A Method for Estimating

8/13/2019 A Method for Estimating

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A METHOD FOR

ESTIMATING THE STANDING CROPS AND SPECIES COMPOSITIONS

OF RESERVOIRS USING SAMPLE NETTING AND A ROTENONE COVE

SAMPLE ILLUSTRATED WITH SAMPLE NETTING D T FROM BUNDH

B RETH 14 OCTOBER 1969 20 J NU RY 1971.

Prepared by

Philip M FearnsideAmerican Peace Corps VolunteerBundh Baretha Fish FarmDis t Bharatpur Rajasthan)April 11 1971.


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Page

TA B L E O F C O N T E N T S

I . JNTRODUCTION

A.) Need for Estimate. p.1

B.) Summary of the Method for Making the Estimate p .1 -2

II . ) MAiqNG THE ESTIMATE

A.) The Catchabil i ty Correction Factor C .C .F. )

1 . ) Need for a C F . . . . . . . . . . . . . . . . . . . . . . . p 32 . ) Computation of the C . C . F. . . . . . . . p. 33 ) Use of the C . C F. . . . . . . . . . . p 4

B.) The Habitat Correction Factor H.C.F. )

1 . N e e d f o r a n H . C . F . . . . . . . . . . . . . p.42 . ) Definitions of the four habitats (with fig. I). p. 43 . ) Computation of the Mean Depth. . . . . . . . . . . p. 54 . ) Computation of the H. C . F. . . . . . . . . . . . . . . p. 55 . ) Table o f Information on the H a b l t a t s . . . . . . . . p. 56.) Figure II: Area of Water Spread vs . Water

depth for Bundh Baretha . . . . . . . . . . p. 67.) Figure III: Capacity Curve for Bundh Baretha. . ~ 7

C . ) THE NET-WISE BREAKDOWN TABLE

1 . ) Explanation of C .)lumn in Net-wise BreakdownT a b l e p 8

2 .) Sample page from Net-Wise Breakdown Table . . p.9

D. ) THE TABLE OF DATA FROM ALL NETS COMBINED.

1 . ) Explanation of Columns in the Table of Datafrom All Nets Combined

2 . ) Sample Page from Table for Data from All NetsCombined

III.) BUNDH BARETHA: THE RESULTS SO FAR

A.) MATERIALS .AND METHODS

p .10-11

p .13

1 . ) Sample Netting. . . . . . . . . . . . . . . p .142 . ) Rotenone Cove S a m p l e . . . . . . . . . . . . . . . . . . . . p.15

B.) SIZE GROUP SUB-TOTALS AND SPECIES TOTALS SECTIONFROM TABLE OF DATA FROM ALL NETS COMBINED... p .15/19


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Page i i

D.) PIE GRAPHS SHOWING SPECIES COMPOSITION orHYPOTHETICAL SET

. Figure IV for Estimate of Composition of Entire

Hypothetical Catch Based on All Fish in BundhBaretha Sample Netting 14 Nov 69-Jan 2 0 7 1 . . . p .2 l2 . ) Figure V for Estimate of Composition of That

Portion of the Hypothetical Catch Comp:>sed ofFish Weighing Less than 2 kgs. . . . p.21

E.) COMMENTS ON THE BUNDH BARETHA RESULTS... . p.22

IV. LIMITATIONS OF THE METHOD AND SOME POSSIBLE REMEDIES

A.) UNREPRESENTATIVE ROTENONE S A M P L E p.23

B.) UNREPRESENTATIVE SAMPLE N E T I I N G p.23

C . ) LEARNING BIAS IN lHE SAMPLE. NETTING. . . . . . . . . p.24

D.) SMALLNESS OF THE SAMPLE. . p. 24

E. ) EXTREMELY LOW CATCHABILITIES OF SOMESPBCIES ANDSIZE G R O U P S ~ p, 24-25

; VARIATIONS OF CATCHABILITIES WITH THE LUNAR CYCLE 25.

VJGONCL UDING REMARKS p. 2 5-2 6


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A METHOD FOR ESTIMATING THE STANDING CROPS AND SPECIESCOMPOSITIONS OF RESERVOIRS USING SAMPLE NE ITING AND AROTENONE COVE SAMPLE ILLUSTRATED WITH SAMPLE NE ITINGDATA FROM BUNDH BARETHA 14 OCT. 69 - 20 JAN. 71.

I . INTRODlJQTION;

A. t m ~FOR MAKING ESTIMATE;

B.

Determing the species composition of a reseiVoir s flsh populationshould be one of the first orders of business for anyone attempting tose t reservoir management policy. Once an estimate of the speciescomposition of the reseiVoir population has been made comparisonwith the species composition of the commercial catch will quicklyreveal select ive fishing. Selective fishing for major carps can causea reservoir to become taken over by weed-fish. Once select ivefishing has been identified i t can be effectively countered underthe proposed base-rate fishing contract plan 'by raising or loweringthe base-rate percentages charged for the various species . Specieswhich are declining for any reason be i t select ive fishingspawning failure, or whatever c a n be protected by appropriatebase-rate percentage adjustments.

A second way in which the method can be put to immediate usein Rajasthan is in the suggested common carp pilot study. In orderto determine whether introducing common carp in Rajasthan reservoirs

will adversely affect major carp populations, the species composition etc. of one reservoir should be determined before and afterestablishment of a common carp population. This method shouldproduce a useable estimate using simple and inexpensive means;only sample nets and rotenone are required. \

\SUMMARY OF METHOD FOR MAKING ESTIMATE:

The key to making an estimate of the reservoir population basedon sample netting is the relatiG.>nship between the density of the fish

population and t. le number of fish that get caught in the nets . Whenthere are twice as many fish per hectare of water one must assumethat twice as many fish will be caught per one-hundred nets se t . Inorder to find a constant relating the standing crop of each speciesand size of fish with the catch-per-unit-effort information from thesample netting, a comparison must be made between the catch-perunit-effort data from sample netting in a small part of the reservoir(a cove in this case) with the actual population of the cove asdetermined by a rotenone sample. The relationship between thecatch-.per-unit-effort and the pouplation density will be the sameln the cove as in the reservoir as a whole so the constant

. . . . /2


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or catchabillty correction factor 11 C .c .F.) can be used with thesample netting data from the whole reservoir to estimate the populations.

Instead of using a catch-per-unit-effort C U .E.) value for theoove determined directly by sample netting in the cove, a hypotheticalC . U .E. must be constructed based on sample netting from the rest ofthe reservoir. This is made necessary by the fact that Indian carps learnquickly to avoid the gill n e t s introducing a heavy bias from learnlng

under intensive fishing pressure. The sample netting data in the reservoiris collected with a few nets se t over an extended period of time, thusminimizing the bias from learning.

