Condition
description
Transcript of Condition
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Condition
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Learning Objectives• Describe condition and different methods for
measuring or indexing condition• Calculate and interpret length-weight relationships• Describe the advantages and disadvantages of
different methods for describing condition• Describe the RLP technique• Calculate and interpret different condition indices• Describe relations of condition to rate functions
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Power Function
• W = aLb
• b >• b < • b =
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Length (mm)
0 100 200 300 400 500 600
Wei
ght (
g)
0
500
1000
1500
2000
2500
3000
3500
Length-Weight Relationships• Strong relationship between length and
weightIowa SMBR 2 = 0.99P = 0.0001
Weight = 0.00000639 (Length)3.123
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Logarithm Rules
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Logarithm Rules
• Multiplication inside the log can be turned into addition outside the log, and vice versa
• Division inside the log turned into subtraction (denominator is subtracted) outside, and vice versa
• An exponent inside log moved out as a multiplier, and vice versa
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Power Function
• So, if W = a Lb
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Length-Weight Relationship
Length (mm)
0 100 200 300 400 500 600
Wei
ght (
g)
0
500
1000
1500
2000
2500
3000
3500
log10 length (mm)
1.8 2.0 2.2 2.4 2.6 2.8
log 1
0 w
eigh
t (g
)
0
1
2
3
4
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log10 length (mm)
1.8 2.0 2.2 2.4 2.6 2.8
log 1
0 w
eigh
t (g
)
0
1
2
3
4
Length-Weight Relationship
Iowa SMBr 2 = 0.99P = 0.0001
log10 (W) = -5.033 + 3.057 log10 (L)
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Condition
• So…weight can be predicted from length
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Length (mm)
0 100 200 300 400 500 600
Wei
ght (
g)
0
500
1000
1500
2000
2500
3000
3500
Condition
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Indices of Condition
• Fulton condition factor • Relative condition factor • Relative weight
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Fulton Condition Factor
• K = • C =
• KTL, KSL
• CTL, CSL
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Fulton Condition Factor
KTL =
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Fulton Condition Factor
• Condition factors vary for the same fish depending on whether you estimate K or C
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Relative Condition Factor
• Compensates for differences in body shape
• Kn =
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Relative Condition Factor
log10 length (mm)
1.8 2.0 2.2 2.4 2.6 2.8
log 1
0 w
eigh
t (g
)
0
1
2
3
4Iowa SMBr 2 = 0.99P = 0.0001
log10 (W’) = -5.033 + 3.057 log10 (L)
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Relative Condition Factor
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Relative Condition Factor
• Average fish of all lengths and species have a value of 1.0 regardless of species of unit of measurement
• Limited by the equation used to estimate W’– Communication is hindered among agencies
• Also, tend to see systematic bias in condition with increasing length
• To help alleviate these problems and to improve utility of the condition indices, relative weight (Wr) was derived
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Relative Weight
• Wr = 100 x (W/Ws)
• log10 (Ws) = a’ + b log10 (L)
– Note: a’ = log10 (a)
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Relative Weight
• First equation was for LMB using data from Carlander (1977)– Compiled weights and a curve was fit to the
75th-percentile weights to develop the Ws equation
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Regression-Line-Percentile (RLP)
• Obtain length-weight data from populations across the distribution of the species
• Fit log10-transformed length-weight equation to obtain estimates of a’ and b for each population
• Estimate weight of fish at 1-cm intervals (from minimum and maximum lengths in data set) for each population
• Obtain the 75th-percentile weight for each 1-cm length group
• Fit an equation to the 75th-percentile weights
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Regression-Line-Percentile (RLP)
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Regression-Line-Percentile (RLP)
Flathead catfishn = 4 populations
log10 length (mm)
1.8 2.0 2.2 2.4 2.6 2.8 3.0
log 1
0 w
eigh
t (g
)
0.5
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
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Regression-Line-Percentile (RLP)
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Regression-Line-Percentile (RLP)
n = 74
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Regression-Line-Percentile (RLP)
• Obtain the 75th-percentile weight for each 1-cm length group
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Regression-Line-Percentile (RLP)
log10 length (mm)
2.0 2.2 2.4 2.6 2.8 3.0 3.2
log 10
wei
ght
(g)
1.0
1.5
2.0
2.5
3.0
3.5
4.0
4.5
5.0log10 (Ws) = -5.542 + 3.230 log10 (length)Minimum length = 130 mm
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Relative Weight—SMB Example
Minimum length = 150 mm
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Relative Weight
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Relative Weight
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Relative Weight
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Relative Weight
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Relative Weight
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Relative Weight
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Relative Weight
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Relative Weight