Condition

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

Power Function

• W = aLb

• b >• b < • b =

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

Logarithm Rules

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

Power Function

• So, if W = a Lb

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

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)

Condition

• So…weight can be predicted from length

Length (mm)

0 100 200 300 400 500 600

Wei

ght (

g)

0

500

1000

1500

2000

2500

3000

3500

Condition

Indices of Condition

• Fulton condition factor • Relative condition factor • Relative weight

Fulton Condition Factor

• K = • C =

• KTL, KSL

• CTL, CSL


KTL =


• Condition factors vary for the same fish depending on whether you estimate K or C

Relative Condition Factor

• Compensates for differences in body shape

• Kn =


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)


• 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

Relative Weight

• Wr = 100 x (W/Ws)

• log10 (Ws) = a’ + b log10 (L)

– Note: a’ = log10 (a)

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

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


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


n = 74


• Obtain the 75th-percentile weight for each 1-cm length group


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

Relative Weight—SMB Example

Minimum length = 150 mm

Relative Weight

Condition

Documents

Transcript of Condition