A prediction is first made of what the catch would be i f hypotheticalse t of 100 nets were made. Since different species of fish l ive in differenthabitats - - s o m e living only in shallow and some only in deep water, forexample t h e species composition of the cove will not be the same asfor the reservoir as a whole. f there is a greater percentage of shallowwater in the cove than in the reservoir as a whole, one would expect to

catch more shallow-water fish in 100 nets se t in the cove than in 100nets evenly distributed throughout the reservoir. A prediction of thehypothetical catch for pre-rotenone sample netting in the cove musttherefore be based on data collected separately in the different habitatsand then combined Ln proportions reflecting the habitat composition ofthe cove. The prediction i s made by computing C . U .E. data for fourdifferent habitats in the reservoir as a whole, and then multiplyingeech by a 11 habitat correction factor {H C .F. ) for the oove: thefraction of the total volume of the cove occupied by each habitat .

A similar predicted catch for a hypothetical se t of 100 nets ofeach mesh-size se t evenly distributed throughout the entire reservoirmust be made f estimation of the actual standing crop of each speciesin the reservoir. The jump from the catch of the species per 100 setsto the number of kilograms per hectare of water area is made by multiplying the Catch-per-unit-effort for each habitat by the catchabili tycorrection factor. These values are in turn multiplied by a secondH. C . F. reflecting the percentage of the total volume of water in thereservolr represented by each habitat. Adding the values for the fourhabitats then yields the standing crop of each spec ies . The percentagesrepresented by each species in the total standing crop of fish in the

reservoir is the species composition of the reservoir.


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3

I I . MAKING THE ESTIMATE:

A. THE CATC ii}.BU.ITY CORRECTION FACTOR .(C, C .F.):

1 . NEED FOR A C ,C .Fi

A catchabi l i ty correct ion factor C ,C,,F) is needed to obtain

a true picture of the fish populations from catch-per-uni ' effort databy counteracting the bias introduced by the select ivi ty of the sampling gearBecause of the differences in habits , body shape , the presence ofabsence of easi ly-entangled sp ines , e tc . each s ize group of each speciesof fish has a different succept ibi l i ty to being caught in each of thedifferent mesh-s izes of sample net . Mystus seengha l la , with i tsserrated dorsar and pectoral sp ines , i s easi ly ensnared in nets ofalmost any mesh s ize- -very large ones are sometimes cauq'-t in the oneinch bar mesh riet. Channa marul ius , on the other hand, has no spinesand has a tapering body-shape that makes i t unlikely to be caught in

gi l l -ne ts . The percentage of C . marulius in the sample catch might wellbe much l e s s than i ts actual percentage of the fish population in thereservoir. A correction factor for the catchabi l i ty of each species musttherefore be obtained to make the sampling resul ts useful in estimatingthe spec ies composition of the reservoir. This is obtained by comparingthe sum of the catches-pe r-uni t -effor t in a l l nets ( ~ C U .E . ) with theactual population as determined from a complete kilf with rotenone.

2. COMPUTATION OF THE C .C .F:

The catchabi l i ty correction factor is computed from thefollowing formula:

AC .C .F. =

p

where: 11 C . C. F" i s the catchabi l i ty correction factor for a given spec ies ands ize group,

11 A 11 is the actual standing crop of that species and s ize group inkilograms per hectare as determined from a rotenone cove sample, and

11 P 11 is the predicted catch-per-uni t -effor t for the cove: This

represents the number of kilograms of each spec ies and s ize group thatwould be caught i f 100 se t s of each mesh-s ize of net were made in thecove with the nets proportionately dtstribufed to the habitats representedin the cove . In other words, this is too sum of the values for the fourhabi ta t s , each of which is the sum of the catches-per-uni t -effor t foral l mesh-sizes of net t imes the habitat correction factor for the cove:

P = >: . . ~ AH

. ; ~ C U E x H C F A \f

)(cove)

Here11

P11

ls the predicted catch-per-uni t -effor t for the cove,11 J 11 is the summation of the values for the four habi ta ts (value forshal low-water hab i t a t+ value for surface deep hab i t a t+ ) ,


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A--if 11 is the summation of the -values for a l l the nets (value forone-inch bar mesh net +va lue for 1-1/2 inch bar mesh net + . . )

C. U .E. 11 is the catch-per-uni t -effor t : the catch per 100 se t sof all nets for the given species and s ize group,

H . C . ~ b ~ Athe habitat correction factor f o r t h ~c o v e - - theportion of the l:otar water volume of the cove occupied by each of ttefour habi ta ts

3 . USE OF THE C .C .F:

The standing crops can be computed using the C. C. F. usingthe formula:

-_Standing crop C .C .F. X AN P..L. ;.

where : 11 Standing crop is the number o f kilograms per hectare of a givenspecies and s ize group in the habitat ln question,

nc .c .F. II is the catchablli ty correction factor for the givenspec ies and s ize group, and

11 P is the ptedicted C . U. E. described above.

B THE HABITAT CORRECTION FACTOR (H. C. F,) :

1 . NEED FOR AN H C I :

Dlfferent species of fish are specialized fo l ive in specifichabi ta ts of reservoir. To gain an idea of the fish populations of the entirereservoir from sample netting, nets must be se t in all of the habitats .Since the nets are not evenly distributed throughout the reservoir, thefishing effort will vary from habitat to habl ta t . Species character is t lcal lyinha_biting the habi ta ts receiving the greatest fishing pressure will beoverrepresented Ln the sample catch. To counter this bias , catch -perunit-effort (C. U. E.) figures must be computed separately for each ofthe four habi ta t s , then multiplied by an habitat correction factor reflectingthe fraction of the reservoir occupied by each habitat, and finallyrecombined by adding together the corrected values for the C . U. E in thefour habi ta ts .

