissions. Survey
dates are dependent upon geographical location of the marsh, climate,
inundation period, length of growing season, and most important--what
the investigator wishes to learn from the inventory. For some studies,

several inventories in one year would be desirable or even necessary.

DISCUSSION

 

The primary purpose of the method outlined is to save field time
without sacrificing accuracy. A negative correlation undoubtedly
exists between the amount of time spent outlining the data collection
procedure and the resulting field time required, whereas a positive
correlation exists between the amount of planning time and the degree
of precision that will be gained. The Situation can be likened to the
overworked but often unheeded proverb about an ounce of prevention be—
ing worth a pound of cure. A c0py of the instructions I composed for
inventorying a section (see Appendix, Figure 2, for picture of area)
of the Maple River State Game Area is appended (Vegetation sampling
instructions for Maple River West). The high and low vegetation strata
were purely for inventory while the rest of the outlined procedures
had at least a dual purpose.

The establishment of ecotone transects takes time and personnel,
but once established they can be traversed and samples taken in a rela-
tively short period. The measurements and quadrat data (Appendix,
Tables 8 and 9) in addition to applications discussed under "Theory,"

can be used to delineate sample Spaces for the stratified random

l7

sampling and, supplemented with air photos and personal observations,
to make detailed cover maps (Appendix, Figure 3) of the areas (Bennett,
et aI., I96l).

In a good day, I figure on locating and sampling 40 to 50 I/4
milacre quadrats in rank growth. From data collected at the Maple
River State Game Area two inexperienced aides working as a team (one
of the aides had not studied aquatic plants prior to this assignment)
located and censused 98 plots in four days in rank growth (high and
low vegetation strata, Table I), and collected other information. Uti-
lizing information from the first table (Table I), the second table
(Table 2) presents the inventory results and calculated confidence
limits (according to Cochran, I953) for the plant groupings in which
I was interested.

The estimates derived from the high and low vegetation strata
(Table 3) Show a remarkable stratification done entirely from air
photos using a stereoscope to separate the strata. There was abso-
lutely no ground reconnaissance beforehand in relation to vegetation
distribution. The point I wish to stress is that 98 I/4 milacre
plots more than adequately censused 83.5 acres of heterogeneous marsh

vegetation!

l8

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DUCK NESTING INVENTORY

SUMMARY OF EXISTING TECHNIQUES

MosT Techniques for esTimaTing duck or goose nesT abundance (Geis,
l956) follow The paTTern used by L. J. BenneTT (I938). He aTTempTed
In several ways To find all nesTs (complefe census) in an area. Even
wiTh a poinTing dog, only 75 percenT of The nesTs were found. He con-
cluded ThaT probably The besT way was for Two individuals To drag a
rope across sample sTrips if Trained dogs were noT available. BuT
dragging a rope, wiTh or wiThouT Tin cans or chains aTTached To flush
hens, ls resTricTed To Open grassy areas of fairly level Terrain.

OTher invesTlgaTors (Glover, I956; Burgess eT al., I965, for ex-
ample) resTricTed The size of The search area, making no aTTempT aT a
compleTe census and used IocaTed nesTs as indexes (wiTh pair and brood
counTs) To calculaTe ToTal producTion and morTaliTy of young.

STeel ef al. (l956), along wiTh a sysTemaTic search of dry areas,
also aTTempTed a sampling Technique using boaT and moTor for esTimaTing
marsh nesT producTion. IT seemed To work besT for divers and Is an
inTrlguing Technique ThaT should be explored furTher.

Mosf duck nesTs have been IocaTed close To The waTer's edge
(Burgess, I956; BenneTT, I938; Sfeel ef al., I956; Rogers, l964) buT
some nesTs have been found Two miles from wafer and oThers Two miles
from land (WrighT, I948).

Because of species differences in nesT siTe preference, general
adapTabiliTy, and willingness To Travel long disTances over land from

nesT To waTer, any possible duck nesTing invenTory Technique will be

22

23

Taxed To furnish useful and reliable quanTiTaTive daTa. Hammond and
Forward (I956) presenT daTa illusTraTing The facT ThaT nesTing sTudies
usually provide unreliable informaTion on producTion because of dif-
ferenTIaI predaTion on IocaTed nesTs. They feel The greaTesT value of
a nesTing sTudy is To learn deTalIs of nesT densiTy, disTribuTIon,

and cover.

315.98.:
I sTilI Think a nesT lnvenTory can be useful buT wiTh emphasis
placed on The lack of nesTs as a measure of habiTaT raTher Than on nesT

densiTy as a facTor in calculaTing ToTal producTion. The brood census
will give an esTimaTe of ToTal broods in The marsh; whaT is needed is
an evaluaTlon To deTermine wheTher more broods could be produced in
The marsh area Through Improved nesTing siTes. Hence, my proposed
meThod ls poinTed Towards The presenT day ouTlook which dicTaTes we
musT sTrive for maximum uTilizaTion of nesTing grounds (GriffiTh, I948).
When aTTemst are made To improve an area for nesTing, a species re-
sTrlcTion on The poTenTlal brood increase will undoubTedIy be imposed.
For example, species like The Ring-necked Duck (AyThya collaris) and
The Blue-winged Teal (Anas discors) would probably benefiT mosT if The
alTered area is nexT To waTer Though oTher species also mighT nesT in
The Improved area (I have found several Mallard (Anas plaTyrhynchos)
and Black Duck (Anas rubripes) nesTs on small man-made islands).

A basic assumpTion for This meThod when used for esTimaTing ToTal
nesTs is ThaT all hens will be on The nesT aT The Time of The invenTory.

This assumpTion probably is noT True, buT I Think (given a fairly large

24

sample) iT is safe To assume ThaT a fairly consTanT proporTion will be
on nesTs, Therefore, yearly differences of fair magniTude wiTh no over-
lapping confidence limiTs will demonsTraTe real differences aT The
chosen risk level.

My prOposed meThod does noT uTilize a dog, buT a sTrip census Tech-
nique similar To ThaT used for grouse (King, I937) could be adopTed if

dogs are available.

FIELD USE

Two facTors should be considered before sTarTing a nesT survey.
My proposed meThod, Though more versaTIle Than The rope-dragging Tech-
nique, is resTricTed as To where IT can be applied. Also, since nesT-
ing is sTrung ouT over a long period because of laTe-nesTing species
and because of renesTing aTTemst, more Than one survey may be needed

in an area, wiTh Times picked accordingly.

SuggesTed ouTline for nesT invenTory

 

STraTify The enTire area subjecTIvely inTo general caTegories of
expecTed nesTs; "none," "few," "several," and "many," for example.
"None" would be ToTally Open waTer areas, "few" would be areas of dense
caTTail or Open mud flaTs, eTc. Then divide each sTraTum inTo longiTu-
dinal sTrips of predeTermined widTh. Choose sTrips To be invenToried
aT random according To laws of opTimum allocaTion, i.e., based on area
and variabiIiTy (which reflecT esTimaTed nesT densiTy).

Several of The ways of nesT censuslng in sTrips probably are saT-

isfacTory buT I will cover only The one I used while aT The Erie Club.

25

This meThod called for Three men To walk abreasT aT IO-fooT inTervals,
each man carrying a sTaff and swinging iT Through The vegeTaTion aT a
heighT of approximaTely Ii feeT above The ground. In This manner each
man surveyed a IO-fooT sTrip (five feeT eiTher side of The line of
Travel) giving a ToTal sTrip widTh of 30 feeT. More people can be used
if available, Thereby increasing The sTrip widTh and decreasing The
number of samples needed.

DaTa collecTed from such a sampling meThod can Then be used To
obTain an esTimaTe of The ToTaI nesTs wiThin The sampled area and To
compuTe confidence limiTs on The esTimaTes.

If small nesTing Islands occur in The marsh being sTudied, sTraT-
ify Them using The same crITerion, choose a random sample of islands,
and lnvenTory The picked islands compleTely. Then The ToTal nesTs,

wiTh confidence limiTs, can be compuTed for all islands.

DISCUSSION

A desirable side-effecT of randomly choosing sTrips To census and
running a sTrip only once is The possiblliTy of reducing The chance of
predaTors learning To locaTe nesTs more easily by following The human
spoor.

The resulTs of The survey l conducTed on The Erie Club marsh
(Table 4) demonsTraTed ThaT There was no dearTh of nesTing siTes, jusT
ThaT siTes on dikes were Too accessible To predaTors. The deserTion
of nesTs on Islands probably resuITed from harassmenT by muskraTs which
clipped all grass nesTing cover To wiThin abouT Two inches of ground

level. Probably The besT way To raise brood producTion on ThaT marsh

26

would be To increase The number of nesTing islands and provide beTTer
muskraT conTrol. Since Trapping of muskraTs probably will noT suffice,
conTrol can be aided by planTing unpalaTable woody species such as

biTTer nighTshade (Solanum Dulcamara) on The islands along wiTh grass

 

(nesTs in The shade of woody shrubs were neiTher exposed by The musk-
raTs nor subsequenle abandoned).

This meThod should yield useful informaTion wiTh much less Time
and efforT Than any aTTempT aT a ToTal nesT census. DaTa from a nesT-
ing sTudy need noT be compleTe for deTermining producTion, since The
brood lnvenTory meThod described in The nexT sechon, l hOpe, esTimaTes

The ToTal number of broods on The area aT The Time of survey.

