1. Summary of Caribbean Data Evaluation SEDAR January, 2009 3/24/09 Todd Gedamke (SEFSC)

2. Terms of Reference – Data Evaluation SEDAR (paraphrased) 1)Review available data and develop recommendations regarding their accuracy and reliability. Provide complete tables. 2)Review the basis for existing stock complexes. 3)Recommend species or stock complexes for which informative SEDAR benchmark assessments may be feasible. 4)Review alternative methods for estimating mortality rates and abundance trends that might be useful for those species or stock complexes for which data are deemed sufficient. 5)Review the research and monitoring recommendations from the previous assessments in the U.S. Caribbean. 6)Provide guidance on developing ACLs given data accuracy and reliability recommendations.

3. Terms of Reference – Data Evaluation SEDAR 1)Review available data and develop recommendations regarding their accuracy and reliability. Provide complete tables. Recreational Data Fishery Independent Data Commercial Trip tickets—Landings Commercial Trip Interview Program (TIP)—Length Frequency Data Available Data

4. Recreational Fisheries Data MRFSS initiated in Puerto Rico in 2000 –In 2005: 470,00 shore mode trips; 380,000 private mode trips; <35,000 charter boat trips –No data collected on conch, whelk, or lobster MRFSS is not conducted in the US Virgin Islands Occasional, short-term recreational surveys do occur, e.g. May- Sept. 2000 when 50,000 recreational conch fishers were estimated in Puerto Rico and the Virgin Islands There is no long- term, ongoing monitoring of recreational fishing in the US Caribbean other than MRFSS in Puerto Rico

5. Fishery-Independent Data Catalog of datasets being compiled/reviewed –documenting coverage, focus, availability of data –NMFS/NOS cataloging coral reef monitoring to improve coordination Most studies spatially or temporally limited –earlier studies very limited –increase in coverage ~ 2000 to present Diver-based studies limited to <100ft –shallow water snapper, groupers, grunts, parrotfishes – OK –no (or few) deep water snapper, big grouper, or pelagics Need context of study – e.g., catches from spawning aggregation, targeting depths, methods Courtesy: Ron Hill

6. Fishery-Independent Data SEDAR’s 4, 8, and 14 did not find a useful time series to conduct assessments Need strong recommendations for well- funded, well-designed fishery-independent research programs Courtesy: Ron Hill

7. Trip Tickets aka. Sales Records Self reported commercial fishing data Reported Landings

8. {other-1 =(conch, whelk, octopus, squid, clams, oysters); other-2 = (does not include conch, whelk); other-3 = "other"} Quantity of gear and fishing timeNo effort data (# of pots recorded in shaded years/groups) Available years of landings data and species groups that were used on the St. Thomas/St. John trip tickets.

9. Puerto Rico Sales Records Available Computerized Since 1983 Identifies species specific landings on each sales record For early/most years not a unique 1:1 relation between sales records and trips (multiple trips on one ticket) Trends in Total Catch Landed affected by reporting rates Review- reporting rates of fisher sales records vary by year, area, gear

10. Trip Tickets aka. Sales Records Self reported commercial fishing data Reported Landings Expansion Factors

11. Reported Landings Only (Not expanded)

12. Puerto Rico Commercial Fishery Reporting Rates

13. USVI 1.Lower expansion factors 2.No species specific records 3.Some effort data exists 4.TIP data can’t be used to estimate species composition Puerto Rico 1.Higher expansion factors 2.Species specific records 3.Questionable effort data hampers CPUE calculations Pros/Cons of Trip Ticket Data

14. Use of Trip Ticket/Landings data to generate indices of abundance (CPUE)

15. Data filtering Significant reduction in sample sizes Trips reporting multiple gears or regions fished were excluded Hours fished must be reported Gear fished must be reported Only single trip reports used

16. Conclusions regarding CPUE Indices With careful evaluation of raw data (primarily effort measure) reasonable CPUE indices may be possible but they have limited utility because: -Short time series  limited contrast -Started well after initiation of fishery Potential to use CPUE in conjunction with mean length methodology Obvious trends could be used in ‘informed judgement’ approach

17. Trip Interview Program (TIP)

18. Data collected by port samplers Provides length frequency of sampled catch In terms of characterizing catch (e.g. species composition, landings verification, or CPUE) there are two issues: 1) Very small fraction of the total landings are sampled. On the order of 1-2% in the USVI and 3-5% for PR. 2) Questions as to whether samples were complete catch samples (i.e. 100% of catch sampled for length).