2. DEFINITIONS OF THE FOUR HABITATS:

For the purposes of sample netting, the reservoir has beenarbitrarily divided into four habitats which are defined as follows:

a) Shallow water habitat: This is defined as all water less thanei9ht feet ln depth.

b) Surface deeo habitat: This is defined as the top eight feet ofal l areas of the reservoir more than eight feet in depth.

c) Bottom deep habitat; This is defined as a l l water more thaneight feet from the surface and l ess than eight feet from the bottom.

d) Midwater deep habitat: This is defined as all water more thaneight feet from the surface and more than eight feet from the bottom. A 1 ~

.. The four habitats are i l lustrated below in figure 1 . - - __ w - -vf\..- .... -. ... . - ------- - .. - --- -- ----- - - - --- .. --------- ---------- --.- ___ ../ . . - . .?t cl Ft

, _ - _ / ;1

- : . - , S J Rfl\-ct. .DEE.-? ; f -' I


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3 COMPUTATION OF THE MEAN DEPTH;

Because the depth of the reservoir fluctuates a great dealduring the period of sample netting the fraction of the water volumeoccupied by each habitat does not remain constant . Ideal ly, separate

H .C .F. values should be~ o m p u t e

for each day, but since the amountof work involved in this task would be prohibitive a mean value will beused i n computing the habitat correction factors . This is obtained bysumming the lake level figures for al l the days on which nets were se tand dividing by the number of days . The average lake level for 56 dayson which nets were se t in Bundh Baretha from 14 October 1969 to 20January 1971 was 21.2 feet .

4 . COMPUTATION OF THE H.C.F. ;

The proportions of the total water volume of the reservoirrepresented by each of the four habitats are computed as shown below.Values for the areas arx J water volume of the reservoir a t various levelsare taken from figures I and II .

a . Surface deeQ: Area a t 13,.2 feet times a feet times 0.04356 mcf/acre- f t . : 820 acres X 8 f t X 0.04356 mcf/acre-foot = 2a6 million cubic feet .

'

b . Shallow Volume a t 21.2 feet minus. the volume a t 13.2 feet minusthe surface deep volume:

875 mcf - 475 mcf - 2a6 mcf = 114 mcfc , Bottom deep; The surface deep volume minus the overlap volume.

The overlap volume equals the difference between the area a t 13 .2 feet andthe area a t 5.2 feet t imes a feet times 0.04356 mcf/acre-f t . divided by 2:

2 86 mcf - (820 acres - 270 acres X 8 ft X 0. 0435 6 mcf/acre-f t =190

d . Midwater deeg; Volume a t 13 .2 ft. minus the bottom deep volume:475 m c f - 190 mcf = 285 mcf.

5 TABLE OF INFORMATION ON HABITATS

Habitat area in volume in of tbtal H .C .F.acres mcf water volume

Shallow 800 114 13.0 0.130Midwater deep 820 2a5 32.5 0.326

Surface deep 820 286 32.7 0.327Bottom deep 820 190 21.7 0.217

Total 1620 875 100.00 1. 000

*values a t lake level of 21.2 ft (672 .2 ft above MSL)


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6 . ) FIGURE I I : AREA OF WATER SPHEAD VERSUS WATER DEPTH FOR BIDillH BARETHA

2500 -' {/ 2 9 2 0

f

2560*

/2420**

I .

2000At 21.2 f t sample ~ 0n e t t i n g ave rage depth f rom Oct .

169 to - .. ,

J a n . 1 71 - a r e a . __ .i s 1620 a c r e s o -500

1400*I .

1000 - A r e a a.t5 2 f ' tl s 270 a c r e ~

500 , . 480*

, '

0

0 10depth of wate r

2

a t dam i n30

f ' ee t40

651 661 671 681 691e l e v a t i o n above :ivLS S. i n f ' ee t

* f i g u r e s t aken f rom a monument on the dam** j f ' igureK f'rom F i s h e r i e s Pro a c t Re o r t f 'or Bundh Baret ha,

i s s u e d by: Of'f'ice of' Dep. Dir. F i s h e r i e s Animal Hus. D e p t . ,J a i p u r , Dated: 1967-8.


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7. ) FIGURE I I I : CAPACITY CURVE FOR BUNDH BARETHAVOLUME OF WATER VERSUS WATER DEPTH)

\ ..

l8 T

lI

I

I1500

1200 ..

I

l

ll/

II r 1096*At 21.2-f ' t t h e mean 11 depth fo r sample j

900 I_ ne t t i ng days,. . - . . _ ~_I Oct. '69 J a n . 7 1 - ~ 1

I the volume i s875 mcf. 1 731

I/600 c j

At 13.2 f t Ival ume ;> /i s 475 m c f / /

- / ,313*300

I //I /

0 ~ _ ._ _ _ _ _ _ _ _ . _ _____ J0 10 2

.

\_I 30depth of water a t dam in f e e t

651 661 671 681

..l

_____ }

40

691


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C , l HE N E T ~ 1 / I S EBREAKDOvvN TABLE:

1) EXPlANATION OF COLUMNS IN T H ~NET-WISE BREAKDOWN TABLE:

COLUMN - -NET: The bar mesh s i ze of the sample ne t .

COLUMN R --HABITAT: The four habttats into which the reservoir hasbeen divided are defined on page 4 in the sec t ion on the HabitatCorrect ion Factor.

COLUMN T --NUMBER OF TIMES NET SET: This is the sum of thefigures from the effort column in the raw data proforma describedin the paper Procedure and Need for Col lec t ion of Sample Nett ing

Data a t Bundh Baretha Jan . 2 8 1 1971}, page 7.

COLUMN U --SIZE GROUP: Since the C . C . F . s for different s izegroups are different , a s i ze -wise breakdown is necessary to get at rue picture of the re servoir populat idn The s ize groupings of l e s sthan 1 kg, 1-1 .5 kgs , 1 . 5-2 kqs , arr l 2-5 kgs 1 and more than5 kgs were chosen arbitrarily for convenience in co:nputlng A-Tvalues l a t e r on. The smaller the range of weights l n each catego.ry,the more accura te the predict ions wil l be. Only 5 s ize groupcategor ies were made because of the prohibi t ive amount of workinvolved in fur thers ubdi vision into smaller categor ies .

COLUMN V --NUMBER OF FISH CAUGHT: This is the number ofindividual f ish actual ly caught in the sample nett ing. This informationi s useful n judging the rel iabil i ty of thG f igures, and pro;ides afirm t ie with real i ty throughout l e s t one forget the pit i ful ly smallnumber of observations on which the whole es t imate is based .

COLUMN W K S of FISH CAUGHT: The number of kilograms offish fal l ing into the given category that were actua l ly caught inthe sample nett ing.

COLUMN X - - C U .E . : The catch-per-uni t -effor t is the numberof kilograms of f i sh caught per 100 se t s of the specif ied net . Thisis obtained y dividing the value in column W (kg of fish caught}by the value in column T (number o f times net set} and mult iplyingby 100 0

A sample page from the net -wise breakdown table fellows showingfigures for Labeo calbasu caught in the 2 and 2-1 /2 nets . Thefull table i s 38 pages in length and i s thus too bulky to be includedhere .