27

 

 

Table 4. Duck nesTing
No. of
Species Eggs Area DaTe
Mallard IO* Island No. I, nesT abandoned 6/I6/6I
Mallard 7 Island No. IO, sTarTing incubaTion. 6/l6/6I
HaTched 7/I2/6I
? Bl./Ma. I* Island No. IO, nesT abandoned 6/l6/6l
Black 7 Island No. IO, sTarTing IncubaTion. 7/l2/6I
Abandoned
B.W. Teal I2 30 yds. easT of wier on so. side 6/I6/6l
of dike, l0 yds. so. of road.
LaTer broken up
Mallard l Island l2 6/l7/6I
Mallard 2 Island I4 6/I7/6l
Mallard 9 Island I5 6/l7/6I
Mallard 5 Island I7 6/l7/6l
Mallard 3* Blind on Island l9, abandoned 6/l7/6I
B.W. Teal I So. side of Sulfur Springs, on
dike. Increased To Two eggs
and boTh broken by 7/4/6l
B.W. Teal 8 So. main dike, direchy so. of 6/24/6l
Is. l7, 5' from road. June 30,
only 4 eggs IefT, no sign of break-
age. July 2, four previously re—
maining eggs gone, no sign of
breakage.
Mallard 8 I5' SE of lasT sTake on firsT 7/5/6I
TransecT N of Sand Island.
LaTer broken up
*RoTTen

 

(From BenneTT eT al., I96l)

I I III-ll J

Il‘l

DUCK BROOD INVENTORY

SUMMARY OF EXISTING TECHNIQUES

 

PresenT brood invenTory Techniques are basically of Two Types;
large-scale surveys used To form yearly indexes of ToTal waTerfowI
producTion and InTensive sTudies on single marshes or small areas To
deTermIne acTual producTion or use. DaTa from duck brood invenTories
on small areas have ofTen been used as an adjusTmenT facTor To correcT
resuITs of oTher sTudies.

L. J. BenneTT (I938) ouTlines an exTremer Time-consuming Tech-
nique for esTimaTing duck producTion ThaT enTaiIs deTermining ToTaI
nesTs in The area, percenT of nesTs successful, and number of young
(reaching flying age) per female. Hammond and Forward (I956) presenT
daTa To illusTraTe ThaT duck nesTing sTudies usually provide unreli-
able producTIon informaTion. Many oTher invesTigaTors, for example,
Glover (l956), STeel eT al. (l956), and Burgess eT al. (I965), used
esTimaTed breeding pairs as being equal To The ToTaI number of nesTs
sTarTed, Thereby eliminaTlng an inTensive nesT survey by adding a
breeding pair survey.

STIII oTher observers (Berg, I956; Geis, I956; WrighT, I948;
Rogers, I964) feIT ThaT Through InTensive field work They were able To
locaTe all broods In Their sTudy areas. Hence, Their producTion esTi-
maTes were absquTe counTs. STewarT (l958) aTTempTed in several dif-
ferenT ways To geT acTuaI counTs of wood duck producTion Through obser-
vaTions. He concluded "ThaT brood surveys are noT sufficienle sensi-

Tlve To indicaTe True Trends in wood duck popuIaTlons." The Technique

28

29

ouTlined by Blankenship eT al. (I953) for locaTlng broods by flushing
can be exTremer accuraTe depending on efforT buT puTs such a Tremen-
dous demand on Time and personnel ThaT iT is usually noT feasible for
areas oTher Than of small poThole size.

Hochbaum (I948) sTaTed ThaT "There are conflicTing reporTs of The
numerical ToTaI for The waTerfowl populaTion. DifferenT groups give
ouT differenT figures obTained by differenT meThods in differenT ranges
aT differenT Times of The year." If a large-scale brood survey de-
signed To esTimaTe ToTal producTion was aTTempTed using The previously
described Techniques, These shaky pOpuIaTion esTimaTes would probably
have To serve as a base.

In I935 The More Game Birds in America FoundaTion conducTed The
firsT wide-scale ground and aerial survey of The Canadian weTlands
(CarTwrighT, I944). They believed The resulTs of This survey esTimaTed
ToTal producTion. The same survey (CarTwrighT, I948) was IaTer con-
ducTed by Ducks UnlimiTed. QuiTe ofTen, in The firsT aTTemst aT a
complex survey by a sporTsman-orienTed group, The zeal wiTh which The
work is conducTed is greaTer Than The accuracy of The esTimaTe; This
survey was no excepTion.

Because of The apparenT difficuITies in esTimaTing ToTal produc-
Tion wiTh presenT Techniques, a sysTem based on TransecTs has been de-
vised for deTermining yearly indexes of producTion (SmiTh and Hawkins,
l948; Day, I949; Miller, I949). IT is sTill in use (Crissey, I960) as
The only large-scale survey. This Technique has several difficuITies

(SmiTh and Hawkins, I948) ThaT need eliminaTlng, and undoubTedly iT

30

will never be The panacea which all waTerfowIers are sTriving for.

I feel There is a definiTe need for a meThod of esTimaTing acTuaI
producTion ThaT is noT so Time-consuming as To be impracTical (Pirnie,
I935). In The hope of sTimulaTing a differenT mode of brood-esTimaT-
Ing procedure, I submiT a meThod based on sampling which has been TesTed
wiTh some success aT an ImpoundmenT of approximaTely 70 acres of re-
cenle flooded Timber and brushy lowlands on The area of The Rose Lake
Wildlife Research CenTer (Kadlec, l964).

As implied by The TiTle of This secTion, my proposed meThod is
devised To obTain a quanTiTaTive measuremenT and will noT furnish a
qualiTaTive measure for parTicular habiTaT Types excepT Indirechy
Thnough preponderances of sighT records from proximal observaTion
polnTs. EsTainshed Techniques of beaTing ouT a secTion (Blankenship
eT al., I953) and of using dogs (Pirnie, personal communicaTion) for
locaTlng broods for observaTion sTill seems The besT for measuring The
qualiTy of a parTicular marsh secTion aT a given Time of day. For ex-
ample, from my observaTions used for broods esTimaTes, no real evalu-
aTion of escape cover is possible. Because counTs were made only when
broods exhibiT The greaTesT movemenT wiTh The observer concealed and
moTionless, broods were noT sTimulaTed To seek or use escape cover.

As wiTh any meThod, boTh advanTages and disadvanTages are InherenT.
The field Time involved can be minimal buT precise brood idenTIficaTion

and accuraTe aging of young (Gallop eT al., I954) are "musTs."

3|

£293!

The Theory behind The experimenTal model is ThaT as The number of
differenT broods seen increases, iT becomes progressively more diffi-
cuIT To see a "new" brood. The raTe of This decline when compared To
The raTio of differenT broods seen To ToTal brood sighTings (including
repeaTs) follows a IogariThmic series curve. The formula which I pro-
pose for esTimaTing ToTal broods was originally designed To esTimaTe
The number of planT species in an area of known size (Evans eT al.,
l955).

The meThod, when used in impoundmenT evaluaTion To compare wiTh
anoTher impoundmenT or wiTh ITself, esTimaTes The ToTaI brood use.

The exisTence of brood movemenT In or ouT is immaTeriaI (and apparenle
self—compensaTing) excepT for iTs impacT on The meThod iTseIf when The
survey period is Too long.

The basic formula, wiTh The symbol ldenTificaTion I used, is as

 

follows:
logl0 (n + I)
where B = esTimaTed TOTaI broods

b = number of differenT broods seen
n = ToTal brood sighTings
N = TheoreTicaI esTimaTed ToTal brood sighTings
necessary To see all The broods
N is an unrealisTic value buT logical appearances of The number
is ImmaTerial. ThaT iT is equal To The TheoreTical number of ToTal

nod sighTings necessary To see all broods can be easily demonsTraTed:

32
B = b loglo (N + I)
loglo (n + I)
when all broods have been seen, B = b
Therefore: N = n
The formula conTains Two unknowns, B and N. The N values musT be
assumed; I submiT They fall around The poinT on The IogariThmic curve
where The TangenT sIOpe Is .008. So To calculaTe N deTermine iTs value
aT The poinT where The TangenT To The curve is .008.

Following is The derivaTion of The sIOpe formula:

 

 

logI0 (n + I)
for any parTicular problem b = a consTanT, X
Ioglo (n + I)

N + I 3'N when N is large

B = X IogloN
dB/dN = §_Iog|0e
N
dB/dN = b/log|0(n + I) Iog|0e

 

N

Then by Transposing The equaTion inTo The following form iT can

be used To calculaTe N.
b
N = IogldTn T I) log|0e

dB/dN

 

The slope value of .008 was empirically derived and subsequenle
judged To be reliable. This is noT The procedure for calculaTing N
I firsT devised. The original scheme called for arbiTrarily picking
differenT values for N and compuTing B values from The esTimaTing

formula unTII B = B' where B' = N,
b

33

Why The new N?

 

A Table of comparisons beTween The TangenT and The B = B' proce-
dures of deTermining N is aTTached (Table 5); counTs IisTed in Table 5
were made by personnel of The Michigan DeparTmenT of ConservaTlon as-
signed To The Rose Lake Wildlife Research CenTer and by myself. The
error values (differences beTween brood esTimaTes compuTed from The
Two procedures) form a sTralghT line, and have an inverse relaTion wiTh
esTimaTed broods. IT is readily apparenT ThaT This musT arise purely
from The differences in N values since The brood esTimaTion formula
remains unchanged. I believe The beTTer of The Two N esTimaTing pro-
cedures can be deTermined by looking aT The Table showing The resulTs
of The Time sTudy (Table 6). The greaTesT difference in B beTween The
Two procedures is in The I5-minuTe period which is also The Time of
fewesT observaTions. The final N value is fairly large and comparable
in all cases. When The probabiliTies (see probabiliTies secTion) of
The nexT brood seen being a "new" brood are calculaTed for all Time
caTegories, IITTle change Is observed for The sIOpe procedure while a
larger change appears in The B = B' sbheme.

WITh N being large and The probabiliTy being exTremely small for
final values, Then The smaller changes should be from beTTer approxi-
maTions of N. Therefore, I conTend The slope procedure for deTermin—

Ing N values is more universally applicable.

ProbabilITies

CalculaTions of The probabiliTies under each Time caTegory for

boTh esTimaTing procedures over all years were made for Two reasons:

34

To observe The conTinuiTy over Time periods for each scheme, and To
shed IighT on which is The beTTer of The Two esTimaTing procedures.

ProbablliTies were calculaTed from The formula (Feller, I950):
I“) M
qk = k r-k IeT r = k = l
n
r

which becomes:

 

for The nexT evenT using my esTimaTing formula symbols. Since The
formula uses The unrealisTic value N, The resulTanT probabiliTy is also
unrealisTic and is only To be considered as a pure number conTrasTable

in magniTude alone.

FIELD USE

The meThod calls for making observaTions from predeTermined poinTs
and TabulaTing all observed broods (noT flying) seen according To spe-
cies, age, and number. ObservaTIon periods are The firsT 2 hours of
daylighT (sTarTing approximaTely i hour before sunrise) and The I hour
before dark (sTarTing approximaTely l5 minuTes before sunseT).