19. Grouper Unit 4 Total Number of Measured fish in TIP Database Priority FMP Units

20. Number of Measured Fish – Puerto Rico – All Grouper Unit 4

21. Snapper Unit 1

22. Number of Measured Fish – Puerto Rico – All Snapper Unit 1 SNAPPER UNIT 1-PUERTO RICO Gear_DescriptionGEARCODE_FREQ_GEAR_CLASS1%TOTAL LINES HAND, OTHER61023402HOOK AND LINE62.67% POTS AND TRAPS, FISH34510996TRAPS29.45% TROLL & HAND LINES CMB6001089HOOK AND LINE2.92% LINES TROLL, OTHER660339HOOK AND LINE0.91% LINES LONG, REEF FISH676333LONG LINE0.89% POTS AND TRAPS, SPINY LOBSTER355305TRAPS0.82% ROD AND REEL611234HOOK AND LINE0.63% POTS AND TRAPS, CMB300219TRAP NETS0.59% GILL NETS, OTHER425142GILL NETS0.38% REEL, MANUAL61291HOOK AND LINE0.24% HAUL SEINES, LONG3085SEINE NETS0.23% LINES LONG SET WITH HOOKS67531LONG LINE0.08% TRAMMEL NETS53025TRAMMEL NETS0.07% LINES TROLL, MACKEREL66519HOOK AND LINE0.05% DIVING OUTFITS, OTHER94313DIVING BY HAND OR SPEARFISHING0.03% BUOY GEAR, VERTICAL61410HOOK AND LINE0.03% 8TRAP NETS0.02% POTS AND TRAPS, PERWKLE OR CKL3652TRAPS0.01%

23. Number of Measured Fish – St. Croix – All Snapper Unit 1

24. Number of Measured Fish – St. Thomas/St. John – All Snapper Unit 1

25. Parrotfish – All Species

26. PARROTFISH-PUERTO RICO Gear_DescriptionGEARCODE_FREQ_GEAR_CLASS1%TOTAL TRAMMEL NETS53018715TRAMMEL NETS58.63% POTS AND TRAPS, FISH3458080TRAPS25.31% GILL NETS, OTHER4252544GILL NETS7.97% DIVING OUTFITS, OTHER943891DIVING BY HAND OR SPEARFISHING2.79% POTS AND TRAPS, CMB300639TRAP NETS2.00% LINES HAND, OTHER610510HOOK AND LINE1.60% HAUL SEINES, LONG30338SEINE NETS1.06% BY HAND, OTHER955102DIVING BY HAND OR SPEARFISHING0.32% POTS AND TRAPS, SPINY LOBSTER35599TRAPS0.31% TROLL & HAND LINES CMB60043HOOK AND LINE0.13% POTS AND TRAPS, CRAB, BLUE33037TRAPS0.12% POTS AND TRAPS, LOBSTER INSHOR35028TRAPS0.09% ROD AND REEL61128HOOK AND LINE0.09% HAUL SEINES, BEACH2018SEINE NETS0.06% 15TRAP NETS 0.05% ENTANGLING NETS (GILL) UNSPC40012GILL NETS0.04% LINES TROLL, OTHER66010HOOK AND LINE0.03% POTS AND TRAPS, EEL3409TRAPS0.03% GILL NETS, DRIFT LARGE PELAGIC5205GILL NETS0.02% SPEARS7603DIVING BY HAND OR SPEARFISHING0.01% LINES TROLL, TUNA6551HOOK AND LINE0.00% Number of Measured Fish – Puerto Rico – Parrotfish

27. Number of Measured Fish – St. Croix – Parrotfish

28. PARROTFISH-ST.THOMAS/ST. JOHN Gear_DescriptionGEARCODESP_FREQ_GEAR_CLASS1%TOTAL POTS AND TRAPS, FISH3452276TRAPS85.53% POTS AND TRAPS, CMB300196TRAP NETS7.37% POTS AND TRAPS, SPINY LOBSTER35577TRAPS2.89% 54TRAPS2.03% POTS AND TRAPS, BOX TRAP38049TRAPS1.84% LINES HAND, OTHER6105HOOK AND LINE0.19% HAUL SEINES, LONG302SEINE NETS0.08% LINES TROLL, OTHER6601HOOK AND LINE0.04% SPEARS7601 DIVING BY HAND OR SPEARFISHING0.04% Number of Measured Fish – St. Thomas/St. John – Parrotfish

29. Evaluation of Spatial Changes in the Fisheries TIP DATA

30. # of measured fish (normalized by annual totals) Change in proportions of regions sampled (two different periods indicated by red arrows Puerto Rico – Hook and Line (610) -Snapper Unit 1 Limited information available to evaluate spatial changes (USVI distance from shore variable uninformative) Deep water snapper fishery (WNW Puerto Rico) needs to be evaluated separately Highlighted the need to collect better spatial and depth information

