1. Condition

2. 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

3. Power Function W = aL b b > b < b =

4. Length-Weight Relationships Strong relationship between length and weight Iowa SMB R 2 = 0.99 P = 0.0001 Weight = 0.00000639 (Length) 3.123

5. Logarithm Rules

6. 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

7. Power Function So, if W = a L b

8. Length-Weight Relationship

9. Iowa SMB r 2 = 0.99 P = 0.0001 log 10 (W) = -5.033 + 3.057 log 10 (L)

10. Condition So…weight can be predicted from length

11. Condition

12. Indices of Condition Fulton condition factor Relative condition factor Relative weight

13. Fulton Condition Factor K = C = K TL, K SL C TL, C SL

14. Fulton Condition Factor K TL =

15. Fulton Condition Factor Condition factors vary for the same fish depending on whether you estimate K or C

16. Relative Condition Factor Compensates for differences in body shape Kn =

17. Relative Condition Factor Iowa SMB r 2 = 0.99 P = 0.0001 log 10 (W’) = -5.033 + 3.057 log 10 (L)

18. Relative Condition Factor

19. 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

20. Relative Weight Wr = 100 x (W/W s ) log 10 (W s ) = a’ + b log 10 (L) –Note: a’ = log 10 (a)

21. Relative Weight First equation was for LMB using data from Carlander (1977) –Compiled weights and a curve was fit to the 75 th - percentile weights to develop the Ws equation

22. Regression-Line-Percentile (RLP) Obtain length-weight data from populations across the distribution of the species Fit log 10 -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 75 th -percentile weight for each 1-cm length group Fit an equation to the 75 th -percentile weights

23. Regression-Line-Percentile (RLP)

26. n = 74

27. Regression-Line-Percentile (RLP) Obtain the 75 th -percentile weight for each 1-cm length group

28. Regression-Line-Percentile (RLP) log 10 (Ws) = -5.542 + 3.230 log 10 (length) Minimum length = 130 mm

29. Relative Weight—SMB Example Minimum length = 150 mm

30. Relative Weight