If The observer keeps sTiIl, broods will move abouT freely, and
The differences In wariness beTween species should Thereby be minimized,
albeiT some broods are more readily seen Than oThers and are more likely
To repeaT. A random sample of broods and of species is TheonITically
possible as long as The observer is Trained To look boTh in edges of
vegeTaTion and In open areas. Kadlec (I964) presenTs daTa supporTIng

This assumpTion.

35

EsTablished observaTion poinTs, preferably lookouTs hidden in
Trees To reduce disTurbance (Beard, l964), should be used. These are
To be siTuaTed so ThaT a fairly large area of The marsh is under sur-
velliance from each poinT, buT when The area seen from all poinTs is
compared To The ToTal area, iT can be exTremely minimal. The only
criTerion possible To use for placemenT and number of observaTion
poinTs is The number of broods and The esTimaTed degree of brood mo-
biliTy for The Individual area where The meThod Is To be employed.
Every brood should have The chance of being seen, i.e., each brood
should pass wiThin sighT of an observaTion poinT someTime beTween
haTchIng and The flying age.

An exTremely large sample area can be furTher sTraTlfied or sub-
divided To reduce counTs necessary for sample esTimaTes based on brood
mobIlITy.

ApproximaTely 3 counTs per sTaTion are necessary, buT ToTaI obser-
vaTions can conceivably run from 2 To 6. The adding of more counTing
sTaTions on a sample pIoT reduces The number of observaTion Times needed

per sTaTion.

SuggesTed ouTline for conducTing brood invenTory

Randomize The sTaTions and The observaTion periods per sTaTion by
using a LaTIn square: IT may become necessary To Throw ouT cells from
The square when The number of counTs and The number of sTaTions are
noT equal.

The counTing Time per observaTion period was originally seT aT 45

minuTes. This meanT only 3 counTs per day were possible If The counTing

36

period limiTs are observed. By recording The Time of each brood obser-
vaTion, several Time caTegories can be devised and The esTimaTed number
of broods calculaTed. Table 6 has The resulTs of The caTegories I

felT worThy of TesTIng. ThirTy minuTes, IT appears, Is ample counTing
Time.

Ideally counTs should be made afTer all renesTing aTTemst have
haTched and before any early haTched broods have sTarTed flying. For
souThern Michigan laTe June and early July seem nearly OpTimum. The
formula is designed To give an InsTanTaneous esTimaTe of broods presenT
aT Time of counT. This means ThaT The necessary counTs for a reliable
esTimaTe have To be conducTed in a fairly shorT period of Time. If The
area To be invenToried is large, iT can be broken InTo blocks and each
block TreaTed as a separaTe impoundmenT. I Think all counTs for a
single impoundmenT of relaTively small size should be compleTed In The
space of one week. CounTs should be made only on days having no rain

and IITTIe or no fog during counTing periods.

SuggesTed meThod for calculaTing esTimaTes

For calculaTing brood esTimaTes The algebraic manipulaTions can
be lessened by firsT calculaTing The b/Iog'o (n + I) value. Then N
can be calculaTed by mulTiplyIng The value by .43429/.008. The loga-
riThm of N is Then mulTipIIed by The firsT division and calculaTes The
ToTal number of broods.

In maThemaTical Terms:

IeT XI= ' b
loglo (n + I)

37

N = XlogIQe
dB/dN

N = .43429X
.008

and Then:

ToTaI Broods (B) = XIogION

DISCUSSION

 

Table I3 from Kadlec (l964) is appended (Table l0). IT conTains
The resulTs of The brood lnvenTory and a comparison of The known broods
presenT (a minimum figure) by species for 2 years. The "shore circuiT"
counTs, or "circuiT" counTs as I chose To call Them, were also Tried
as a possible fuTure Technique.

Kadlec was able To spend considerable Time Trying To deTermine The
acTual number of broods using The area, buT he IefT prior To The I963
invenTory. Since Then nobody has been able To devoTe The necessary
Time To obTain The known broods presenT figure wiTh which To compare
The esTimaTe from The proposed meThod.

As a resuIT, I have recommended conTinuaTion of The circuiT counTs
as a parTiaI check on The observaTion poinT counTs (Table 5). I fully
reallze ThaT The circuiT counTs are subjecT To personal bias (which
can be easily demonsTraTed), buT This bias is somewhaT predIcTable from
knowing The personnel. The more familiar They are wiTh brood behavior
and The survey area, The greaTer The inflaTion due To personal bias.

I am fairly saTisfied ThaT The lnvenTory meThod I have proposed
gives beTTer esTimaTes of ToTal brood use on a single impoundmenT for

The Time expended Than any oThers wiTh which I am familiar. In areas

38

having boTh early and laTe nesTing species iT will probably be neces-
sary To run The survey Twice and have iT species-orienTed.

In I964 The opporTuniTy arose To aTTempT using The meThod on a
series of small lmpoundmenTs in close proximiTy To each oTher and some-
whaT similar To The Rose Lake ImpoundmenT In habiTaT and expecTed waTer-
fowl species. I divided The area inTo Three separaTe secTions and
assumed no brood InTerchanges beTween secTions (noT an alTogeTher valid
assumpTion buT of IiTTIe consequence when movemenT ls slighT). WiThin
each secTion I assumed There would be free inTerchange beTween The im-
poundmenTs, so I TreaTed each secTion as a large single impoundmenT wiTh
one observaTion poinT per small impoundmenT (Two had Two poinTs because
of large size) wiThin iT, i.e., seven small impoundmenTs In a secTion
would have seven observaTion poinTs.

The counTing Times were again randomized wiTh a LaTin square de-
sign by secTion. Final esTimaTes were To be calculaTed also by secTion.
To SpeculaTe a biT furTher, I believe The meThod can be adapTed

To invenTorying waTerfowl producTion aT leasT on The small inTerIor
marshes of a sTaTe. To accomplish such a survey would enTail sTraTify-
ing all areas InTo expecTed number of broods caTegories, plcking a
random sample, making counTs and esTimaTing ToTals on Those picked,

and applying Those resulTs To The apprOprIaTe sTraTum. EberhardT (I963)
explains beTTer Than I The reasoning for This meThod.

"When mobile populaTions are involved, any probabiliTy sampling

scheme is likely To be essenTIaIIy 'Two-sTage' or 'clusTer'

sampling. ThaT is, sTraTifIcaTion by areas may be quiTe

39

feasible, and random samples of areas wiThin sTraTa can be
drawn, buT rarely will iT be possible To enumeraTe acTually
all individuals on The selecTed sample areas. Some kind

of subsampling Thus becomes involved, ofTen wiTh selecTion
probabiliTies quiTe Thoroughly unknown. Whlle The quesTion
of cenTral imporTance concerns The bias of These subsam-
pling esTimaTes, a mildly comforTing general principle Is
ThaT esTimaTes of over-all variabiliTy may be based on The
ToTals or means for The subareas, wiThouT dealing direchy
wiTh The variabiliTy of subsampling (aIThough such vari-

abiliTy is, of course, an inTegraI parT of The whole)."

The biggesT drawback, I believe, for seTTing up such a large-scale
survey is neiTher The maThemaTIcs nor sTaTisTics ThaT would be neces-
sary, buT The InabiliTy of observers wiThouT prior Training and experi-

ence To be able To idenTify and age broods accuraTely.

40

Table 5. Brood esTimaTes

 

The error column shows The difference beTween B values deTer-
mined from using N values compuTed from The TangenT of .008 and from
The formula B = B' where B' = N,

 

 

b
.008 TangenT slope
"B" esTimaTe Error
l96l
CircuiT counT* 2| +3
ObservaTion counT* 2l +2
Kadlec and sTudenT aide**
I962
CircuiT counT 40 -2
ObservaTion counT 30 +I
Kadlec**
I963
CircuiT counT 36 0
ObservaTIon counT 40 -|
BenneTT and sTudenT aide**
I964
CircuiT counT 34 0
ObservaTion counT 30 +l

BenneTT and Duvendeck**

*These daTa are from Two differenT Types of counTs made on The im—
poundmenT of The Rose Lake Wildlife Research CenTer.

**ObservaTions made by:

DaTa collecTed laTe June and early July each year.

4|

Table 6. ObservaTion Time sTudy, using daTa from observaTion poinT
counTs on The impoundmenT of The Rose Lake Wildlife Research CenTer.

 

 

IS 30 35 40 45
minuTes minuTes minuTes minuTes minuTes
I96l
DifferenT broods 6 9 9 l0 Il
ToTal sighTings 9 l6 I8 20 22
B from slope form. l5 l9 I8 20 2|
ProbabiliTy** .0284 .0262 .0247 .0256 .0240
B from B = 8' form. ll l6 l5 l7 l9
ProbabiliTy .0893 .0556 .05l3 .0473 .0435
I962
DifferenT broods II I5 l7 l7 I7
ToTal sighTings I6 25 3I 32 35
B from slope form. 24 29 3| 3| 30
ProbabiliTy .0277 .0255 .024l .0243 .0233
B from B = 8' form. 2| 28 3| 30 29
ProbabiliTy .046l .0332 .0285 .0269 .0268
I963
DifferenT broods I3 20 20 20 22
ToTal sighTings I5 33 36 39 42
B from slope form. 30 37 38 37 4I*
ProbabiliTy .0298 .025I .02l7 .0208 .0222
B from B = 8' form. 28 38 39 38 42*
ProbabiliTy .0436 .0566 .0230 .0224 .0205
I964
DifferenT broods I2 l6 l6 I7 l7
ToTal sighTings 20 30 32 37 37
B from slope form. 24 30 29 3O 30
ProbabiliTy .0254 .0254 .024l .0238 .0238
B from B = 8' form. 22 29 28 29 29
ProbabiliTy .0370 .0304 .0289 .0263 .0263

*Brood observaTion Times were missing for 2 counTs so four
brood sighTings are noT Included buT immaTerial To This
observaTion.