31. Terms of Reference – Data Evaluation SEDAR (paraphrased) 1)Review available data and develop recommendations regarding their accuracy and reliability. Provide complete tables. 2)Review the basis for existing stock complexes. 3)Recommend species or stock complexes for which informative SEDAR benchmark assessments may be feasible. 4)Review alternative methods for estimating mortality rates and abundance trends that might be useful for those species or stock complexes for which data are deemed sufficient. 5)Review the research and monitoring recommendations from the previous assessments in the U.S. Caribbean. 6)Provide guidance on developing ACLs given data accuracy and reliability recommendations.

32. Cluster Analysis – Species Composition Andy Strelcheck, Nick Farmer, Jason Reuter Analysis was relatively consistent with current FMP species groups Discussion group with fisherman resulted in some suggested modifications Joe/Jason?

36. Terms of Reference – Data Evaluation SEDAR (paraphrased) 1)Review available data and develop recommendations regarding their accuracy and reliability. Provide complete tables. 2)Review the basis for existing stock complexes. 3)Recommend species or stock complexes for which informative SEDAR benchmark assessments may be feasible. 4)Review alternative methods for estimating mortality rates and abundance trends that might be useful for those species or stock complexes for which data are deemed sufficient. 5)Review the research and monitoring recommendations from the previous assessments in the U.S. Caribbean. 6)Provide guidance on developing ACLs given data accuracy and reliability recommendations.

37. Estimating Mortality from Mean Lengths in Non-equilibrium Situations (Gedamke and Hoenig 2006) Photos from Nancie Cummings Life History report--Photos reprinted from http://www.flmnh.ufl.edu/fish/gallery/descript/muttonsnapper/muttonsnapper.html. http://www.flmnh.ufl.edu/fish/gallery/descript/muttonsnapper/muttonsnapper.html

38. F = 0.2 F = 0.4 More Fishing  Less Older/Larger Fish

39. 5 assumptions: 1.Asymptotic growth, K and L  known & constant over time. 2.No individual variability in growth. 3.‘Constant’ & continuous recruitment over time. 4.Mortality constant with age (eg. Selectivity, M). 5.Mortality constant over time  Population in equilibrium (mean length reflects mortality) Beverton-Holt mean length mortality estimator

40. Assumption 5 Population in equilibrium (enough time elapsed after change in mortality that mean length reflects new mortality). Hard to meet in the real world! Years to “reach” equilibrium after change in mortality Life History Parameters from Goosefish

41. fishing mortality instantaneously increased from 0.4 to 1.0 Z will be underestimated until new equilibrium is reached

42. fishing mortality instantaneously increased from 0.4 to 1.0 With new method able to calculate mean length at any time after change

43. Z = 0.14 Z = 0.31 Z = 0.56 Z = 0.25 Goosefish Mortality Estimates--Northern Management Region NEFSC Fall Groundfish Survey Sample sizes range from 12 to 108 per year

44. Puerto Rico – Silk Snapper - Traps (345) – All Depths Z = 1.12  0.31 in 2001.8

45. Integrating Catch Rates into the Mean Length Analysis Model Development Extensions to base model to maximize use of available data Multi-Species / Multi-Gear Approach Assumes that species within ‘complex’ are subject to similar patterns of effort (e.g. same year of change or same proportional change in F)

46. Multi-gear Analysis – Traps and Hook/Line

47. Silk Reference lines - Expected Mean Length assuming F = M as proxy for F msy

48. Multi-gear Analysis – Traps and Hook/Line Silk Reference lines - Expected Mean Length assuming F = M as proxy for F msy F msy F cur F msy / F cur = 1.2

49. Terms of Reference – Data Evaluation SEDAR (paraphrased) 1)Review available data and develop recommendations regarding their accuracy and reliability. Provide complete tables. 2)Review the basis for existing stock complexes. 3)Recommend species or stock complexes for which informative SEDAR benchmark assessments may be feasible. 4)Review alternative methods for estimating mortality rates and abundance trends that might be useful for those species or stock complexes for which data are deemed sufficient. 5)Review the research and monitoring recommendations from the previous assessments in the U.S. Caribbean. 6)Provide guidance on developing ACLs given data accuracy and reliability recommendations.