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NET-WISE BREAK O'Jl'.T TABLE

2

Il e s sthan1 kg

4 '?..7 2?, .5 I

l1 - 1 . 5

--------,

12 .0 kg 2 2 . 1 17 .5

,_.I

i - . 5 ~ - ~ ? ~ . - - - - - ~ - - - - - - - - - -

kg- - - - - ~ ~ - - ~ ~ - - - - - - - - - -2-5kg

~ - - - - - - r - - - - - ~ - - - - ~ - - - - - - - - -morethan _ J i g _ - - - - - t - - - - - - - -Hab.subt o t a l

l e s sthan1 kg

6

3

4 . 8 40 .0

? .o ..._2,8_ _ :_ c l - 1 . 5

- 'Ek'- ' :g'=-=-+----4----- 1.5-? .

7 0- ~ ~ : g , _ - - - - - - - 1 - - -..- . ,_5

_k..:::;g:.. .--+---t----

t - j ~ h - o ~ ~ ~ : ; _ t - - - - + - - - - - ---Hab. t--sub- L

.... t o _ t _ a _ l - - 3 - - - - , . . = - ~ ~ - - - ~ 8 ~ - - -l e s sthan 13 o 8 51 51 kg ---. T: l . S 7 7 .4 38.8

- ~ g _ = : : t t..-1.5- ?.

,_ lF.K. - - -+- - - - - - I f - - - -+- - - - - - -

1 9 . o - = ~ = g - s _ - - _ 1-?__B_-+-_14 _ _ 7 _morethan

~ . s k g : ; . . . . , - + - - - - + - - - - + - - - - - Hab.sub .t o t a l

l e s sthan

21

3

?.0.0 105.0

? . 5 17 .8.....:l:::::...... .ko :.l::g;>.....f---+----+------

5 6.15 48 .1- 1 . 5

14. ( kg~ . ~ o r t - - - - - - - - 1 - - - - kg I --+---- -----I2 :0.5 kg

- - - - - - - - - - + - - - - - + - - - - 1

2-t

Kg off i shcaught

C .U. -

_ _ -- - - - - - - + - - - -

5 5 . 9 49 .0 - - - - - - - - t - - - - + - - - - -

I l ? . o 1 1 . 5 12 .5

6 .0

1

- - - - - + - - - - - - - + - - - - -

- - - - - - - - - ~ .

7 8 .3 69.0---- --- r - - - - - + - - - -

________ ~ : : 2-5 41 .7

- - - - - - ~ - - - - - - -

3 ~ . 0 8 3 ~

I 0 ,..,I i :1t

5 7 .5 1 24 .9.........._.__ - - - - - -+- - - - - -

2 . 7 13 .4

r---g--+----1-3-.-4+-6-6-.

20.125 3.T .

2

4 . 9 ?.4.4

?. .0 10 .0....... --- - + - - - - - + - - - - 1

17 ?.3.0 114 .- - - - - - - - - + - - - - -

1 0 . 9 5 .61f t

3 3 . 5 2 2 . 5t-

9 .45.925 1 1 . 5II -----+------+-----

1


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D . THE TABLE OF DATA FROM ALL NETS COMBINED:

1 EXPlANATION OF COLUMNS IN .THE TABLE OF DATA FROMALL NETS COMBINED :

COLUMN A - - HABITAT: The four habitats of the reservoir aredefined on page four of this paper in the section on the habitatcorrection factor.

COLUMN B - - H .C .F. : The habitat correction factor is derivedin a separate section on pages 4-7 o .this paper.

COLUMN C - -S IZE GROUP: This is the same as column U of thenet-wise breakdown table. An additional category has beenadded in the size-group sub- tota ls section for the total figuresfor fish weighing l e s s than 2 kgs. Because of the low catchabil i t ies o the larger fish n gUl nets , the estimate of thatportion of the population composed o individuals weighing l e s sthan 2 kgs is l ikely to be more accurate than the estimate forthe population a s a whole from the species totals figures. f thesample of larger individuals proves to be too small for an accurateest imate . some other method wlll have to be used for that sectionof the population.

COLUMN D - - N O . OF FISH CAUGHT: This is the sum of the_figures entered for the specified category in column V no. offish caught) o the net-wise breakdown table.


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The habitat sub- to ta ls represent the kgs of fish of each speciesthat would be caught in the given habitat i 100 se t s of a l l netswere made 1n the whole reservoir evenly distr ibuted. This isobtained by adding the s i ze group 1gures for the habitat inquestion

COLUMN G NO. OF FISH CAUGHT: This is the sum of theentries for the specif ied category in column D.

COLUMN H C . C . F . : The derivation oc the catchabil i ty correction factor is described in a separate section on page 3 of thispaper Additional information from a rotenone cove sample wil lbe needed to obtain values for this correct ion factor.

COLUMN I ~ C .U E X H .C . F . : This iS the sum of the catchp e r - u n i t - e f f o r t ~ l 1 o ra l l nets times the habitat correct ion factor.The values entered here are the sum of the appropriate ent r ies incolumn F.

The s i ze group subtotals represent the weight of fish in each s i zegroup that would be caught i the evenly distributed hypotheticalse t of 100 nets of each kind were made in the reservoir. This isobtained by :1dding the appropriate s i ze group entries in column F.

The species total represents the number of kgs of the species thatwould be caught i the evenly distr ibuted se t were made. This isthe sum ~ f the five s ize group sub- tota ls .

COLUMN J Z:c U E X H . C . F. X C . C . F . : This is the summation of the ~ l c h - p e r - u n i t - e f f o r t sfrom a l l nets times the habitatcorrect ion factor times the catchabil i ty correct ion factor. Thesize-group sub- to ta ls represent the calculated standing crop in k g /hectare of each s ize group of each species in the reservoir as awhole. The species total row represents the standing crop of eachspecies in kg/H.A. in the reservoir a s a whole . The figures inthe s ize group sub- to ta ls rows of column J are computed bymultiplying the corresponding figure in the s ize group sub- to ta lsrows of column I by the C .C . F. (column H). The species totalis the sum of the size group subtotals

COLUMN K o f ~ C . U .E . X H . C . F. : This is the percentageof the sum of the catch-per- tn i t -effor ts for a l l nets times thehabitat correct ion fc)ctor. The size-group sub- to ta ls represent thepercentaqe of the catch of fish i.. 1. the specif ied s ize group thatwould be repn 'sented by the given species i a hypothetical setof 100 nets of each mesh s ize were made with the nets evenlydistr ibuted throughout the reservoir. They are computed bydividing the corresponding s ize group sub- to ta l in column I

~ c . u . E .X H . C . F. ) by the size-group sub- to ta l in the a l l~ i e stotals sec t ion of the table, and multiplying by 100 .

