|Creel census method|
|Array (  => Neuhold, John M.  => Lu, Kuo H. )|
|Publication Number 8|
|Utah. State Department of Fish and Game|
|Array (  => Not Specified )|
|,_ ........ -
;i '1c,tJtJ . 5 : C r e/tJS7
"- - - - .
John M. Neuhold
Kuo H. Lu
_-:-__ PUBLICATION NO. 8 OF THE FEDERAL AID DIVISION OF THE -:-~-:-:--::----:-:-:~T::~--::--:-::JiIiIioi.
UTAH STAT EP AR TMENT
STATE OF UTAH
George Dewey Clyde, Governor
FISH AND GAME COMMISSION
K. E. Bullock
Robert B. Mitchell
Golden G. Sanderson
Dr. Paul G. Stringham
W. Rulon White
UTAH STATE DEPARTMENT OF FI SH AND GAME
J. Perry Egan, Director
/Ie!. ' i 1'1 ).r';9 .z
Figure 2, page 12.
The solid lines represent the pres-
sure and the dotted lines the rate
of success. (Omitted from the
Page 28, line 3 should read:
2 " • •• and Sr equals the root mean
square errors of the mean number of
boat fisherman hours and the mean
rate of fishermen per boat ••• "
Page 29, line 26 should r ead:
286,870 t 82,732 fishermen II • •• C
CREEL CENSUS METHOD
JOHN M. NEUHOLD
KUO H. LU
Publication No. 8
UTAH STATE DEPARTMENT OF FISH AND GAME
Submitted for Publication March 1, 1957
Printed by the Utah State Department of Fish and Game
Salt Lake City, Utah
A contribution of projects F~l~R, and FA~RJ
Federal Aid Division, Utah State Department
of Fish and Game
TABLE OF CONTENTS
List of Figures ........ .
List of T ables ...... .
Introduction __ _ .
Creel Census Design ..
Fisherman Counts _
Calcul ation of pressure
The Interview ____ ..
Calcul ation of n:tte of success
Calcul ation of harvest ____ ............... .
Evaluation of the Method
Literature C ited
. ................ 34
C redi t is given to Dr. W illiam F. Sigler, H ead of the Department
of Wildlife Management, U tah State U niversity, Logan, U tah, who origin ..
ally provided the concept of counting on intervals of the average daily
fishing curve and to W illiam J. McConnell , who fostered this concept and
w as instrumental in the developments o f the m ethod.
Thanks are given to Dr. Rex Hurst 0 !the U. S. U. D epartment of
Applied Statistics for his valuabl e advice and assistance in editing the
LIST OF FIGURES
1. Fishing pressure and rate of success on Deer Creek Reservoir during
2. Mean daily rate of success and pressure on four 1955 creel census
3. A correlation between air temperatures and fishing pressure.
4. Seasonal fishing pressure curve on Fish Lake during the 1955 season.
S. Correlation between mean days fished per season and rate of success.
6. A shore fisherman situation on which an instantaneous count is
7. A shore fisherman situation representing a progressive type count.
8. A biased progressive count situation.
9. A hypothetical lO-day fishing season.
LIST OF TABLES
1. Difference in the mean pressures of shore fishermen on Scofield
Reservoir and boat fishermen on Fish Lake during June and July,
1956, between inclement and non~inclement weather categories.
2. Differences in mean pressures on Scofield, Deer C reek, Strawberry
Reservoirs and Fish Lake during 1955 between weekday and week-
end days and holidays.
3. Relation of number of counts of fishermen to accuracy and precision
of the estimate in which the total number of fisherman hours per
season is 944.
4. The effect of stratifying a sample on the basis of days in the lO-day
hypothetical situation of Figure 9.
5. Fisherman counts from Scofield Reservoir during the 1955 season.
6. Scofield Reservoir 1955 creel census rate of success.
7. Summary of mean rate of success estimates for species by boat and
shore fishermen on Scofield Reservoir during 1955 creel census.
8. Summary of harvest from Scofield Reservoir during the 1955 season.
Creel census in a cold water trout fishery is, perhaps, one of the most
useful tools availabl e in the management of tha t fishery. This statement
is particularly true in situations where the fishery is being maintained, of
necessity, by artificial means, and tcue to a lesser extent when the fishery
is maintained through natural processes.