**See TexT explaining value's magniTude.

DUCK KILL INVENTORY

SUMMARY OF EXISTING TECHNIQUES

Probably The firsT survey of a sysTemaTic naTure for deTermining
ToTal kill over a large area uTiIized basically a Technique I choose
To call "The hunTer reporT card sysTem" (Lee, I964; Sondrini, I950;
Hayne and EberhardT, I954). Such a Technique has since been scruTI-
nized and deemed unsuITable for acquiring useful daTa (Sondrini, I950;
Hayne and EberhardT, I954; EberhardT, l955)..

Elder (I950) proposed The idea of using an x-ray To deTermine
The proporTion of The duck pOpuIaTion by species carrying lead shoT
(oTher Than IngesTed). He hypoThesized ThaT,

"The amounT of lead shoT fired aT waTerfowl in any parTicular

year, or aT any one species in ThaT year, should be propor-

TionaTe To The number 04 ducks killed or The number killed

of ThaT Species; and also iT should be proporTionaTe To The

number of ducks ThaT are crippled and die, and The number

ThaT survive Their wounds and carry lead shoT in Their flesh

..... An accuraTe measure of any one of These four facTors

should give us an index To all oThers."
If The amounT of lead shoT fired Is consTanle proporTionaTe To The
ToTal pOpuIaTion, Then The four facTors are also pOpuIaTion dependenT
and probably fairly consTanT in Their relaTionshIp To boTh The ToTal
pOpuIaTion and each oTher. Therefore, wiThouT a reliable esTimaTed
ToTal of aT leasT one of The defined populaTions, no esTimaTe of ToTal

kill is possible. Also, since These facTors would differ beTween

42

43

regions, considerable efforT would necessarily be expended gaThering
daTa during a busy Time of The year for biologlsTs (spring) besides
being a difficulT Time To geT around and a difficulT Time To Trap birds.

The U. S. Fish and Wildlife Service aTTempTed a Telephone survey
one year To deTermine ToTaI kill (Day, I949) buT seemingly failed To
secure adequaTe daTa. Recenle They have used a wide-scale mail sur-
vey sysTem (HeaTh and Rosasco, I963) To esTimaTe ToTal kill, and also
a wing collecTion survey (Carney and Godin, I963) To obTain species
composiTion of The kill. Many sTaTes, Including Michigan (Hawn, I964),
now use mail surveys To esTimaTe kIII of several game species.

Even Though mail surveys are widely employed, The daTa should noT
be used in blind faITh; checks need To be periodically employed.

ATwood (l956) illusTraTes Types and magniTudes of biases he found in
a survey of waTerfowl hunTers. Indeed, IT appears ThaT any form of ‘
InTerview, direcT or IndirecT, is vulnerable To bias (reSponse errors)
regardless of The subjecT when answers musT be based on memory--es-
pecially if some measure of compeTence is involved (SToke and Lehman,
I930; ProcTor, l964).

For large-scale mail surveys, The pOpuIaTion being sampled is all
Those who boughT duck sTamps. When a smaller pOpuIaTion is To be sam-
pled, e.g., ThaT using a special area, IT musT be defined. Two Tech-
niques of esTimaTing kill are designed To define The pOpuIaTion and,
in essence, gaTher kill and efforT daTa simulTaneously. Wandell (l946)
and Palmer (I963) boTh used a sysTem of placing cards on cars asking

The drivers To fill in The desired daTa. Cards were Then collecTed by

Technicians (Wandell, l946) or mailed To The invesTigaTor (Palmer, I963).

44

The second Technique uses personal inTervIews To gaTher The daTa
wiTh an acTuaI check of each individual's Take. An early season index
of The waTerfowl kill in Michigan is deTermined Through car counTs and
bag checks on selecTed areas (Mikula, I965). Also, an esTimaTe of
ToTaI fish Taken from cerTain selecTed lakes in Michigan is obTained
wiTh inTerviews and boaT counTs (Taube, I965). This Technique requires
considerable man-days To perform.

Since adequaTe meThods of invenTorying ToTaI kill are already in
use, I propose none of my own, buT describe Two of The beTTer esTimaT-
ing meThods adapTable for single marsh use. The besT esTimaTe would
of course, arise from a check-in, check-OUT sysTem where an absquTe
counT is obTained, buT because of The uncomplicaTed naTure of The esTi-
maTe and The infrequency of such a siTuaTion, I will noT consider This

sysTem furTher.

E951 .

BoTh meThods I am presenTing are based on sTraTlfied random sam-
pling and have compuTabIe confidence limiTs. The firsT is a mail sur-
vey as used by Palmer (I963) and The second a combinaTIon of The Two
personal InTerview Techniques (Taube, I965; Mikula, I965). The one To
be used In a parTicular siTuaTion musT be chosen according To whaT in-
formaTion is desired, how much manpower is available, and how much
money can be SpenT on iT.

For The mail survey meThod, lisTings of hunTers by name and ad—
dress are necessary. Several ways are possible buT The easiesT prob-

ably is To sample cars, record license plaTe numbers, and place a

45

quesTionnalre posTcard in a conspicuous place on The auTo. The name
and address of all The car owners can Then be obTained from The car
license files. This allows boTh a check of The responses on passed-
ouT cards and follow-up mailings To each non-reSpondenT. The ques-
Tionnalre design can eliminaTe much of The bias resulTIng from sam-
pling jusT car owners. The drawback of This meThod Is The hunTer:
you have To assume ThaT he Is honesT and can idenTify waTerfowl, and
ThaT in reporTing kill he uses accepTed and disTlnguIshabIe names.
The bias due To fauITy memory is reduced by asking only abouT ThaT
day. If species kIlI esTimaTes are noT necessary, The hunTer bias is
furTher reduced. This meThod does noT have The demanding manpower
requiremenT of The oTher and is cheaper To operaTe.

The hunTer InTerview meThod calls for having Trained personnel
record The hunTing Time and acTually check all ducks bagged by inTer-
vlewees. EsTimaTes from inTerviews of boTh compleTed and lncompleTed
hunTs are possible as described by Taube (I965) for The InTensive creel
census. The daTa have To be handled differenle.

For compleTed hunTs:

ToTal bag = :1 = bag per hour
ToTaI hours ‘ZX

 

Then ToTal hours hunTed Times ducks bagged per hour esTimaTes The ToTal
duck kill.

For lncompleTed hunTs:

i_ Yi = bag per hour
hirer

number of people conTacTed
caTch

hours

IIh_Individual

II

46

This formula correIaTes The Time hunTed wiTh The probabiliTy ThaT The
parTicular hunTer is In The sample. Variances for eiTher esTimaTing
Technique can be calculaTed from:

Var. E3 = E2 var. S + 52 var. E

E = ToTaI hours
S = bag per hour
ES = ToTal bag

This meThod requires considerable manpower buT assumpTions as To The

hunTer are nonexisTenT.

FIELD USE
BoTh meThods are based on a sTraTifIcaTion of expecTed use by Time
uniT by day wiTh The sum of The Time uniTs wiThin a day ToTaIIng The

hours from opening Till closing of shooTIng.

SuggesTed ouTline for conducTing kill lnvenTory

lnsTanTaneous car counTs are To be made aT Times selecTed by sam-
pling wiTh unequal probabiliTies. The sample space in reaIiTy Then
becomes The ToTaI number of car hours. Figures can be calculaTed
eiTher on The kill per carload of hunTers or per hunTer Through a de-
TerminaTIon of The number of hunTers per car.

InTerview as many hunTers as possible. If only compleTed hunTs
are sampled, The possible bias resulTIng from non-uniform kill of ducks
over Time is removed. This requires several Trained people simulTane-
ously for shorT periods of Time ThroughouT The season in order To

obTain a sufficienTIy large sample.

47

QuesTionnaires for The mail survey meThod need To be placed on
cars periodically ThroughouT The season and can logically be disTri-
buTed during The InsTanTaneous car counTs, Thereby reducing The neces-
sary field Time. Several follow-up mailings will undoubTedly be
necessary for obTaIning a sufficienT response To eliminaTe any non—
response bias (unsuccessful hunTers appear less likely To reTurn ques-
Tionnalres; EberhardT and Murray, I960) and To assure a sufficienle

large sample To give meaningful esTimaTes.

DISCUSSION

Since The above suggesTed meThods are neiTher mine nor previously
used by me, I have no daTa showing The abiIITy of The meThods To esTi-
maTe ToTal waTerfowl kill on a single area. DaTa from Taube (I965)
IllusTraTing personal lnTerviews and from Palmer (I963) illusTraTing
The posTcard mail survey resulTs are appended (Table II and Table l2).

VarIaTions of The proposed meThods deal primarily wiTh oTher ways
of deTermining The pOpuIaTion. For example, If The area were an
island, insTanTaneous boaT counTs, eiTher ToTal or samples, could be

used in lieu of car counTs.

CONCLUSION AND SUMMARY

Previous Techniques of vegeTaTion-and brood producTion-invenTory-
ing neiTher provided reliable quanTiTaTive daTa nor gained The maximum
amounT of informaTion for The ToTal Time expended. When waTerfowl pro-
ducTion Is deTermined from breeding pair, nesT densiTy, and nesTing
success invenTories, which are biased and InaccuraTe for ThaT purpose,
enough man-days To lnvenTory producTion for mosT sTaTes are undoubTedly
consumed.

To employ Techniques of vegeTaTion—InvenTorying on groups of planTs
Taxonomically and morphologically differenT from Those planTs for which
The survey was originally designed inTroduces an unmeasurable error be-
fore fleld work is even begun. Here again The raTio of useful daTa
gained To ToTal energy expended is Too low.

The four invenTory meThods l have presenTed when used as direcTed
should yield quanTiTaTive daTa of a useful naTure wiTh relaTively
IlTTle efforT.

The accuracy of The brood esTimaTing meThod (Appendix, Table I0)
for The years IT was checked was phenomenal, albeiT IT Isn'T ThaT good
' since The meThod Is subjecT To sampling error besides having an empir-
ically derived cuToff poinT. BuT I am willing To accepT inghT errors
In esTimaTed ToTaI brood use To save Time. Only nine man-hours were
needed To invenTory waTerfowl use on The impoundmenT of The Rose Lake
area and even This can probably be reduced by more Than half.