50. Terms of Reference – Data Evaluation SEDAR (paraphrased) 1)Review available data and develop recommendations regarding their accuracy and reliability. Provide complete tables. 2)Review the basis for existing stock complexes. 3)Recommend species or stock complexes for which informative SEDAR benchmark assessments may be feasible. 4)Review alternative methods for estimating mortality rates and abundance trends that might be useful for those species or stock complexes for which data are deemed sufficient. 5)Review the research and monitoring recommendations from the previous assessments in the U.S. Caribbean. 6)Provide guidance on developing ACLs given data accuracy and reliability recommendations.

51. Summary Tables Summary rating of the quality of commercial, recreational and fishery independent data available for species listed in the Caribbean Fishery Management Council’s fishery management plans. The labels ‘BENCH’ or ‘OFL’ indicate the data may be sufficient to warrant either a full SEDAR benchmark assessment or OFL advice, respectively (it is assumed a benchmark assessment would also render OFL advice). The numerical rating scale is: (5) reliable data for more than 10 years; (4) reliable data for recent years; (3) data for more than 10 years, but reliability, comprehensiveness or coverage is questionable; (2) data for recent years, but reliability, comprehensiveness or coverage is questionable; (1) scattered or occasional observations, reliability questioned; (0) data unavailable or unreliable.

52. St. Croix

53. St. Thomas/ St. John

54. Puerto Rico

55. Conclusions/Recommendations of Caribbean Data Evaluation SEDAR If stock has adequate length and catch data (listed as ‘OFL’ in Summary Table) Estimate total mortality (Z) using the Gedamke and Hoenig (2006) base model and newly developed multispecies/multigear extensions to the method. Compute recent fishing mortality rate by subtracting out an assumed natural mortality rate (F = Z – M). Select a proxy for FMSY such as the natural mortality rate or the fishing mortality rate associated with a given spawning potential ratio Set OFL = FMSY*(recent average catch)/F Otherwise, if no reliable catch data exist, develop rationale for alternative management measures that do not conform to the framework established in the NS1 guidelines. Otherwise, if stock has adequate catch data, then use informed judgment if consensus can be reached on a proxy for FMSY and the level of depletion relative to unfished levels, d = (Bfirst – Blast)/B0, then set OFL = (average catch)/(n + d/(0.4*FMSY)) if consensus can be reached on a vulnerability scalar from a PSA analysis, then set OFL = (average catch) * vulnerability scalar if no consensus can be reached, adopt protocol of PFMC, i.e., OFL = average catch and ABC = 0.5*(average catch).

56. Conclusions/Recommendations of Caribbean Data Evaluation SEDAR If stock has adequate length and catch data (listed as ‘OFL’ in Summary Table) Estimate total mortality (Z) using the Gedamke and Hoenig (2006) base model and newly developed multispecies/multigear extensions to the method. Compute recent fishing mortality rate by subtracting out an assumed natural mortality rate (F = Z – M). Select a proxy for FMSY such as the natural mortality rate or the fishing mortality rate associated with a given spawning potential ratio Set OFL = FMSY*(recent average catch)/F Otherwise, if no reliable catch data exist, develop rationale for alternative management measures that do not conform to the framework established in the NS1 guidelines. Otherwise, if stock has adequate catch data, then use informed judgment if consensus can be reached on a proxy for FMSY and the level of depletion relative to unfished levels, d = (Bfirst – Blast)/B0, then set OFL = (average catch)/(n + d/(0.4*FMSY)) - (Alec MacCall – DCAC) if consensus can be reached on a vulnerability scalar from a PSA analysis, then set OFL = (average catch) * vulnerability scalar if no consensus can be reached, adopt protocol of PFMC, i.e., OFL = average catch and ABC = 0.5*(average catch).

57. Conclusions/Recommendations of Caribbean Data Evaluation SEDAR If stock has adequate length and catch data (listed as ‘OFL’ in Summary Table) Estimate total mortality (Z) using the Gedamke and Hoenig (2006) base model and newly developed multispecies/multigear extensions to the method. Compute recent fishing mortality rate by subtracting out an assumed natural mortality rate (F = Z – M). Select a proxy for FMSY such as the natural mortality rate or the fishing mortality rate associated with a given spawning potential ratio Set OFL = FMSY*(recent average catch)/F Otherwise, if no reliable catch data exist, develop rationale for alternative management measures that do not conform to the framework established in the NS1 guidelines. Otherwise, if stock has adequate catch data, then use informed judgment if consensus can be reached on a proxy for FMSY and the level of depletion relative to unfished levels, d = (Bfirst – Blast)/B0, then set OFL = (average catch)/(n + d/(0.4*FMSY)) if consensus can be reached on a vulnerability scalar from a PSA analysis, then set OFL = (average catch) * vulnerability scalar if no consensus can be reached, adopt protocol of PFMC, i.e., OFL = average catch and ABC = 0.5*(average catch).

