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Time-Varying vs. Non-Time- Varying Growth in the Gulf of Mexico King Mackerel Stock Assessment: a Case Study Southeast Fisheries Science Center Jeff Isely,

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Presentation on theme: "Time-Varying vs. Non-Time- Varying Growth in the Gulf of Mexico King Mackerel Stock Assessment: a Case Study Southeast Fisheries Science Center Jeff Isely,"— Presentation transcript:

1 Time-Varying vs. Non-Time- Varying Growth in the Gulf of Mexico King Mackerel Stock Assessment: a Case Study Southeast Fisheries Science Center Jeff Isely, Michael Schirripa, John Walter and Matt Lauretta SEFSC J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 1

2 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 2

3 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 3

4 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 4

5 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 5

6 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 6 Landings

7 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 7

8 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 8

9 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 9 Investigative Model Configures KMK_GOM_1:uses CPUE only with no length or age-at-length(AAL); Two length bins (i.e. one big plus group) Allows recruitment deviations; Fixed sex-specific growth at Data Workshop values KMK_GOM_2:start with #1 Add only lengths and selectivity KMK_GOM_3:starts with #2 Adds Age at Length Freely estimated constant (time invariant) growth (i.e. no informed priors)

10 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 10 Females seems to be getting smaller over time

11 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 11

12 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 12 Additive random walk deviations in the growth parameters

13 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 13 Approaches to Model Selection use numerical methods quantify the performance of the model fit to the data for each model use more of a “deductive reasoning” approach: utilizing “if / then” logic to arrive at a “common sense” decision Some combination of the two methods

14 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 14 Model_3: Ignore the observed changes in size-at-age and fits model to the data “as is” (null model). Model_4: Use time varying growth to address the changes in observed size-at-age. Fixes the growth parameters at those estimated in in #3. Allows for annual deviations in male and female L ∞ and k. Model_5: Use time varying selectivity to address the changes in observed size-at-age. Fixes the growth parameters at those estimated in in #3. Allows for annual deviations in fleet-specific selectivites. Three Models for Consideration

15 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 15 IF Model_3 is “more” correct THEN: No pattern to the size-at-age over time We would expect no significant improvement in the fit statistics if we vary growth We would expect no significant improvement in the fit statistics if we vary selectivity

16 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 16 IF Model_4 is correct THEN: we would expect to see a similar decrease in size-at-age for both male and females

17 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 17 Both sexes show similar patterns

18 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 18 Resulting Growth Curves

19 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 19 IF Model_5 is correct THEN we would need to believe that all gears changed selectivity at the same rate

20 J.J. Isely | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 20

21 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 21 There IS a significant improvement in the model fit statistics for Models_4 & 5 ** Although the LL maybe lower, it does not mean that the model is the most parsimonious

22 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 22 Both Model_4 and _5 fit better than _3

23 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 23 SSB for the four model configurations

24 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 24 SSB trends are similar, certainty is not Model_1Model_2 Model_3 Model_4

25 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 25 Both of the alternative models (Model_4 & Model_5) explain the data better than the null model (Model_3) but requires the belief of unbiased length/age sampling. Cannot identify underlying ecological or environmental causes. Model_4 accounted for the most variation in the data while using the fewest number of parameters to do so, but requires the belief that growth has decreased consistently and substantially in the past 25 years. Model_5, while not requiring a change in growth, requires the belief that the selectivity for all gears changed in synchrony without a change in fishing methods. Conclusions (Assessment Scientist)

26 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 26 Model_4: A 25-year decreasing trend in growth is unlikely.- Reject Model_5: It is highly unlikely that selectivity for all gears changed simultaneously. -Reject Model_3, Although not the best fit, requires the fewest assumptions and is consistent with our perception of the fishery. -Accept Conclusions (review workshop)

27 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 27 Weaknesses: The GOM KMK assessment model is not very stable. The data streams are lacking contrast and thus any real definitive signal related to stock status or stock productivity was not captured in the analysis. Strengths: Despite the weaknesses, nearly every model configuration suggests that the stock size has been increasing since 1990 with no indication that the stock is currently being overfished or experiencing overfishing. Recommendation: The current management strategy seems to be very effective at achieving stated goals and there is no evidence to suggest changes in the current quota would be beneficial. Additional Conclusions (review workshop)

28 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 28 Ageing method improvement: Has a change in ageing methods resulted in an increase in age at size? Institutional Memory: Were historical tournament/quota samples included in the general recreational catch samples? Coding/Identification issues: Are the small king mackerel in the historic Headboat samples really king mackerel? Were confiscated illegal catches included in the recreational samples? Regulations: Has there been a change in gear configuration in the Rec and HL fisheries that would eliminate larger fish (e.g. circle hooks)? Ecosystem-based assessment: Continue to investigate possible environmental and food-web changes in the GOM (FATE project). Remaining issues to be resolved