The species total figures for column K indicate the percentage ofthe total hypothetical catch represented by the spec ies . Note,hi i d b di idi h i l fi f l I


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12

by the grand total figure for column I ( SZ C . U .E . X H .C .F. ) andanmultiplying by 100% not by adding the s i ze group sub- to ta ls

of column K.

COLUMN - - O F ~C . U . E . X H C F X C C F : This is thepercentage of the suf Hha t ion of the catch-per-uni t -e ffor t s for a l lnets t imes the habitat correct ion factor times the ca tchabil i tycorrect ion factor. The s ize group sub- to ta ls in this columnrepresent the percentage of the total s tanding crop of each spec ie srepresented by each s i ze group i . e . the percentage of the totalbiomass of cat la in the reservoir composed of individuals weighing

l e s s than 1 kg. 3tc. The values for the s ize group subto ta ls arecomputed by dividing the corresponding s i ze group subtotals forthe species in question in column J by the species total in columnJ and multiplying by 100%.

The spec ie s totals represent the percentage of the total standingcrop of f ish in the reservoir represented by each spec ies . Thisis computed by dividing the species total in column J by the al lspecies grand total in column J and multiplying by 100 .

A sample page from the table for data from a l l nets combined

showing the figures for L. calbasu has been at tached. Becausethe full table contains 9 pages i t is too bulky to be includedhere. The s i ze group sub- to ta ls and species totals sec t ionshowever have been a t tached as pages .


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z M D D L J u D H L l ' t L " l l v l " l ' .LL u .

H a b ~ C FSize N o. of d:CTTE -:.CUEi ta1 Gro11J f i sh Jan an x

caugh1 H ~ F

SizeGroup

D..

ffi~

[ ' -~ C\ '0

C'0< .0co

p..~~~

~ [ ' -0 r-l

tl0 0p:)

1 . 5 ~

kf2 5kgmorethan5 kgHab.sub-t o t a l

l e s sthan1 kg

< 1 1 . 5kgl . S 2

kg2 5kgmorethan5 kgHabsub-t o t a l

l e s sthan1 kg1 .. 1 .5kg1.5--::>kg

? . 5kg- morethan5 kgHab.sub-t o t a l

l e ssthan1 kg1 1 .5

_kg1.5 ?.

kg2 5kg .

11

23

18

6

6

53

8

10

2

more -chan5 kg

l

164.1 53.5

84.2 ?.7-w5

119.6 39.0

50.3 16.5

68.5 ~ = . 4

3 2 ~ . 6105 ~

31 .6 6 . 9

81.9 17 .7

?.0.7 4.51

No of -CCF ~ U i ~ T w .f i sh an x:an xc a u ~ h t HCF { ~ C F

CCF......

% o_f L of~ T T E p;CUE

an x an xHCF HCFX X

HCF CCF

-

t i lH

~I

0

~t i lClIJjI

~t 1t i l


17/29

14

III . BUNDH BARETHA : THE RESULTS SO FAR; .A. MAtERIALS AND METHODS USED FOR COLLECTION OF BUNDH BARETHA DATA:.

1 SAMPLE NETTING:

a) 8 AMPLE GEAR: 1\;set of 12 sinking gill nets of 8 different mesh s lzes wasus.ed in collecting the sample netting data. The nets belonging to the American Peace

Corps. Specifications are given below:

BarMeshSize (in.)

1

1-1/2

2

2-1/2

3

3-1/2

4

5

Bar Stretch Stretch TwineMesh Mesh Mesh SizeSize Size (in,) Size. (American(em.) (em.) N orne nclat ure)

2 .5 2 5.1 104

3 .8 3 7 . 6 104

5.1 4 10.2 104

6.4 5 12.7 104

7 .6 6 15.2 104

8.9 7 17.8 139

10.2 8 20.3 139

12.7 10 25.4 208

Length of nets: 60 ft. (18/29 me'ters)Depth of nets : 8 ft. (245 em.)Distance between t ies : 3 6 em ..

Number ofMesh as pert i e .

16

10

8

6

5

4

4

3

Floats : 125 hard p l a s t i c ~Length: 5 (12, 7 em.)Thickness 1-1/4 (3 .2 cm.) ,Hole s i z e 9/32 (0.7 em.)

Leads : 16 ( oz . or 2 8 grams)Lead and float l ines : 1 /4 braided polyethylene ropeFloat placement: attached v ry 6th t ie .Lead placement : attached every 2nd t ie .Manufacrurer of nets: Nylon net C o. , 7 Vance Ave. , Memphis

Tenn. U.s .A.

b) OTHER EQUIPMENT USED IN SAMPLE NETTING: Twelve-foot tin and woodrowboats belonging to the-Rajasthan Fisheries Department were used during mostof the study. Towards the end of the study a nin-foot teak plywood boat belongingto the American Peace Corps was obtained. This was used with a 5 horsepowerJohnson outboard motor which had t e e n given to the Fisheries Department byU .N . I . C .E .F.

Data was collected using a steel measuring tape a standard fish measuringboard and two kitc.asn-type spring balances., one with 50 gram calibrat ions andone with 5 gram calibrations.

c) SAMPLING PROCEDURE: The procedure used for sett ing the nets makingthe observations and recording the information is described in a separate paper:PROCEDURE AND NEED FOR COLLECTION OF SAMPLE NETTING DATA AT BUNDHBARETHA J 1971


18/29

2) ROTENONE COVE SAMPLE:

a) ~ U I P M N TNEEDED: 50 kgs of 5% act ive ingredient rotenone(derris rootpower), and block nets (to be improvised from commercial- type drag nets orchaundis) a re needed. The Department has offered to make rupee payment forrotenone and the American Peace Corps is to arrange the purchase from the U.s .A.Rotenone is not available in India.

b) PROCEDURE TO BE USED: The procedure to be used in applying the rotenone

and collecting the data i s described in a separate paper: PROPOSAL FOR A ROTENONECOVE SAMPLE IN BUNDH BAAETHA, Sept 29, 1970.