Such basic information concerning the mortality from fishing in the
fish population as a total fishing pressure, rate of fishing success, and tota l
harvest can be obtained by the application of creel census. From this
information the investigator can derive an assortment of data concerning
the fish population, e.g., (I) the extent of harvest of fish, (2) the size
of the fi sh population, (3) the effect of a given fishing pressure on a fish
population, and (4) the numbers of fish required to replace a mortality
caused by fi shing.
Creel censuses can be accomplished by two methods: (1) observing
the total pressure and harvest for an entire season, or (2 ) estimating
the pressure and harvest by sampling of the total population. Observing
the tota l pressure and harvest is costly as well as time and effort con ...
suming except in some isolated instances. One need not argu e, however,
as to the valid ity of the values obtained by this method. Estimates, on the
other h and, are done with considerable saving in time, money, and effort
but with the subsequent sacrifice of certainty that the total observation
Estimates number many in methods and analysis. They range from
a vol untary fisherman ... questionnaire return to counting and interviewing
fishermen, all with varying degrees of success and reliability. Since an
estimate is obtained from sampling a portion of the whole population,
great variance in the accuracy and precision can be encountered depending
upon the thoroughness of the design and the simplicity of the analysis.
A ccuracy can only be atta ined through careful design of the creel
census and precision through sound application of statistical principles.
The prima ry objective of a creel census in management is the deter ...
mination of the harvest or fishi ng mor tality during a specified period.
Secondarily, the objectives incl ude sllch varied information as the eco ...
nomics of the fishery (a function of the fishing pressure) and further
estimates of the fish population (related, in some extent, to the fishing
As stated previously, two methods exist whereby values concerning
the fi shing pressure and harvest ca n be obtained: ( 1) observation of all
fisherm en and their catches during a specified period of time, and (2)
observation of a portion of the fishing pressure and harvest during a speci ..
fied period with a final expansion to an estimate of the whole.
Observation of the whole provides the mOSt desirable kind of data
since no variance in the totals is encountered. Data of this nature repre ..
sent the t rue values of the population being enumerated . This type of a
creel census, however, is usually im practical in terms of time, money, and
effort necessary for accomplishment.
Observation of a portion ot the whole (the sample) and a final ex ..
pansion to the estimate of the whole can be made only with palpable
reservations. Since the sampl e is based on only a part of the total situation,
allowances must be made for that portion of the universe not sampled.
Thus the error that mayor may not be encountered by expanding the
sample to the whole is taken into consideration and qualifies the final
statement about the universe. The estimate, jf used properly, can give
good and even excellent approximations of the actual population values
with an expenditure of money, time, and effort somewhat less than
what would be necessary were the universe obtained.
The goal of most fishery ma nagers is to conduct as many creel censuses
as limited funds will permitj consequently, the estimate becomes, to them,
even more important. H owever, estimates that require excessive expendi ..
tures gain li ttle over obtaining the actual population va lues. The necessity
arises, then, to provide an est imate that will afford a critically accurate
value at the least possibl e cost.
The object of this paper is to present a method th at can be used
under a va riety of conditions with reasonably accurate results.
CREEL CENSUS DESIGN
C reel census methods have been designed under a number of tech~
niques. Designs range from those that provide substantially accurate esti ...
mates of the mean values to those that are palpably inaccurate. The
primary basis for providing accuracy to the estimates of the mean values
is the consideration of all variables, some of which are cryptically subtle;
e.g., the estimate of the average number of fishermen per day for an
entire season must consider the length of the possible fishing day (where
daylight hours are used as the criterion for the length of the fishing day)
progressively and not as an entity, This becomes obvious when the peak
of the fishing pressure occurs in June, that time of the year with the
longest possibl e day, and the trough of the fishing pressure occurs in
December, that time of the year with the shortest possible fishing day. If an
average value for the length of the day for the season were used, the low
pressure would receive weight equ al to the high pressure with a resulting
under~estimate of the total pressure.