58. Todd Gedamke (SEFSC) Thank you! Meeting summary for: Caribbean Data Evaluation SEDAR March, 2009

59. Summary CFMC Annual Catch Limit Working Group (ACLG) Meeting CAROLINA, PUERTO RICO FEBRUARY 23-25, 2009 Todd Gedamke (SEFSC)

60. Day 1 – SEDAR Report and Summary/Discussion of Methodologies Day 2 – Two Working Groups: -Productivity-Susceptibility Analysis -Development of Decision Table for setting of ACL’s (Scenarios table) Day 3 – Discussion, Evaluation of Recent Catch, and recommendations for ACL’s

62. Attributes List (N = 22) Scored on a 1-3 scale (high, med, low) Separate weighting score Productivity Intrinsic rate of increase (r) Maximum age (Tmax) Maximum size (Lmax) Growth Coefficient (k) Natural Mortality (M) Fecundity Breeding Strategy Recruitment Pattern Age at Maturity (Tmat) Mean Trophic Level Susceptibility Management Strategy Areal Overlap (range) Geographic Concentration Vertical Overlap (water depth) Fishing Rate (F) relative to M Biomass of Spawners (SSB) or other proxies Seasonal Migrations Schooling/Aggregation and Other Behavioral Responses Morphology Affecting Capture Survival After Capture and Release Desirability/Value of the Fishery Fishery Impact to EFH or Habitat in General for Non-targets

64. ACLG Working Group – Decision Table for ACL’s

67. Beverton-Holt mean length mortality estimator length at which all animals are fully vulnerable to gear mean lengthtotal mortality growth rate maximum length

68. ACLG Working Group – Decision Table for ACL’s

69. # of measured fish (normalized by annual totals) Change in proportions of regions sampled (two different periods indicated by red arrows Puerto Rico – Hook and Line (610) -Snapper Unit 1 Limited information available to evaluate spatial changes (USVI distance from shore variable uninformative) Deep water snapper fishery (WNW Puerto Rico) needs to be evaluated separately Highlighted the need to collect better spatial and depth information

70. fishing mortality instantaneously increased from 0.4 to 1.0 Z will be underestimated until new equilibrium is reached

71. Tiger Grouper – Hook and Line – Code 610 – Puerto Rico Z BevHolt = 0.59 Given: L inf = 740 mm K = 0.11 yr -1 M = 0.115 yr -1 L c = 514.5 mm If L mean =550 mm then Z BevHolt = 0.59 yr -1

72. Tiger Grouper – Hook and Line – Code 610 – Puerto Rico Z BevHolt = 0.59 Given: L inf = 740 mm K = 0.11 yr -1 M = 0.115 yr -1 L c = 514.5 mm If L mean =550 mm then Z BevHolt = 0.59 yr -1 ?

73. Tiger Grouper – Hook and Line – Code 610 – Puerto Rico Z BevHolt = 0.59 587mm when F=M Given: L inf = 740 mm K = 0.11 yr -1 M = 0.115 yr -1 L c = 514.5 mm (Ault =300 mm) If L mean = 550 mm then Z BevHolt = 0.59 yr -1 When F = M, L mean = 587 mm

74. Tiger Grouper – Hook and Line – Code 610 – Puerto Rico Z BevHolt = 0.18 Z BevHolt = 0.59 587mm when F=M Given: L inf = 740 mm K = 0.11 yr -1 M = 0.115 yr -1 L c = 514.5 mm (Ault =300 mm) If L mean = 550 mm then Z BevHolt = 0.59 yr -1 When F = M L mean = 587 mm If L mean = 600 mm then Z BevHolt = 0.18 yr -1 ?

75. ACLG Working Group – Decision Table for ACL’s

76. F = 0.2 F = 0.4 More Fishing  Less Older/Larger Fish Constant Recruitment

79. Summary ACLG Scenario Recommendations PRSTTSTX QCACL EEZ =0 closely monitor ACL=50,000 lb ACL EEZ=0 (ACL=EEZ+State =50,000 lb; 200 qc/boat 5-month closed NassauABC=0 monitor aggregations ABC=0 NOTE: Commercial Sector

80. Summary ACLG Scenario Recommendations PRSTTSTX Parrotfish3 (99-06 avg.) (80,000) 4 (94-06 avg.) (ABC=50,000) 4 (94-06 avg.) (max. 270,000) GU477 SU11 (99-06 avg.) (284,400) 77 NOTE: Commercial Sector

81. Todd Gedamke (SEFSC) Thank you! Meeting summary for: CFMC ACLG Group March, 2009