B. SIZE-GROUP SUB-TOTALS AND SPECIES TOTAL SECTIONS FROM TABLE OF DI AFROM ALL NETS COMBINED FOR BUNDH BAAETHA SAMPLE NETI'ING,l4 Nov. '6920 Jan. 1971:

QatJ,a catl:l

L, [Ohita

C , mriqala

Size No. of CCF ~ C U EX S : CUE---% of % o fGroup an an ' nCUE ~ C U Eish

caught H C F HCF > 1 X HCF an X CCF

CCFc G H I I

l essthan 3 0.5331 kg _____ ---------- ----------- ---------- -- ..1 .5-2kg-z-=r

1 3.14 ~ ~

K L

0.16

1.15

kg 11 29.15 5.45SpecieS _____ --------------------------- --- ------------

Total 15 32.823 2.11ress ___ - --- - -------------

------------

- than2 kg 4 3.673 0.445

l e s s5.3 1.57han

1 kg.l 1 . 5

kg.1,;5-2

----------------------------------------------

9 20.87 9

kg 16 51.1 18.7 ~ ~

--

- - - - - - - - - ---- 2 kg 17 62.24 11.6specTes _________ Total 53 139.51 9 .0L-ess------------------------than 36 77.27 9.252 kg

Lessthan 9 4.2 34 ~ . 2 6

. . . : .1-=k.=. .ogL. : . ' - - - - - - - - - - - - - - ----------------------1 - 1 . 5kg 9 15.87 7_. 5_ - -r : ~ . : . 2____

kgs 14 66 5 32


19/29

L calbasu

L f imbrtatus

L bata

L .gonius

2 5kgs 6SpeciesTotal 28

Lessthan 222 kg

Lessthan 43

_ ; : 1 ; _ k : : . . : . ; g : ~ . . = 1 1 .5kgs 3 81.5 2kgs 122.:. 5

Kgs 6

6.72 1.25

42.484 ~ . 7 4 . . . . .

35.764 4.3

41.5 12.3

79.8 35.5

49.74 18.1

22.4 4.2S.r)eciesTotal 99

;

Lessthan

2 kg 93

Lessthan

1_ ~ S L _ ~ L1 1 .5kgs 3i . s : . : 2 kgs 22 5kgs 1

SpeciesTotal 41

lessthan2 kgs 40

lessthan 116~ kgSpeciesTotal 116

Lessthan 1162 kgs

lessthan1 kg 221 1.5kgs 3

Species

193.44 12.5

171.04 20.5

12.754 3 .8.

4.44 1.97

3.67 1.34

1.3 0.24

22 .164 1 .43

20.864 2.5

50.34 15.9

50.34 3.25

50.34 6.05

- - - - - - - - -

14.7 4.2

4.53 2.01

T ~ o ~ ~ ~ l ~ ~ ~ 5_____________ ~ 8 ~ ~ 7__________ .21

Lessthan 252 kgs

18.7 2.25


20/29

B. sarana

17

Size No o f CCFGroup fish

caught

Lessthan 1111 kg

1 - 1 . 5kgs 6

Species

~ U ~ U E o f o fan an S::_CUE Fn CUEX C X HCF ern X HCF

HC F X C _ . , C = F - _ . . ; ; . ; ; X H ~ C = F : ; : . _ _ . ; ; ; . ; ;

36.12 1 0 . 8

16 .0 7.15

Total 117 52.12 3 .37Less ~ ~ ~ ~ ~ ~

than2 kg 117 52.12 6.3

- - - - - - - - - - - - - - - - - -- - - - - - . . -C . reba

Catla X rohuhybrid

Lessthan 125 23.82

L s ~ SpeciesTotal 125Leissthan 1252 kg

23.82

23.82

Lessthan 1 0.591 kg

7.1

1. 69

2 . 86

0 .175

SpeciesTotal 1

Less0.59 _________ 0 ~ 0 ~ 3 ~ 8 ~

than 1 0.59 0.0712 kgs

- - - - - - - - - - - - - - - - - - - - - - -W . a t tu

M .Seenghalla

Lessthan 3 0 . 8 7 0.25

~ ~ ~1.5-2

kgs 1 ____ - - ~ - - - - ~ - - - - - - - - - - - - - - - - - 3 ~ : . . . .:::g-------

Kgs 3 17 .6 3 . 3

Morethan 5 44.65 25 .0

5 kg _sspeciesTotal 12 72.457 4 .67Lessthan 4 10.64 7 2 .02 kgs

- - - - - - - - -Less 42than 1 kg.

l - 1 . 5


21/29

M seenghallacontd

M . annatus

Gaaa ta

M.cavass ius

-

18

Size No . o f CCFGroup f ish

caught

c G2 5

kgs 49Morethan5 kgs 6SpeciesTotal 166Lessthan

2 kgs 111Lessthan 881 kgSpeciesTotal 88Lessthan2 kgs 88

Lessthan1 kg 2SpeciesTotal 2Lessthan2 kgs 2

Lessthan

1kg 12

SpeciesTotal 12

Lessthan2 kgz 12

- - -Lessthan 1231 kgSp3ciesTotal

123Lessthan2 kgs 123

H

n U E~ C U EX an

HCF XHCF

XCCF

I I

379.1

82 .6

724 .14

262.44

30.05

33.05

33.05

2.05

2 . 0 5

2.05

2.491

2 ..191

2.491

12.986

12.986

12.986

:>f ~ o f2

- C U E . CUEan X an X

HCF HCFX

CCF

K L

71.0

46 .2

46 .6

31 .5

9 . 8

2.14

4 . 0

0 . 61

0.132

0 . 2 4 6

0.74

0.161

0.3

- -3 . 86

0 .835

1 .56

-


22/29

N , notpptreous

Size No.ofGroup f i sh

caught

C GLessthan

\ 1 kg 84SpeciesTotal 84Less

than2 kgs 84

19

CCF ~ U Ean

X

HCF

H I

51.75

51.75

51.75

~ U E o f o fan ~ C U E ~r.uE

x n arrX XH a ' HCF HCF

X XCCF CCF

J K L

15.3

3.35

6.2

LessN Qhltala than

1 kg 3 1.344 0.4022-5kgs 4 17.44 3.26Morethan5 kgs 7 50.9 28.831 peciesTotal 14 69.684 4.5Lessthan2 kgs 3 1.344 0.162

- -- -- -- - - - - -- -- - - - - - - - - -- -- - - -- -Lessthan1 kg 833 333.54

ALL SPECIES TOTALS 1-1 .5kgs 100 224 . 66

1.5-2kgs 7 272.862-5kgs 97 535 51Morethan5 kgs 18 l77 66GrandTotal 1121 1544.23Lessthan

2 kgs 975 831.06- -- -- - - -- -- - - - - -- -- -- -- - - -- --


23/29

.