When daTa from field surveys used for InvenTorying have confidence

limiTs In The neighborhood of 25 percenT, I am quiTe saTisfied wiTh The

48

49

sampling procedure and sampling inTensiTy. Especially when, as in The
case of The vegeTaTion survey on The Maple River STaTe Game Area, liTTle
field Time was needed To gain resulTs for a large area. If for some
specific purpose I wish To conducT anoTher planT invenTory on ThaT area
(even for a parTicular species) wiTh, say, I0 percenT confidence limiTs,
I can deTermine The number of pIoTs needed and how much field Time

would have To be expended, or if available field Time Is seT I can de-
Termine whaT limiTs will resulT even before I seT fooT inTo The area.

I am noT aTTempTing To presenT These suggesTed meThods as The
ulTImaTe. If I have seemed dogmaTic iT Is because of my sTrong desire
To sTImuIaTe waTerfowl biologisTs and weTlands ecologisTs To search
for beTTer meThods of InvenTorying based on Their knowledge and on The

work of Those of similar InTeresTs who preceded.

LITERATURE CITED

Anderson, J. M. I950. Some aquaTic vegeTaTion changes following fish
removal. J. Wildl. Mng. l4(2):206—209.

ATwood, E. L. I956. ValidiTy of mail survey daTa on bagged waTerfowl.
J. Wildl. Mng. 20(l):l-l6.

Beard, ElizabeTh B. I953. The ImporTance of beaver in waTerfowI man-
agemenT aT The Seney NaTional Wildlife Refuge. J. Wildl. Mng.
l7(4):398-436.

I964. Duck brood behavior aT The Seney NaTional

 

Wildlife Refuge. J. Wildl. Mng. 28(3):492-52l.
BenneTT, C. L., Jr. I960. STudenT assisTanT final reporT, Shiawassee
NaTional Wildlife Refuge. Saginaw, Michigan. 7 pp. (M.S.)

, W. A. MaTulis, and D. J. Drumm. l96l. Technical

 

reporT of research sTudies aT Erie ShooTIng Club marsh. 56 pp.
(M.S.)

BenneTT, L. J. I938. The blue-winged Teal: ITs ecology and manage-
menT. CollegIaTe Press, Ames, Iowa. xiv + I44 pp.

Berg, P. F. I956. A sTudy of waTerfowl broods in easTern MonTana
wiTh special reference To movemenTs and The relaTionship of reser-
voir fencing To producTion. J. Wildl. Mng. 20(3):253-262.

Billings, W. D. l95l. VegeTaTional zonaTion in The GreaT Basin of
WesTern NorTh America. pp. l0I-l22 in Les bases ecologiques de

la vegeveraTion de la vegeTaTion des zones aides U.I.S.B. Paris.

50

5|

Blackman, G. E. I935. A sTudy by sTaTisTical meThods of The disTri-
buTion of species In grassland associaTions. Ann. BOT. Lond. 49,
749-74 (Append. by M. S. BarTIeTT 775-7.).

Blankenship, L. H., C. C. Evans, M. H. Hammond, and A. S. Hawkins.
I953. Techniques for brood producTion sTudies. ConTribuTlon
for The Miss. Flyway Council Techn. Comm. l4 pp. mimeo.

Brown, DoroThy. I954. MeThods of surveying and measuring vegeTaTion.
CommonwealTh Bureau of PasTures and Field Crops. Bull. No. 42.
Hurley, Berks, England. xv + 223 pp.

Burgess, H. H., H. H. Prince, and D. L. Trauger. I965. Blue-winged
Teal nesTing success as relaTed To land use. J. Wildl. Mng.
29(l):89-95.

Cain, S. A. I937. AndropogoneTum HempsTeadi: A Long Island grass-
land vegeTaTion Type. Amer. Midl. NaT. l8:334-350.

Carney, S. M. and P. J. Godin. I963. Wing collecTion survey in waTer—
fowl sTaTus reporT I963. U. 5. Fish and Wildl. Serv., Spec.

Sci. ReporT - Wildl. No. 75. pp. 3-4.

CarTwrighT, B. W. I944. WaTerfowl brood counTs in ManiToba, SaskaTch-

ewan, and AlberTa, I935, I938-42. J. Wildl. Mng. 8(I):79—80.

I948. The wesTern Canadian waTerfowI breeding

 

grounds. Trans. N. Am. Wildl. Conf. l3:63-68.

Clarke, G. L. I954. ElemenTs of ecology. John Wiley and Sons, Inc.,
New York. xiv + 534 pp.

Cochran, W. G. I953. Sampling Techniques. John Wiley and Sons, Inc.,

New York. xiv + 330 pp.

52

Coupland, R. T. I950. Ecology of mixed prairie in Canada. Ecol.
Monog. 20:27I-3l5.

Crissey, W. F. I960. Aerial invenTory Techniques in waTerfowI manage—
menT. 22nd MidwesT Fish & Wildl. Conf. unpl. reporT.

CurTis, J. T. and R. P. McInTosh. I950. The lnTerrelaTions of cerTain
analyTic and synTheTic phyTosocIoIogicaI characTers. Ecology
3|(3):434-455.

Day, A. M. I949. NorTh American WaTerfowl. STockpole and Heck, Inc.,
New York, Harrisburg. xx + 329 pp.

Dobie, J. and R. E. Johnson. I95l. Pond mapping by aerial phoTo-
graphs. J. Wildl. Mng. I5(2):22l-222.

and John B. Moyle. I956. MeThods used for invesTigaTing pro-
ducTIvITy of fish-rearing ponds In MinnesoTa. Minn. DepT. Con-
serv., DIV. Game and Fish, Fisheries Research UnIT Spec. Publ.
No. 5. 54 pp.

EberhardT, L. L. I955. Preliminary revision of deer kill esTimaTes,
I935-I95l. Mich. DepT. Conserv. Game Div. RepT. No. 2030. 5 pp.

and Rose M. Murray. I960. EsTimaTing The kill of

 

game animals by licensed hunTers. Proc. Social STaT. SecT. Ann.
MeeTing Ann. STaT. Assoc. I20:l82-l88.

. I963. Problems in ecological sampling. NorThwesT

 

Sci. 37(4):I44-I54.

Elder, W. H. I950. MeasuremenT of hunTing pressure in waTerfowl by
means of x-ray. Trans. N. Amer. Wildl. Conf. I5:490-503.

Evans, F. C., P. J. Clark, and R. H. Brand. I955. EsTimaTion of The

number of species presenT on a given area. Ecology 36(2):342-343.

53

Feller, W. I950. ProbabiliTy Theory and iTs applicaTions. John
Wiley and Sons, Inc. New York. xii + 4I9 pp.

Gallop, J. B. and W. H. Marshall. I954. A guide for aging duck broods
In The field. Miss. Flyway Council Techn. Sec. l4 pp. mimeo.

GaTes, D. H., L. A. SToddarT and C. W. Cook. I956. Soil as a facTor
Influencing planT disTribuTion on salT deserTs of UTah. Ecol.
Monog. 26:I55~l75.

Geis, Mary B. I956. ProducTiviTy of Canada geese in The flaThead
valley, MonTana. J. Wildl. Mng. 20(4):409-4l9.

Generosoff, V. T. I934. The culTure of food and cover planTs for
waTerfowl. All-Union CooperaTive AssocIaTed Publishing Office.
Leningrad. l28 pp. AbsTracTed in I936 Wildlife Review No. 3:l6-I9.

GevorkianTz, S. R. I954. Problems in foresTry invenTory from The

foresTer's poinT of view. Pages 25I-262. I_ I. KempThorne, T.
A. BancrofT, J. W. Gowen, and J. L. Lush (eds.). STaTIsTIcs
and maThemaTIcs in biology. The Iowa STaTe College Press, Ames,
Iowa. ix + 632 pp.

Glover, F. A. I956. NesTing and producTion of The blue-winged Teal

(Anas discors Linnaes) in NorThwesT Iowa. J. Wildl. Mng.

 

20(l):28-46.

Goodall, P. W. I952. Some consideraTions in The use of poinT quadraTs
for The analysis of vegeTaTion. AusTraI. J. Sci. Research Series
B. 5(I):I-4l.

Grelg-SmITh, P. I957. QuanTITaTive planT ecology. Academic Press

Inc., New York. Ix + l98 pp.

54

GriffiTh, R. I948. Improving waTerfowI habiTaT. Trans. N. Am. Wildl.
Conf. l3:609-6I7.

Hammond, M. C. and W. R. Forward. I956. ExperimenTs on causes of
duck nesT predaTion. J. Wildl. Mng. 20(3):243-247.

Hanson, H. C. I962. DIcTIonary of ecology. Philosophical Library
Inc., New York. 382 pp.

Hasel, A. A. I954. Problems in foresT invenTory: from The sTaTisTi-
cal poinT of view. Pages 263-272. ig_0. KempThorne, T. A.
BancrofT, J. W. Gowen, and I. L. Lush (eds.). STaTIsTIcs and
maThemaTIcs in biology. The Iowa STaTe College Press, Ames,
Iowa. Ix + 632 pp.

Hawn, L. J. I964. I963 small game kill esTimaTes. Mich. DepT. of
Conserv. Research and DevelopmenT SecT. RepT. No. 4. 8 pp.
Hayne, D. W. and L. L. EberhardT. I954. NaTure of The bias of esTi-
maTes compuTed from volunTary reporTs. Paper presenTed aT The
I6Th MidwesT Wildl. Conf., ST. Louis, Missouri. 8 pp. (M.S.)

HeaTh, R. G. and M. E. Rosasco. I963. WaTerfowl kill survey. In
waTerfowl sTaTus reporT I963. U. S. Fish & Wildl. Serv., Spec.
Sci. ReporT - Wildl. No. 75. Pp. l—3.

Hochbaum, H. A. I948. HarvesTing The waTerfowl crop. Trans. N. Am.
Wildl. Conf. I3:48l-49l.

Jessen, R. L. and R. Lound. I962. An evaluaTion of a survey Tech-
nique for submerged aquaTIc planTs. Minn. DepT. Conserv. SecT.

of Research and Planning, Game InvesT. RepT. No. 6. IO pp.

55

Kadlec, J. A. I960. The effecT of a drawdown on The ecology of a
waTerfowl impoundmenT. Mich. DepT. Conserv. Game Div. RepT.
No. 2276. l8l pp.

l964. Michigan DeparTmenT of ConservaTion. Michigan

 

P.-R. ProjecT W-40-R. Job 2. 43 pp.

