Parul (MFSc) CCSAU,Hisar FRM-504 tropical fish stock assessment (Gear selectivity, sampling of commercial catches)

1. GEAR SELECTIVITY, SAMPLING OF
COMMERCIAL CATCHES
Submitted by: Parul
(2020FS06M )
FRM Department
TROPICAL FISH STOCK ASSESSMENT (FRM-504)

2. GEAR SELECTIVITY
The complete length ranges (or age ranges) of fish or
shellfish are not always under full exploitation. Most
fishing gears, for example trawl gears, are selective
for the larger sizes, while some gears (gill nets) are
selective for a certain length range only, thus
excluding the capture of very small and very large
fish. This property of fishing gear is called "gear
selectivity".

3. CONT…
• we want to estimate the real size (or age) composition
of the fish in the fishing area.
• Regulating the minimum mesh sizes of a fishing
fleet, can more or less determine the minimum sizes
of the target species of certain fisheries.
• Gear selectivity is strongly related to the estimation
of the total mortality, Z, the analysis of trawl survey
data vis-it-vis commercial fisheries and predictions of
future yields (Thompson and Bell)

5. Estimation of Trawl Net Selection
The fine- meshed end of the net where the catch is
collected is called the codend. It appears that the
"mesh size" of the codend determines, to a large
extent, the selectivity of trawl gear.
The "mesh size" is usually defined as the length of the
"stretched" whole mesh.
Mesh size= 2*d
Where, d is the length between two
knots

6. Trawl net selectivity

7. The selectivity of the gear can then be determined by
comparing the sizes of the fish in the codend with
those of the fish in the cover. The "covered codend
method" has been described, among others, by Pope
et al. , 1975, and Jones, 1976.
 Covered codend expriment, Nemipeterus japonicus,
South China Sea:
• The threadfin bream, Nemipterus japonicus, which is
caught with a trawl net with a codend mesh size of 4
cm and a cover of much smaller meshes. The typical
catch of one trawl haul

8. • The fraction of the total catch which was retained in
the codend can then be calculated.
• It is presented as the fraction (e.g. 1/7 = 0.14) retained
of each length group.
• When the fraction retained is plotted against the mid-
length of the corresponding length group, it appears
that the points are following a sigmoid curve, which
reaches 1.00 (100% retention) at a certain length and
which approaches 0.00 (0% retention) at a certain small
length.
• This sigmoid curve is called the "gear selection ogive".
It resembles a cumulative normal distribution.

9. covered codend experiment
• The easiest mathematical expression to describe the
gear selection ogive is the so-called “logistic curve”:

10. and L is the length interval midpoint (mid-length). S1
and S2 are constants
Rewritten as:
l n(l/SL - 1) = S1 - S2*L
l n(l/SL - 1) = S1 - S2*L
l n(l/SL - 1) = S1 - S2*L
l n(l/SL - 1) = S1 - S2*L
l n(l/SL - 1) = S1 - S2*L

12. Estimation of Gill Net selection
1. Symmetrical selection curves: Gill net are usually
long rectangular nets where the upper edge, the
head rope has floats while the foot rope has sinkers.
Often gill nets (drifting & set nets) are in the form
of gangs of net with different mesh size.
Gill nets are “passive gears” i.e. the fish have
to swin into the get caught. The large fish move
faster than small fish of the small species.

13. The swimming speed can be approximated by a constant
time a power function of length:
Rudstam, Magnuson & Tonn(1984) included swimming
speed (with B=0.8 for the cisco, Coregonus artedii, from
wisconsin,USA) in to a model for gill net selection. They
considered the selection as the product of two probability:
(selection)=(probability of encounter)*(Probability of
being cought given encounter

14. For simple gill net: The selection curve has unlike trawl
(selection) a descending slope on the right hand side.
Small fish can not pass through the meshes as was as
the case for trawl nets. But large fish may also avoid
being caught in a gillnet, because their heads are so
large that they cannot be “gilled”. This is the simple
theory behind gill net selection.
Karlson & Bajarnason 1986 distinguished four way of
getting caught as illusted-
a) Snagged: where the mesh is around the fish just
behind the eye.
b) Gilled: where the mesh is around the fish just
behind the Gill cover.

15. c) Wedged: where the mesh is around the body as far as dorsal
fin.
d)Entangled: where the mesh is held in the teeth maxillaries, fin
or other projection.
Gill Net Selection

16. Holt’s Model for two mesh size
For gilling & Wedging Holt(1963) suggested a Bell-
shaped selection curve similar to the Normal
distribution:
where, Lm is “optimum length for being caught
S= standard deviation of Normal distribution
SL=A fraction i.e. 0<SL<=1

18. Mode for various mesh size:
n=mesh size, all used together in net of same size, there
will be n-1, estimates of the intercept (a) & slope(b):
[a(1),b(1)],[a(2),b(2)]…………[a(n-1)],[b(n-1)]
Corresponding to Mesh size:
[m(1),m(1)],[m(2),m(3)]…………[m(n-1)],m(n)]

19. Hanging Ratio
Gill net selection depends on a variety of factors besides
mesh size: Net construction,Visibility, Stretchability of net,
Net material, the shape, behaviour of fish. Entangling more
than wedging & gilling is affected by net construction.
“Hanging Ratio” or “Hanging coefficient” defined as:
length of the head rope
(no. of meshes)*(mesh size)
Hanging ratio= C
2*d
for square mesh, d= C
2

20. Hanging coefficient is demonstrated by Riedel(1963)
who reported catches of Tilapia mossambica with 10
cm mesh gill net with three different hanging ratios:

21. 2. The product of two Logistic curve(Asymmertical
curve): Estimating the selection curve would be
compare the catches of gill net to non-selective gear
i.e. trawl catches a Asymmetrical curve can be
obtained by multiplying two logistic curves.
Probability of gilled on wedged is ‘SL’
where, L=left hand side of selection curve
The curve is modelled by a “Reserved Logistic Curve”
i.e “SR” where ‘R’=right hand side of selection curve

23. Other Aspects of gear selectivity
 Knife edge pattern:
• Curve A has selection range 3cm & curve B has
selection range of 0cm. Curve B is a so called “Knife
Edege Curve”(beverton &Holt,1957)
• A shallow curve that gradually change between
L25% & L75% where as curve that very quickly
change from 0% to 100% selection (vertically curve).
• The small selection range produced a vertical line
selection and this is called Knife edge pattern.

25. Recruitment & Selectivity:
S=R*G
where, S=Resultant curve
R= Recruitment curve
G=Gear selection curve

26.  selectivity as function of age: The value of S1, S2, L50% &
L75% corresponding to this curve are as follows. Using the
Bertanlanffy growth equation, express length as function of
age & express S as function of age.

27. SAMPLING

28. Introduction:
Sampling is the process of selecting observations (a
sample) to provide an adequate description and
inferences of the population.
Sample
a) It is a unit that is selected from population
b) Represents the whole population
c) Purpose to draw the inference
Why Sample???
Sampling Frame Listing of population from which a
sample is chose

30. Sampling of Commercial Catches
The total net of catch & length & age composition of
the catch of each stock. Obtain data to sample the
landings of commercial fisheries. Sampling scheme
should take account the following factors:
The total area of distribution of stock of species.
All the fishing activities taking place in that area.
They may include different types of fleets and
different types of gears.

31. Sampling Errors
• The errors which arise due to the use of sampling
surveys are known as the sampling errors.
• Two types of sampling errors
 Biased Errors- Due to selection of sampling
techniques; size of the sample.
Unbiased Errors / Random sampling errors-
Differences between the members of the population
included or not included.