~ 0

C 1 SfEClES COMfOSITION OF A H Y P O r ~ E T I C A L S E TOF 100 NETS OF EACH MESHSIZE EVENLY DISTRIBUTED THROUGHOUT THE RESERVOIR (% of iU:l CUE X HCFl

FOR ALL FISH FOR FISH VVEIGHING LESSTHAN 2 Kgs

No of of No of offish on which CUE fish 0n a n CUEes t imate an

Xwhich X

-is based HCF est imate HCFis based

MAJOR QAR:fS&Cat la Catra 16 2 11 4 0 45L rohita 53 9 0 3S 9 25C mrlgala 28 2 74 22 4 3L calbasu 99 12 5 93 20 5L fimbriatus 41 1. 13 40 2 5

total major 236 27 78 195 37 0

MINOR CARfS:

L bata 110 3 25 116 6 05- L gonius 25 1 21 25 2 25

B. sarana 117 3 37 117 6 3C reba 12 5 1 69 125 2 85cat la X rohuhybrid 0 04 1 0 07

total minor 384 9 55 384 17 53

ffiEDATORS:

W at tu 12 4 57 4 2 0M seenghal la 116 4 6 6 111 31 5M armatus 88 2 14 88 4 0Gagata 2 0 13 2 0 25

totaYpredators 218 53 0 5L1 205 37 75

O T H ~~ ; e E Q I E S ;

M Cavass ius 12 0 16 12 0 30 Pabda 123 0 84 123 1 56N notopterous 8 :1 3 35 84 G.2N chi tala 14 4 5 3 0 16

total other 233 8 85 222 8 22


24/29

D. SPECIES 'COMPOSITION OF A HYPOTHETICAL SET OF 100 NETS OF EA.CH :MESH SIZE= E ~ V E = N : : . : L : : . : : Y : : . - : D : I . : : . S r ; ; . ; : r R I : ; : . : B ; . ; ; U T . : . : : E D : ; . . . . . ; T H R ; ; . ; : ; ; ; , ; ; . ; ; . O . = . U G ; ; . ; : H ; ; . ; O : : . . : ; U ; . ; ; T ~ T I ;ZlCUE X HCF):

1 . ) FIGURE IV: GRAPH SHOWING ESTIMATE OF COMPOSITION OF ENTIRE HYPOTHETICALCATCH BASED ON ALL FISH IN BUNDH BARET.Hl SAMPLE NETTING 14 Nov. 196120 Jan. 1971:

PREDATORS

2.) FIGURE V: GRAPH SHOWING ESTIMATE OF COMPOSTTION OF TH.I.T PORTION OF~ H Y P O T H E T I C LCATCH COMPOSED OF FISH WEIGHING LESS THAN ~ f KGS,

BA.SED ON ONLY THOSE FISH IN BUNDH BARETHA SAMPLE NETTDIG WEINGINGLESS THAN TW KGS. 11 Nov. 1969 - - 20 Jan. 1971:

. 7 75

..

:;r .

Note: These data do B 1 r ep resen t an es t imate of the s p ~ c i e scompositionof the rese:flvoir f i s h popula t ions . The data have not been oorrec ted .

fo r the varyingc t c h b i l i ~ e s

of thed i f f e r e n ~

species and smzegroups i n the sampling gear. This w i l l be ~ o n ea f t e r c a t c h a b i l i t ycor rec t ion fac to r s C.C.F. s ) have 'l reen computed from rotenone covesample data .


25/29

22

E. COMMENTS ON THE BUNDH B RETH RESULTS:

The study LsI of course not as yet complete and the ultimate goal ofa population estimate of the reser;oir will have to await the results of theplanned rotenone cove sample . The present data has certain weaknesses whichare discussed along with possit ive remedies in the section entitlecj Limitationsof the Method and Some P Jss ible Remedies on page 22. The most obviouslimitation of the present data i s the conspicuous absence of large catla androhu from the sample catch. A separate presentation of the data for only

that portion of the catch composed of individuals weighing l e s s than two kgs. has therefore been made to give a more relat ive picture of a t l eas t part

of the population. Here the predators are not quite so over-represented asthey are in the figures for the ontlre catch. The largo fraction attributedto M. e;eenghalla will be further r3duced when the data is corrected forcatchabil i ty after the rotenone sample.

Even in i t s present imperfect and incomplete s ta te , certain facts areobvious from the present resul ts . One is that the rC:lservoir contains a largepopulation of L. calbasu which is not being harvested by the contractor.The second is that M. Seenghalla is l ike wise being avoided by the commereialfishermen. The same can be said for N. notogetrous and the minor carps .Another fact is that the vast populations of catla that are the legendof yesteryear exis t no more.

Immediate action is needed to curb se lec t ive fishing and prevent furtherdeterioration of the f ish populations. Fortunately s e b c t i v e fishlng willbe combated in future years with a naw base '1 atc system for sett ing n y a l t yrates to be started at Bundh Baretha in the 1971-72 fishing season.


26/29

23

IV. LIMITATIONS OF THE METliOD AND SOME POSSIBLE REMEDIES:There are a number c f pitfal ls which must be avoided when using this method ofpopulat ion estimation. There are a lso lnherent weaknesses w.hich must becompensated for as much as poss ib le to produce a useable es t imate . Some ofthese problems and poss ib le remedies are discussed below:

A. UNREPRESENTAtiVE ROTENONE SAMPLE:

1 PROBLEM: f the covo ch.:.Jsen for the rotenone sample is unrepresentat iveof the reservoir the C . C . F . s based on the sample wil l be wrong. At certaintimes of year the fish concentrate in s p ~ i f lparw of the reservoir as whenthey move to the upper end of the parts >f the reservoir a t the s tar t of themonsoon. Some species may move ~ groups a t other times of the year alsointroducing a chance e>f error. The est imation method makes the assumptionthat the fish are evenly distributE::d within such habitat_.

2) REMEDY: The problem of an unrepresre tat lve rotenone sample can beminimized by carefully picking a cove that is typical of the reservoir in alloutward reservoir in all outward r e spec t s . The t ime of year of the sampleis also Important; the sample should perhaps not be taken from April toSeptember. f more than one rotenone sample could be taken and the resultsaveraged this would obviously be bet ter.

The rotenone sample can a l so be checked for gross deviat ions from reservoirwide averages by comparing the results of sample netting in the cove aft-2rblocking i t off Immediately prior to taking the sample with the results thatwould be predicted for the cove from sample net t ing data from the reservoir

as a whole The learning factor must be remembered in considering thepre-rotenone sample netting in the cove. In spi te of this I a large school of

some spec ies of f ish could be detected from the ne.tting.