KeiTh, L. B. I96I. A sTudy of waTerfowl ecology on small ImpoundmenTs
in souTheasTern AlberTa. Wildl. Mono. No. 6. 88 pp.

King, R. T. I937. Ruffed grouse managemenT. J. ForesTry. 35(6):
523-532.

Lee, F. B., R. L. Jensen, N. J. Ordal, R. I. Benson, J. P. Lindmeier,
and L. L. Johnson. l964. WaTerfowl in MinnesoTa. Minn. DepT.
Conserv. Div. of Game and Fish, Tech. Bull. No. 7. 209 pp.

Leedy, D. L. I948. Aerial phoTographs, Their InTerpreTaflon and sug-
gesTed uses In wildlife managemenT. J. Wildl. Mng. I2(2):I9l-2I0.

Loveless, C. M. I957. Clipping sTudy Techniques In marsh ecology In-
vesTigaTions. Proc. ElevenTh Ann. Conf. SouTheasTern Assoc. Game
and Fish Comm. Pp. II9-I24.

MarTin, A. C. and F. M. Uhler. I939. Food of game ducks in The UniTed
STaTes and Canada. U.S. DepT. Agr. Tech. Bull. No. 634. l57 pp.

Mikula, E. J. I965. WaTerfowI hunTing season Michigan l964. Mich.
DepT. Conserv. Game SecT. ReporT No. 2469. 6 pp.

Miller, H. J. I949. WaTerfowI breeding ground survey, I949, In Michi-
gan. Mich. DepT. Conserv. Game Div. RepT. No. l038. 6 pp.

Moyle, J. B. I945. Some chemical facTors influencing The disTribu-
Tion of aquaTIc planTs In MinnesoTa. Amer. Midland NaT. 34(2):

402-420.

56

Palmer, W. L. I963. Non-hunTing season public use of region Ill sTaTe
game and foresT lands compared To hunTing season use. Mich. DepT.
Conserv. Game Div. RepT. No. 24l2. 7 pp.

Penfound, W. T. and E. S. HaThaway. I938. PIanT communiTies in The
marshlands of souTheasTern Louisiana. Ecol. Monog. 8:l-56.

. I945. A sTudy of phyTosociological relaTionshlps by

 

means of aggregaTions of colored cards. Ecology 26(l):38-57.
Pielou, E. C. I962. Runs of one species wiTh respecT To anoTher in
TransecTs Through planT pOpuIaTions. BiomeTrIcs I8(4):579-593.
Pirnie, M. D. I935. Michigan waTerfowI managemenT. Mich. DepT.
Conserv. Game Div., Lansing. xxi + 328 pp.

and J. FosTer. I964. Summary of Erie research acTiviTies

 

I960 Through I963. RepT. sumeTTed To members of The Erie Res.
Comm. 90 pp. (M.S.)

ProcTor, C. H. I964. ScaTTer, sTabIliTy and vigilance In The response
errors of facTual surveys. Paper presenTed aT The l964 STaT.
workshop sponsored by The SouTheasTern CooperaTive Fish and Game
STaT. ProjecT, NorTh Carolina, sTaTe of The Univ. of NorTh
Carolina aT Raleigh, NorTh Carolina. I5 pp. (M.S.)

Rice, E. L. I952. PhyTosociologIcal analysis of a Tall-grass prairie
in Marshall CounTy, Oklahoma. Ecology 33(I):ll2-ll6.

Rogers, J. P. I964. EffecT of droughT on reproducTion of The lesser
scaup. J. Wildl. Mng. 28(2):2I3-222.

Siegel, 3. I956. NonparameTrlc sTaTisTics for The behavioral sciences.

McGraw-Hill Book Co., Inc., New York. xvii + 3l2 pp.

57

Siegler, H. R. I94l. A waTer planT census Technique. J. Wildl. Mng.
5(4):423-426.

Sincock, J. L. and J. A. Powell. I957. An ecological sTudy of waTer-
fowl areas In cenTraI Florida. Trans. N. Am. Wildl. Conf.
22:220-236.

SmiTh, R. H. and A. S. Hawkins. I948. Appraising waTerfowI-breeding
pOpuIaTions. Trans. N. Amer. Wildl. Conf. l3:57-62.

Sondrini, W. J. I950. EsTimaTing game from licensee reporTs. Con-
necTicuT P.-R. ProjecT 7-R. P.-R. Bull. No. 3. 50 pp.

STeel, P. E., P. D. Dalke, and E. G. Bigeau. I956. Duck producTion
aT Gray's Lake, Idaho, I949-I95I. J. Wildl. Mng. 20(3):279-285.

STewarT, P. A. I958. Some wood duck census meThods and Their evalua-
Tion. Ohio CooperaTive Wildl. Research UnIT Release 209. I3 pp.
mimeo.

SToke, S. M. and H. C. Lehman. I930. The influence of self-InTeresT
on quesTionnaire replies. School and Soc. 32:435-438.

SToudT, J. H. I944. Food preferences of mallards on The Chippewa
NaTIonal ForesT, MinnesoTa. J. Wildl. Mng. 8(2):l00-II2.

SubcommiTTee on Range Research MeThods. I962. Basic problems and Tech-
niques in range research. NaTl. Acad. of Sci., NaTl. Research
Council, WashingTon, D. C. Pub. No. 890. xvi + 34l pp.

Swindale, D. N. and J. T. CurTis. I957. PhyTosocioIogy of The larger

submerged planTs In Wisconsin lakes. Ecology 38(3):397-407.

58

Swindale, D. N. and L. R. Jahn. I956. ResulTs of sampling The sub-
merged vegeTaTion in some cenTral and norThern Wisconsin flowages,
wiTh noTes on environmenT. Wisconsin P.-R. ProjecT W-77-R-3
(phase D). Job No. l-A. 70 pp.

Taube, C. M. I965. EvaluaTion of fish managemenT procedures. Michi-
gan D.-J. ProjecT F-27-R. Work Plan No. 2. 4| pp.

Tryon, C. A., Jr. I954. The effecTs of carp exclosures on growTh of
submerged aquaTic vegeTaTion In PymaTunIng Lake, Pennsylvania.

J. Wildl. Mng. l8(2):25l-254.

Uhler, F. M. and F. B. McGiIvrey. I965. WaTerfowl managemenT Through
waTer-level conTrol. Biennial Prog. ReporT - I963 To I944 Work
UniT A-3.I Bureau of SporT Fisheries & Wildl., PaTuxenT Wildl.
Research CenTer, Laurel, Maryland. 49 pp.

Wandell, W. N. I946. An inTensive meThod of deTermining hunTer numbers
and acTiviTies. Trans. N. Amer. Wildl. Conf. Il:373-382.

WrighT, B. S. I948. WaTerfowl InvesTigaTion In EasTern Canada, New-

foundland and Labrador, I945-l947. Trans. N. Amer. Wildl. Conf.

I3z356-365.

APPENDI X

NECESSARY BACKGROUND INFORMATION

I. Air PhoTos

 

The firsT sTep is To obTain Scaled, verTical air phoTos for base
mapping and for sTraTifyIng vegeTaTion (GevorkianTz, I954; Leedy, I948).
They are cheaper, more accuraTe, and far easier To make and use Than
are ground surveys (Dobie and Johnson, l95l).

A map accuraTe as To ground scale is a necessiTy since The ToTaI
number of ploTs per vegeTaTive communITy musT be deTermined. BoTh
Leedy (I948) and Dobie and Johnson (l95l) give meThods To deTermine map
scale which allows resulTs from a random sample To be applied To The
enTire sTraTum. Aerial obliques (Leedy, I948) Taken in color and aT
lower levels also help In making accuraTe sTraTifIcaTions. The beTTer
The original sTraTifIcaTion, The easier and quicker is The sampling

procedure for any accuracy selecTed (Cochran, I953).

ll. Sgii§_

A soil map showing The general series is usually sufficienT. The
purpose of The map Is fourfold: (I) when compared To The air phoTo,
areas of homogeneous vegeTaTive Types are ofTen found To conform To a
soil series (Billings, l95l) so such a map will help The InvesTigaTor
To sTraTIfy The vegeTaTion; (2) knowledge of The series can dicTaTe
whaT planT communiTies are possible (GaTes eT al., l956) afTer some
form of habiTaT manipulaTion; (3) rankness of aquaTic planT growTh is
dependenT on The firmness of The boTTom (Pirnie, I935; MarTIn and Uhler,

I939); and (4) a knowledge of The disTribuTion of good diking soils

59

60

such as clay is a necessary requiremenT before creaTing conTroIled

floodings.
Ill. Limnology

A cursory limnological sTudy is exTremely desirable. Knowledge
of TurbidiTy, pH, TemperaTures, boTTom conTours, and availabiliTy of
crITical nuTrienTs again will limiT The kind, number, and disTribuTIon
of vegeTaTive communiTies (Moyle, I945).

The greaTesT efforT should be expended collecTing daTa in The
shallows. I have never observed dabblers uTiIizing boTTom feeds in
more Than six feeT of waTer excepT indirechy (e.g., baldpaTes sTeal-
ing food from redheads).

Duck food availabiliTy sTudies should also be included. This
enTails making rough esTimaTes of The abundance of suiTable aquaTic
organisms and of The waTerfowl food porTions of purely aquaTic vegeTa-
Tion. I have no Technique To offer for sampling The vegeTaTion oTher
Than raking up quadraTs which are chosen randomly if possible and Then
raTing The ToTal edible amounT on a selecTed scale devised by The
invesTigaTor.

Duck food-producing vegeTaTion boTh submerged and floaTing should
undoubTedly be sampled Twice during The growing period. AT The Erie
marsh my firsT invenTory showed abouT 95 percenT coverage of sago pond-
weed (PoTamogeTon pechnaTus) in much of The Open waTer area; by mid-
July (second invenTory) wild celery (Valllsneria americana) had replaced
The sago and had as greaT a percenTage of coverage as iTs predecessor.

The sago had borne fruiTs which were also available for food along wiTh

6|

The celery during The fall. In essence Then, a double crOp of waTer-
fowl foods had been produced in The shallow areas.