29 J.J. Isely | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 29

30 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 30 Ageing method improvement: Has a change in ageing methods resulted in an increase in age at size? Institutional Memory: Were historical tournament/quota samples included in the general recreational catch samples? Coding/Identification issues: Are the small king mackerel in the historic Headboat samples really king mackerel? Or were theyconfiscated illegal catches included in the recreational samples? Regulations: Has there been a change in gear configuration in the Rec and HL fisheries that would eliminate larger fish (e.g. circle hooks)? Ecosystem-based assessment: Continue to investigate possible environmental and food-web changes in the GOM (FATE project). Remaining issues to be resolved

31 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 31

32 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 32 Ageing method improvement: Has a change in ageing methods resulted in an increase in age at size? Institutional Memory: Were historical tournament/quota samples included in the general recreational catch samples? Coding/Identification issues: Are the small king mackerel in the historic Headboat samples really king mackerel? Were confiscated illegal catches included in the recreational samples? Regulations: Has there been a change in gear configuration in the Rec and HL fisheries that would eliminate larger fish (e.g. circle hooks)? Ecosystem-based assessment: Continue to investigate possible environmental and food-web changes in the GOM (FATE project). Remaining issues to be resolved

33 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 33

34 J.J. Isely | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 34

35 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 35 Ageing method improvement: Has a change in ageing methods resulted in an increase in age at size? Institutional Memory: Were historical tournament/quota samples included in the general recreational catch samples? Coding/Identification issues: Are the small king mackerel in the historic Headboat samples really king mackerel? Were confiscated illegal catches included in the recreational samples? Regulations: Has there been a change in gear configuration in the Rec and HL fisheries that would eliminate larger fish (e.g. circle hooks)? Ecosystem-based assessment: Continue to investigate possible environmental and food-web changes in the GOM (FATE project). Remaining issues to be resolved

36 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 36

37 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 37 Ageing method improvement: Has a change in ageing methods resulted in an increase in age at size? Institutional Memory: Were historical tournament/quota samples included in the general recreational catch samples? Coding/Identification issues: Are the small king mackerel in the historic Headboat samples really king mackerel? Were confiscated illegal catches included in the recreational samples? Regulations: Has there been a change in gear configuration in the Rec and HL fisheries that would eliminate larger fish (e.g. circle hooks)? Ecosystem-based assessment: Continue to investigate possible environmental and food-web changes in the GOM (FATE project). Remaining issues to be resolved

38 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 38 Questions?

39 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 39 Approaches to Model Selection Can use numerical methods quantify the performance of the model fit to the data for each model? Can use more of a deductive reasoning approach: utilizing “if / then” logic to arrive at a “common sense decision”? Some combination of the two methods (It’s critical to keep in mind that the data are likely biased to some degree (not perfect); one can favor the “right” model for the wrong reasons)

40 J.J. Isely | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 40 Figure 3.2.9. Observed and predicted length compositions of landings of GOM king mackerel in the recreational charter-private fleet (top). Observed (N) sample sizes and effective sample sizes (effN) estimated by SS are also reported. Pearson residuals for the length composition fit (bottom). Solid circles are positive residuals (i.e., observed greater than predicted) and open circles are negative residuals (i.e., predicted greater than observed).

41 J.J. Isely | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 41 Figure 3.2.6. Observed and predicted length compositions of landings of GOM king mackerel in the commercial handline line fleet (top). Observed (N) sample sizes and effective sample sizes (effN) estimated by SS are also reported. Pearson residuals for the length composition fit (bottom). Solid circles are positive residuals (i.e., observed greater than predicted) and open circles are negative residuals (i.e., predicted greater than observed).

42 J.J. Isely | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 42

43 J.J. Isely | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 43 Profile on Steepness

44 J.J. Isely | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 44

45 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 45 Fit to Lengths was improved with each successive model Model_2 Model_3 Model_4

46 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 46 Fit to Lengths was improved with each successive model Model_2 Model_3 Model_4

47 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 47

48 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 48 Fit to Observations

49 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 49 Model Configurations The total fishery was parsed into 5 fleets Commercial fisheries included handline (H&L), gillnet, and shrimp-fishery bycatch Recreational fisheries included Headboat and Charter/Private Surveys included Commercial H&L CPUE, Shrimp Effort, Headboat CPUE, SEAMAP Trawl Survey (age_1), and SEAMAP Larval Survey (SSB)

50 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 50 Landings

51 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 51

52 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 52 Life History Functions

53 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 53 Try constant growth with time varying selctivities Next Steps

54 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 54 Additive random walk deviations in the growth parameters parm’ (y) = parm (y-1) + dev(y)

55 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 55 Time varying growth adds 92 parameters but reduces LL by 769 units Model_3Model_4

56 J.J. Isely et al. | CAPAM Workshop | La Jolla, CA | November 3-7, 2014 Growth: theory, estimation, and application in fishery stock assessment models | Page 56 Fits to HL CPUE Model_1 Model_2 Model_3 Model_4

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