Precision of the estimate in most creel censuses is not even considered,
and yet, without precision the values derived from an estimate are but
guesses. Fishery biologists commonly tend to temper what they call the
precision of their estimate with assumptions, many of which are un ..
qualified; e.g., in a fisherman count along a 20~mile st retch of stream
where an attempt is made to count and contact all the fishermen for the
sample day, the assumption is made that all fishermen are counted and
contacted during the sampl e day or that the number of fishermen missed
is probably insignificant. In most si tuations the number of fishermen missed
is probably insignificant and probably has little bearing on the accuracy
of the estimate of the mean number of fishermen per day. However, if
fishermen are missed, they are probably missed in proportion to the in~
tensity of the fi shing pressure and, consequently, would have a variance
similar to the variance of the fishermen count. The precision of the
mean number of fishermen per day, then, could be and probably is
Fishermen numbers, as many other biological populations not under
laboratory control, are influenced by a number of non~predictable phe~
nomen a as well as some that are predictable. Factors such as weather
and rate of fishing success definitely have an effect on numbers of fisher~
men fishing a given body of water during a season; yet, weather' and
fishing success are not predictable.
Data coll ected from Scofield Reservoi r and Fish Lake during 1956
show a significant difference in mean numbers of fishermen between
counts made during the inclement weather and counts made during non~
inclement weather (T able 1). The counts were made on the basis of
water condition (calm, choppy or whi te caps) and on the weather index
(clear, less than 50% overcast, greater than 50% overcast, and rai ning
or snowing). Andriano fou nd that weather categories, similar to those
mentioned, produced one of the greatest d ifferences in numbers of fi she r~
men on Henry's Lake in Idaho of all the variables examined ,l
T ABLE 1. Differences in the mean pressures o f sh ore fi shermen on Scofield
R eservo ir and boat fishermen on Fish Lake d uring June and July,
1956. be twee n inclem ent and non -inclem en t weather categor ies.
Fish Lake ........ _
Inclem en t
W ea ther
N o n.inclem en t
1 Both values represe n t mean number of hoats per count.
t·va lue l
2 Both values represent mean number of fishermen per COUnt.
3H ypothesis tested is one of equal means (after D ixon and Massey, 195 1, pp. 102 and
103) . Bo th insta nces show a t.value grea te r than would be expected at the 95% confi.
dence leve l, and the hypothesis of equal means is rejected.
Not onl y does the nature of the weather at the particular body of
water u nder surveill ance have a di rect effect on the numbers of fishermen,
but the weather at nearby centers of population shows indicat ions of affect-
ing fishermen nu mbers. D ata from Bear Lake, Uta h ~Idaho, imply that
weather in the cities of Logan and Ogden might have some infl uence
on num bers of fishermen even though the weather at the lake was
opposite the weather at the mu nicipalities.
Additional data from the 1955 Deer C reek Reservoir Creel Census
indicate a significant d ifference in mean numbers of fi shermen between
days following periods of good success and days following periods of poor
success (Fig. 1). The effect appears to be somewhat delayed in that the
the rate of success appears to influence fishermen nu mbers after occur~'
rence rather than during occurrence.
Similarly, the time of day seems to have delayed effect on the daily
fishing pressure. The fishermen numbers, except for the opening hours
of the day, appear to be influenced by the rate of success in the period
preceding, as on Deer C reek Reservoir during the 1955 season (Fig. 2).
IPersonal cor res pondence with Don And riano of the Idaho Department of Fish and
G a me dated August 22, 1956.
'" .3 u.
w .... ..
Since fishermen fish to catch fish this quasi~correlation probably has
Differences in mean pressures between week days and week~end days
and holidays also appear to be significant from creel censuses conducted
in Utah (Table 2). Best and Boles (1956) implied as much when they
sampled all week-end days and holidays of the 1953 Rush C reek and
Castle Lake data .
" I \
Figure 1. Fishing pressure and rate o f success on Deer Cre ek Reservoir during
August, 1955 . The so lid line represents the fi shing pressure and
th e dotted line the rate of success in fi sh per hour. Note that
the fishing pressure tends to lag after the rate of success. The peak
in the rate of success occurred after an application of copper sulfate
for plankton control.
|Array (  => Array ( [state] => Utah [province] => ) )|
|Tue, 05 May 2020 19:04:31 +0000|
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|Content: 7aa6cfffc0ff0583d75e6490ee4bdfe85a3b355e | Abstract: 2191fc0c9e5968161f4a6e37d3212af80adca3a0|