Since The correlaTion beTween soil and/or waTer chemisTry and
aquaTic planT communiTies and Their disTribuTion Is poor, unrefined,
and general (Kadlec, I960) aT our presenT level of knowledge, a fairly
inTensive limnological field sTudy such as described by Dobie and Moyle

(l956) doesn'T seem jusTifiable if The guides are saving Time and money.

62

73 e Litton: u. I _

“URI—(IO I‘- .I I.

UV:O ‘

 

 

eer.:~ mzah
msakcz.<3
sneemxmeqz Ezu
~$_.eeas
Ezéeérge

A_©m_ .._m +O ++Occmm EOLmv

.cmm_co_z .>+c:oo
ooLcoz .memz O_Lw ..oo.
mco_+moo_ +OemcmLH ._ Ocam_m

63

Table 7. TransecT IocaTIons
TransecT: T-l

UniT: PoTTer's Cove
ToTaI disTance: I,966 feeT
DirecTion: N 830 30' E

STarTIng poinT (T-IA): On souThwesT corner of PoTTer's Cove dike
Ending poinT (T-IB): On norTheasT corner of PoTTer's Cove dike
Q-l is 242' from T-IA in caTTail

0-2 is l78' from Q-l in caTTail

Q-3 is 276' from Q-2 on souThside of sprayed sTrip

0-4 is 455' from 0-3 on norTh side of sprayed sTrip

0-5 Is 5l7' from Q-4 ecoTone of open waTer and caTTaiI

0-6 is l79' from Q-5 ecoTone

Q-7 is II9' from 0-6 in meadow ecoTone

T-IB Is 356' from Q-7 in meadow

TransecT: T-2

UniT: Sulfur Springs
ToTal disTance: l,858.7 feeT
DirecTion: N 40° 30' E

STarTIng poinT (T-2A): BeneaTh dock aT Sulfur Spring roll over

Ending poinT (T-2B): On Sulfur Spring dike wesT of channel To number
-I0 pond and jusT easT of sharp bend in dike

Q-B Is 4l9.7' from T-2A in bulrush on souThwesT side of Horse's head
IO' In from edge of Open waTer

0-9 Is 343' from Q-8 on ecoTone of caTTail and bulrush in Horse's head

Q-IO is 300' from 0-9 on norTh side of Horse's head IO' In from edge
of open waTer

Q-Il Is 348' from Q-IO on norTh side of channel I0' in from edge of
Open waTer

Q-2B Is 448' from Q-II

TransecT: T-3
UniT: Mink Creek and Cain PoinT

ToTaI disTance: 3,354.9 feeT

DirecTion: s 50° 45' E

64
Table 7 (conTinued) - TransecT T-3 (conTinued)

STarTIng poinT (T-3A): 0n wesT Mink Creek dike approximaTely I The
disTance from norTh end of dike To sTarT of research
uniT

Ending poinT (Q-2l): On norThwesT end of largesT island souTheasT of
Cain PoinT

Q-IZ is 676.4' from T-3A on norTh edge of dump spray sTrip

Q-l3 is 65.9' from Q-l2 on souTh edge of dump spray sTrip

Q-I4 is I06.7' from Q-I3 on norTh side of buckwheaT paTch

Q-I5 Is 400' from Q-l4 aT souTheasT corner of buckwheaT paTch

Q-I6 is II3.5' from Q-I5 on souTheasT side of highbank

Q-l7 is 224.8' from Q-l6 ecoTone of caTTail and Open waTer

0-l8 is 388' from Q-l7 ecoTone of meadow and caTTail

Q-l9 is 404.7' from Q-I8 on small pond souTh of souTh dike

0-20 is 552.4' from Q-l9 Tip Of Cain PoinT

Q-2l is 422.5' from 0-20 norThwesT corner of large Island souTheasT
of Cain PoinT

TransecT: T-4

UniT: Secor and area To norThwesT
ToTal disTance: 4,030 feeT

DirecTion: s 53° 00' E

STarTIng poinT (T-4A): On wesT dike norTh of Secor uniT jusT above
sharp bend in dike

Ending poinT (0-32): On ecoTone of caTTail and open waTer souTheasT
of easT Secor dike

0-22 is 388' from T-4A on ecoTone of meadow and caTTail

0-23 is l86' from 0—22 on ecoTone of caTTail and Open waTer

Q-24 is 7l8.9' from 0-23 on ecoTone of open waTer and caTTail jusT
norTh of Secor norTh dike

T-4B is 220' from Q-24 on inside edge of barrow plT inside norTh end
of Secor uniT

0-25 Is 32I' from T-4B on norTh edge of sprayed sTrip

Q-26 is 304.2' from 0-25 on souTh side of sprayed sTrip

0-27 Is 83' from Q-26 on norTh side of mIIIeT paTch

Q-28 is 300' from Q-27 on souTh side of miIIeT paTch

0-29 is 638' from 0-28 in norThwesT corner of S-5

0-30 is l00.6' from 0-29 on norThern parT of wesT side of S-5

T-4C Is 3l7' from Q-30 on inside of barrow piT on inside of souThern
porTion of easT dike

Q-3l Is I70' from T-4C on ecoTone of open waTer and caTTail

0-32 is 284' from Q-3l on ecoTone of caTTail and open waTer

65

Table 7 (conTinued)

TransecT: T-5

UniT: Research uniT
ToTal disTance: l,022.2 feeT

DirecTion: N 86° 30' E

STarTIng poinT (T-5A): 0n dike beTween research uniT and pancake cuT,
abouT midway of The widTh of The research uniT proper

Ending poinT (T-SB): 0n dike beTween research uniT and Mink Creek
souTh of T-3A (Mink Creek sTarTing poinT)

0-33 Is 229.3' from T-5B whole uniT is inTermingled caTTail and meadow
vegeTaTion, sTakes mark The sharper and clearer
ecoTones

0-34 Is 95.7' from 0—33

0-35 Is l23.l' from 0-34

0-36 is I84.4' from 0-35

0-37 Is 239.7' from 0-36

T-5B Is l50' from Q-37

TransecT: T-6

UniT: EasT Dike

ToTaI disTance: 330 feeT

DirecTion: s 70° 00' w

STarTIng poinT (T-6A): Is jusT souTh of Sand Island and l2' wesT (on
The line) of The cenTer of The road

Ending poinT (0-39) on ouTer edge of caTTail

Q-38 is l52' from T-6A on ecoTone of meadow and caTTail
Q-39 is I78' from 0-38 on ouTer edge of caTTail

TransecT: T-7

UniT: EasT Dike

ToTaI disTance: 584.5 feeT

DirecTion: S 700 00' W

STarTIng poinT (T-7A): is jusT norTh of Sand Island and I9' wesT (on

The line) of The cenTer of The road
Ending poinT (0-43) Is on The ouTer edge of caTTail

66

Table 7 (conTinued) - TransecT T-7 (conTinued)

Q-40 is l62' from T-7A on The ecoTone of meadow and caTTail
Q-4l is 6l' from 0-40 on The ecoTone of caTTail and open waTer
0-42 I5 I74' from Q-4l on The ecoTone of open waTer and caTTail
0-43 is I87.5' from 0-42 on The ouTer edge of caTTail

TransecT: I T—8

UniT: EasT Dike
ToTal disTance: 575.2 feeT
Direction: 5 70° 00' w

STarTIng poinT (T-8A): Is norTh along dike from T-7A and 26' wesT (on
The line) of The cenTer of The road

Ending poinT (0-47): is on The ouTer edge of caTTail (ecoTone of caT-
Tail and The open waTer of EasT Bay)

Q-44 is 88.2' from T-8A on ecoTone of meadow and caTTail

Q-45 ls l02.5' from Q-44 on The ecoTone of caTTail and Open waTer

Q-46 is 225.5' from 0-45 on The ecoTone of open waTer and caTTail

0-47 I5 I59' from Q-46 on The ouTer edge of caTTail

TransecT: T-9
UniT: EasT Dike
ToTaI disTance: 4l4 feeT

Direction: 5 70° 00' w

STarTIng poinT (T-9A): is on dike norTh of T-8A and 44' wesT (on The
line) of The cenTer of The road

Ending poinT (Q-5I): is on The ouTer edge of caTTail

0-48 is ll7' from T-9A on ecoTone of meadow and caTTail

Q-49 Is 32' from 0-48 on ecoTone of caTTail and open waTer

Q-50 ls I53' from Q—49 on ecoTone of Open waTer and caTTail

Q-5l is ll2' from 0-50 on ouTer edge of caTTail

67

Table 7 (conTinued)

TransecT: T-IO

UniT: EasT Dike

ToTal disTance: 276.5 feeT

Direction: 5 70° 00' w

STarTIng poinT (T-IOA): Is norTh of T-9A on dike and 26' wesT (on The
line) of The cenTer of The road

Ending poinT (0-54): is on The ouTer edge Of a caTTail

0-52 is 46.5' from T-IOA on ecoTone Of meadow and caTTail

0-53 Is l37' from Q-52 on ecoTone of caTTail and Open waTer
0-54 is 93' from Q-53 on ouTer edge of caTTail

(From BenneTT eT al., l96l)

68

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IIIIIIIInIiiliili ,
41.3.53. ”#1741 ..

 

VEGETATION SAMPLING INSTRUCTIONS FOR MAPLE RIVER WEST

The sampling program is divided inTo five differenT invenTories,
each having a unique seT of insTrucTions. I Think The reason for This
breakdown will be made self-evidenT upon reading Through each series
of insTrucTions.

AT every sample quadraT The daTa To be gaThered are The same. Re-
cord The densiTy, heighT, and seed producTion for each species, The per-
cenT cover per layer, presence or absence of planTs Too far under waTer
To obTain above lnformaTion, and depTh of waTer. The seed producTion
is To be a subjecTive raTing, pick The appropriaTe caTegory from The
following choices: excellenT, good, fair, poor, or none. Bear in mind

ThaT These raTIngs apply only To The species In quesTion.