B. UNREPRESENTATIVE SAMPLE NETIING:

1) PROBLEM: An unrepresentat ive sample can contaminate the resultsby giving misleadlrg C. U .E s in the sample netting data . f the f ish are notevenly distr ibuted within each ~ the four habi ta ts a t the time of the samplenett ing the catch-per-unit-effort figures will sho N a bias which will bemultiplied many times in computing the est imated standing crops . There is some

Indicat ion in the data of unequal distr ibution of some species such as Catla 1within the habi ta ts . Since an


27/29

24

An addit ional point to remember with regards to unrepresentat ive samplenetting is that sample netting should not be done a t times Jf year whenthem is reason to believe that the fish popula tbns are unevenly distributedwithin the habi ta ts .

C. LEARNING BIAS IN SAMPLE NETTING:

1 PROBLEM: The Indian Major Curps are very quick to lec.rn to avoid gillnets . This is eas i ly seen during the r:>yalty fishing when a regular patterncan be seen of a high catch -per-untt -eff:>rt the f irst day, followed by asharp decline. The fishing i s normally interrupted by the contractor a numberof times during the season fc)r a variety c f reasons . After each interruptionthe s tar ts off high and then falls off rapidly as the fish learn to avoid thenets. Sample n e ~ t i n gdono lmmediatd after a period of f ishing by thecontractor yielded miserably small ca tches . i l so , i f the nets were setin the same place several nlghts in success ion the catches decreaseddramatically. Such learned avoidance c:>uld severely bias the sample.

2) REMEDY: Bias from learning can be mlntmized by collecting the sampleunder condit ions of wec2k but extended fishing pressure. It is theintensive fishing pressure of commercial fishing that causes the learningb ias . Sample netting should not b e done during or soon after a perlod offishing by the c.::>ntractor. Care should be taken not to set nets in thesame place on two nights in success ion. The nets should be rotatedsystematically between widely a separately between wldely ~ e p a r a t e d

sampling areas . Any data suspect of bias from learning should not be used

D . SMALLNESS OF THE SAMPLE:

1 PROBLEM: Because >f the great effort required to get a large samplethrough sample nett ing, the number of fish in each category is always l ikelyto remain smal l . When the difference of a single fish can significaratlychange the prediction, the sample must be considerec too small to berel iable.

2) REMEDY: The small sample problem can mly be c0untercd by makingthe sample as large a s possible . More se ts should be made with largemesh s ized nets and in sparsc: ly populated habitats such as the bottomdeep. ' he estimate is :_-,nly .:1s g.:>od as the category with the l eas t c a s e s .

The best way to judge when the point :>f diminishing returns has beenpassed for sample s ize and the sample is large enough is to analyze thedata and make a population est imate a t several points during the collectionof the data . f the predicted perc0ntages of the various species do notchange significantly with the addition of more data , then the sample ls

large enough .

E. EXTREMELY LOW CATCHABILITIES OF SOME SPECIES AND SIZE GROUPS:

1 PROBLEM: No matter how many times the nets are s e t , there willnot be a sufficient number of individuals caught in certain categorieswith very low catchabil i t ies to give a rel iable C . C. F. for that category.Very l g fi h f l h t b ght i th l t t i g


28/29

25

in his royalty ca tch . Certain species such as Channa marulius haveunusually low catchabil i t ies and are not present in the sample catch. nycategory with so few cases that the addit ion or subtraction or a singlefish can greatly affect the est imate must be considered unreliable.

2 .) REMEDY: The problem of very low catchabil i t ics can be compensatedby 1.) increasing the s ize of the sample and 2 . ) using catch-per-uni t effortdata for other kinds of gear. Larger mesh sized gil l nets , flag nets (faslas),hoop nets , trap ne t s , drag nets (chaundis), and trotlines for predators l ikeChanna marulius.

C . U. E. data for certain parts of the commercial catch might beuseable with caution. The royalty data i s biased by learning and by thepractice of discarding unwanted variet ies of f ish. Porha ps for a fewc a s e s , however, as for large catla caught on the first day of fishing, thedata would be useable . One other factor to keep in mind when using dragnet data from the commercial catch is the tremendous variation in the effectiveness of the gear in different depths of the water. f sufficient ingenuity i s u s e d .surely much could be found in this large and eas i ly gathered body ofinformation on the royalty catch that would add to the value of the populationestimate.

s a l a s t resor t , the problem of extremely low catchabil i t ies can bedeal t with by using the data from the rotenone cove sample direct ly forestimating the reservoir populations of species and s ize groups notadequately represented in the sample netting catch . This makes the assumptioneither that the habitat composition of tr sampled cove is the same as thereservoir as a whole, or that the fish are evenly distr ibuted throughout thehabitats of the reservoir. Both of these assumptions are highly unlikely.Using this method the kg/H .A. in the sampled cove would be taken as equalto the kg/H .A. for the entire reservoir.

F. VARIATIONS OF CATCHABILITIES WITH THE LUNAR CYCLE:

1.} PROBLEM: There is some evidence that the catch-per-unit-effortsdecrease when the m::>on is full. This etas could greatly prejudice thepopula tlo n es t imate .

2.) REMEDY: More study is needed t:J a s s e s s the baia from the moon.

The bias would be assessed by further subdividing the data and computingcatch- Jer- unit -effor ts separately for data collected when the moon is morethan half full and data collected when the moon is l e s s than half full. f thebias were found to be significant , then the ultimate remedy would be to dosample netting only on those days when the moon is l e ss than half full.

V CONCLUDING REMARKS:

The method for estimating standing crops and species compositions ofreservoir f ish populations using catch-per-unit-effort data from samplenetting and gear selectivity (catchability) information from a rotenonecove sample can be an easy and cheap tool for making reservoir managementdecisions in Rajasthan. When used in conjunction with other methods such

t h i t ff t from th g di t t i f t


29/29

26

in the sample netting ca tch , t promises to yield serviaeable pvpulat ion est imates.These estimates can be put to immediate use n Rajasthan in set t ing roya l tyrates under the proposed base-rate system to counter se lec t ive f i sh lng Seeproposal for improvement of f ishing c:>ntract arr l auct ion system a t BundhBaretha Sept 29, 1970; an illustration-.:> how the base-rate system wouldwork, Dec 5 1970; the base-rate system: .Jbjections answered March 29,1971;a Guide to the Base-Rate system March 30, 1971) and in conduct ing thesuggested common carp p i lo t study see Report of work done a t Bundh BarethaJuly 5 1970, page 0) a t some reservoir in Rajasthan.

PF:v

Documents

A Method for Estimating