Length, Weight, and Associated Structural Indices

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Length, Weight, and Associated Structural Indices

• Chapter 15
• R. O. Anderson and R. M Neumann

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What good are length Weight Data?
Length Weight
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Sampling and Measuring Considerations
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Length Measurements..
Insert scanned pic of fig 15.1
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Length

• Two approaches -
• Three common whole body measurements
• Measurement of body parts

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Measuring Devices

• Measuring boards
• tape measurers
• calipers
• electronic boards/computers

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• Weight Measurements.
• Weighing fish is more difficult, particularly in
  the field.
• Can use top-loading electronic balances,
  mechanical balances, or hanging spring scales.

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• Accuracy and Precision of Measurements-
• Calibration with standard weights-- accuracy.
• Influence of water on fish upon weight measures
• (error is inversely proportional to fish size)--
  results in a loss of precision.

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Preservation can result in deviations from
fresh length and weight.
Insert scanned image of Fig 15.2
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Weight - Length Relationships. Analysis of LW
data has been directed toward 2 objects. LeCren
(1951) first presented the general relationship
between weight and length of fishes. W a
L b where W weight, L length, and a and b
are parameters.
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The parameters for L - W relations can be
transformed for linear regression log10 (W)
a b log10 (L) May need to develop
different relationships for males and females if
they grow / mature differently.
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Scan in figure 15.3 here
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Indices of condition

• Can be a wide variation in weight between fish of
  the same length
• Three basic variations of indices of condition
  for whole fish

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Fulton Condition Factors (K and C) for metric
units K ( W / L3 ) X 100,000 for English
units C ( W / L3 ) X 10,000 Values differ
for same fish with K and C Fultons Folly
Size effects on the factor.
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Relative Condition Factor (Kn) compensates for
allometric growth (shape changes as fish
grow Kn ( W / W ) Where W is the weight
of the individual and W is the length-specific
mean weight for a fish in the study population.
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Relative Weight (Wr) Wege and Anderson (1978)
presented a refinement of Kn. Wr ( W / Ws ) X
100 Where W is the weight of an individual, Ws
is a length- -specific standard weight predicted
by a L-W regression designed to represent the
species. The Ws equation log10(Ws) a b
log10(L) a - y intercept b - slope L - max total
length of the fish
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Caution Wr has been found to be influenced by
size. Wr equations are available for most
sport and game species (see Table 15.1). Wr
has been found to be significantly related to
Consumption and Growth in walleye, but
relationship was not strong enough for
prediction (r-sq. lt 0.4).
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Sample calculation of Wr (insert box 15.4).
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Wr has been successfully used to estimate fat
levels in bluegills (insert box 15.6)
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Length-frequency Histograms. - typically use
N100 individuals - can be used to compare
populations and angler catches.
Insert L/F histogram of Swekas Brook trout
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Stock Density Indices. Numerical descriptors of
length-frequency data. Proportional Stock
Density PSD of fish gt minimum quality
length of fish gt minimum stock length
X 100
Stock length approximate length at maturity,
minimum length effectively sampled by traditional
fisheries gears and the minimum length of fish
that provide recreational value 20-26 of world
record Quality length defined as minimum size
desired by anglers. Example LB minimum stock is
20 cm and minimum quality is30.
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Stock Density Indices. Relative Stock
Density RSD of fish gt specified length
of fish gt minimum stock length
X 100
Insert table 15.3 Stock density ranges.
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PSD may be related to density and biomass in some
cases insert fig 15.7