DITches:

Measure wiTh a map measurer ToTal diTch dIsTances, also keep a
record of individual diTch dIsTances. Divide The ToTaI and The indi-
vidual diTch dIsTances by 6.6'. This gives The ToTaI linear square
milacre quadraTs in The diTches (I choose To call These quadraT seg-
menTs). Then pick quadraTs aT random. To locaTe These ploTs, counT
up The segmenTs on The Individual diTches unTiI The correcT quadraT
segmenT is reached, Then measure ouT on The map wiTh map measurer and
mark The segmenT. Pick random numbers one ding longer Than necessary,
Then Through an even-odd randomizaTIon choose which side of cenTer The
quadraT lies. Since The diTches are l4' wide and 2 milacre quadraTs

make only I3.2', .8' Is lefT over. Therefore, every oTher pIoT should

69

70

be shoved againsT The bank wiTh Those beTween on The cenTer line. Pick
The sTarT posiTion aT random. Take The average disTance of The "sTalks"
(disTance from channel To poThole; The connecTion channel) and mark off
ThaT disTance on The map of Those poTholes having exTra long channels.
PuT all buT The average sTalk IengTh inTo The diTch survey, place The
marked off sTalk IengTh wiTh The poThole. When measuring diTches, save
all elongaTed sTalks Till lasT, Then include In The diTch dIsTances,
also TreaT as an exTra long sTalk, The diTch IengTh of The oddiTy

called a donuT.

PoTholes:

Number all The poTholes and Then sTraTify Them according To The

following scheme:

STraTum l - Half or more of The waTer area covered wiTh emergenT
vegeTaTion.
STraTum II - Less Than half - buT aT leasT wiTh edges covered wiTh

emergenT vegeTaTion.
STraTum Ill - No vegeTaTion visible from aerial phoTograph.

PoThoIes are To be picked aT random for each sTraTum. The sTarT-
Ing posiTion for sampling a picked poThole is The corner ThaT mosT
nearly fITs The sTipulaTion "Diagonally across from sTalk." Randomly
pick a number beTween I and 6, mulTiply iT by 6.6'. This disTance is
Then To be measured off along The shorT leg of The poThole. Pick an-
oTher number aT random beTween 0 and I9. This disTance is already in
feeT and is To be measured off along The long leg of The poThole from

The sTarT corner. AT The InTersecTion of The lines, perpendicular To

7|

The sides aT The measured disTances, is The firsT pIoT locaTion. The
milacre sample is To be alined wiThin The inTersecTing lines wholly
Towards The diTch and away from The sTaIk corner. This means The firsT
ploT lies in The second quadraT formed by The InTersecTion of The per-
pendiculars. SeparaTe each pIoT by 2 feeT from iTs neighbors and keep
all ploTs along The line perpendicular To The shorT side. Run five
ploTs In This line. The poThole area includes The "sTaIk." When The
poTholes are acTually sampled, The IengTh and widTh of poThole and
IengTh and widTh of The sTalk are To be measured. Also measure The

widTh of The sTalk parallel wiTh The diTch.

Bank Area:

A sTrip l6.5' wide and on each side of all diTches is To be TreaTed
as a separaTe enTiTy. To sample This area, divide The ToTal diTch
IengTh InTo 3.3' (TreaT The same as for diTches). When The l/4 milacre
quadraT segmenTs have been deTermined by diTch over all diTches, ran-
domly pick sample segmenTs. AdjacenT To The diTch and on eiTher side
There is a Tier of 5 l/4 milacre squares. As each random number Is
obTained, Take The nexT row number To deTermine which l/4 milacre will
be sampled. Also look aT The nexT digiT in The random number row To
deTermine which side of The channel To census. PloTs are To be IocaTed
in The same manner as Those In The diTches only measure back from The
bank To The appropriaTe Tier. Do noT Include The linear diTch disT-

ance of The donuT.

72

Mound Area:

 

The mound area Is The nexT l6.5' away from The diTch wiTh The bank
area InbeTween. This Is To be handled exachy The same as The bank

area. Draw new random numbers To deTermine sample areas. Also include

The donuT in The mound sTraTum.

OuTside Area:

 

From The air phoTos separaTe The Timber from The herbaceous areas
and sTraTify The herbaceous area inTo high and low vegeTaTion. Use a
planimeTer and deTermine The area wiThin each porTion of The marsh
(IsolaTed by diTches, diTches and Trees, eTc.) as a separaTe enTITy us-
ing diTch borders as The ouTside limiTs where presenT. Then reproduce
each area onTo a grid paTTern as was ouTlined for The poTholes. Ran-
domly pick milacre quadraTs for all areas, TreaTing Them as a single
enTlTy wiThin each sTraTum (To be marked on The grid paTTerns also) and
Throw ouT all ploTs ThaT would fall wiThin 40 feeT of a diTch or in a
poThole. Randomly pick one I/4 milacre quadraT and sample jusT ThaT
one wiThin each milacre. This ploT will remain The same for all mil-
acres, e.g., The souThwesT l/4. DeTermine The locaTlon of each ploT
by counTing down rows and across columns of square milacres unTil The
correcT one is reached. These dIsTances can Then be used To compuTe
linear lengThs in feeT for pacing purposes. By compuTing The ToTaI
marsh area, subTracTing The Timber, diTch, poThole, bank, and mound
areas, you can deTermine The less imporTanT herbaceous planT area.

The sTraTum areas can Then be deTermined by prOporTions.

73

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74

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 9. A TransiTion from caTTail To meadow In PoTTer's Cove.*
WaTer DensiTy per PresenT
depTh DaTe Species l/4 milacre cover Remarks
l2" 8-I-6I Typha angusTifolia Sample is aT
dead sTems I ecoTone of caT-
Iive sTems 8 Tail & meadow.
Asclepias incarnaTa 3
High waTer has
Leersla oryzoides 35 killed mosT of
Eleocharis s2, I00: The caTTail.
0" 6-I4-62
Typha angusTifolia 4| WaTer lowered.
Polygonum lapaThifoIium 9 CaTTaiI re-
Hibiscus palusTris I8 covered. Bul-
Leersia oryzoides scaT— rush & smarT-
Eleocharis s2, l50 Tered weed Typical
Scirpus validus 8 planTs ThaT fol-
SOnchus arvensTs I low drawdown.
0" 9-8-62
Typha angusTifolia 35 CaTTaiI edge
Polygonum lapaThifoIium 5 exTends 20 fT.
Hibiscus palusTris l5 beyond sTake in-
Leersia oryzoides pres- To meadow.
enT
0" 6-l6—63
Typha angusTifolia 33 CaTTail exTends
20' beyond sTake
Asclepias incarnaTa I2 in meadow buT
GramInae 50 Is scaTTered
and appears To
EEEIDE-éflf ' lack vigor.
0" 9-5—63
Typha angusTifolia 5 STake is on
Asclepias incarnaTa IO boundary be-
Leersia oryzoides I500 Tween caTTail

 

Hibiscus palusTris

 

and meadow.

 

*DaTa from TransecT I QuadraT 6.

(From Pirnie and FosTer,

I964).

 

- Bulrush
- Charo

Meadow
m, _ Cailoil
I Pondweed
E No Vegeiaiion

 
 
  

 

Figure 3. Eric Croc‘in: and Fisnin; Club PoTTer's Cove. Cover "Up
Ci TF1" v£:"}":'diii_iri.

(From Pirnie a“: Fosiur I914)

I

76

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.m+0h Lomcomcoe .mo+ xozu 6003 x036 xom.m Ocm..mz

60600: uOmc.2IO:.m

 

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77

Table II. Creel census daTa, Duck and Fine lakes, I958l

 

ToTal fishing

 

 

Lake Trips Hours CaTch
Duck 26 80 83
Fine l2 30 55

 

 

CaTch by species

 

 

Yellow Blue- Pump- Black Rock Large- Small- Wall- Pike
perch gill kin- crapple bass mouTh mouTh eye
Lake seed bass bass
Duck 24 50 3 2 I 2,749 39 44 398
Fine 4 4| 6 2 .. l,l0l ... 49 34

 

|EsTimaTes are shown To The nearesT Thousand, excepT for large-
mouTh and smallmouTh bass, walleyes, and pike, which are acTual
esTimaTes.

(From Taube, I965.)

78

Table I2. Summary of use

The following Then presenTs The five componenTs enTering InTo my
final esTimaTe of non-hunTing-season use:
Man-hours
(I) Basic use compuTed from posTcard reTurns . . . . . 906,000
(2) EsTimaTed nocTurnal use noT adequaTely sampled . . 300,000
(3) EsTimaTed use by peOple in cars ThaT did noT
STOp on game areas . . . . . . . . . . . . . . . . 200,000
(4) Allowance for cars missed during daylighT counTs . 200,000
(5) EsTimaTed use March 2-April 28 before check began. 25,000
ToTal: March l-SepTember 30, I962 . . . . . . . . . . l,63l,000

Types of Use

An analysis of 2,444 posTcard reTurns indicaTed a wide specTrum of
uses during spring and summer--from fishing To pracTicing musical in-
sTrumenTs and hunTing Tadpole food!

 

Number of PercenT
AcTiviTy respondenTs of ToTaI
Fishing I,29I 53.0
Picnicking 328 l3.5
Berry picking 296 I2.2
Swimming 259 I0.6
Camping 247 I0.l
SighT-seeing 246 I0.I
BoaTing I49 6.l
Mushroom hunTing l27 5.2
Hiking II5 4.7
Loafing, resTing 49 2.0
VisiTing camper friends 22 0.9
Bird-waTching and banding 22 0.9
TargeT shooTIng (gun) l9 0.8
Field Trials I8 0.7
Archery pracTice l5 0.6
WaTer skiing I4 0.6
Dog Training I2 0.5
PhoTography l0 0.4
Miscellaneous l25 5.I

Some respondenTs reporTed more Than one acTiviTy. Therefore, column
ToTals exceed 2,444 responses and I00 percenT.

A decided seasonal variaTIon occurred ThroughouT The spring and
summer. Mushroom hunTing was a principal acTiviTy in early spring and
again in SepTember. Fishing was pOpuIar ThroughouT The enTire sTudy
period. Swimming, camping, and picnicking were popular mosTIy from
July 4 Through Labor Day. In SepTember, dog-Training, TargeT shooTIng,
and relaTed InTeresTs associaTed wiTh The forThcoming hunTing season
increased in imporTanT.

(From Palmer, I963)

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