George Bank Cod Base –Similar to GARM2005 assessment Fleet_dome Survey_dome Survey_and_Fleet_dome Purpose: test models ability to estimate correctly when.

Slides:



Advertisements
Similar presentations
Stock Assessment for Central Southern Management Area (CSMA) Striped Bass Stocks Marine Fisheries Commission Business Meeting February 11, 2011.
Advertisements

Differential Item Functioning of the English- and Spanish-Administered HINTS Psychological Distress Scale Chih-Hung Chang, Ph.D. Feinberg School of Medicine.
Normal Distribution Sampling and Probability. Properties of a Normal Distribution Mean = median = mode There are the same number of scores below and.
Are the apparent rapid declines in top pelagic predators real? Mark Maunder, Shelton Harley, Mike Hinton, and others IATTC.
Models for Measuring. What do the models have in common? They are all cases of a general model. How are people responding? What are your intentions in.
An evaluation of alternative binning approaches for composition data in integrated stock assessments Cole Monnahan, Sean Anderson, Felipe Hurtado, Kotaro.
Determining relative selectivity of the gulf menhaden commercial fishery and fishery independent gill net data Southeast Fisheries Science Center Amy M.
Tradeoffs between bias, model fits, and using common sense about biology and fishing behaviors when choosing selectivity forms Dana Hanselman and Pete.
Growth in Age-Structured Stock Assessment Models R.I.C. Chris Francis CAPAM Growth Workshop, La Jolla, November 3-7, 2014.
Black Sea Bass – Northern Stock Coastal-Pelagic/ASMFC Working Group Review June 15, 2010.
The current status of fisheries stock assessment Mark Maunder Inter-American Tropical Tuna Commission (IATTC) Center for the Advancement of Population.
1 Case Study 1: How to Deal with Estimates with Low Reliability 2009 Population Association of America ACS Workshop April 29, 2009.
Growth in Length and Weight Rainer Froese SS 2008.
458 Model Uncertainty and Model Selection Fish 458, Lecture 13.
The Bell Curve Chapter 9 - Welfare Dependency Chapter 10 - Parenting Sondra M. Parmer March 13, 2003.
Using Scientific Measurements.
Hui-Hua Lee 1, Kevin R. Piner 1, Mark N. Maunder 2 Evaluation of traditional versus conditional fitting of von Bertalanffy growth functions 1 NOAA Fisheries,
458 Fitting models to data – III (More on Maximum Likelihood Estimation) Fish 458, Lecture 10.
Attrition and its effects – example from analysis of the MRC cognitive function and aging study Fiona Matthews MRC Biostatistics Unit.
The (potential) value and use of empirical estimates of selectivity in integrated assessments John Walter, Brian Linton, Will Patterson and Clay Porch.
60º Introduction and Background ù The Barents Sea covers an area of about 1.4 x 10 6 km 2, with an average depth of 230 m. ù Climatic variations depend.
Stock assessment of Summer flounder (Paralichthys dentatus) Managed as a unit stock from New England to North Carolina Maximum size & age fish in NEFSC.
Development and Implementation of a Monitoring Program for Mark-selective Chinook Salmon Fisheries in Puget Sound, Washington Washington Department of.
1 Things That May Affect Estimates from the American Community Survey.
Measuring the effects of a seasonal fishing closure on the abundance of Atlantic Cod (Gadus morhua) off the West Coast of Scotland Joanne Clarke 1*, David.
A retrospective investigation of selectivity for Pacific halibut CAPAM Selectivity workshop 14 March, 2013 Ian Stewart & Steve Martell.
Evaluation of a practical method to estimate the variance parameter of random effects for time varying selectivity Hui-Hua Lee, Mark Maunder, Alexandre.
April 15, 2003 UFE 2002 ANALYSIS. April 15, 2003 LOAD AND UFE – ERCOT PEAK 2002 This is a graphic depiction of load and UFE on the ERCOT Peak Day for.
EFFECTS OF HOUSEHOLD LIFE CYCLE CHANGES ON TRAVEL BEHAVIOR EVIDENCE FROM MICHIGAN STATEWIDE HOUSEHOLD TRAVEL SURVEYS 13th TRB National Transportation Planning.
WP 2.4 Evaluation of NMFS Toolbox Assessment Models on Simulated Groundfish Data Sets Comparative Simulation Tests Overview Brooks, Legault, Nitschke,
The Cod Day Marine Laboratory, Aberdeen, 2 October 2012 The Cod Day - Science Coby Needle, Nick Bailey, Rui Catarino, Steven Holmes Marine Laboratory Aberdeen.
. Assessment of the Icelandic cod stock Björn Ævarr Steinarsson Marine Research Institute.
Stock assessment of jack mackerel (Trachurus murphyi): a non- homogenous stock and changes in catchability. Hugo Arancibia* and Liesbeth van der Meer**
Problem of the Day x m x m x 10 8 km – 3.4 x 10 7 m 3. (9.21 x cm)(1.83 x 10 8 cm) 4. (2.63 x m) / (4.08 x.
Biodiversity of Fishes Growth Rainer Froese
Things that May Affect the Estimates from the American Community Survey Updated February 2013.
1 Follow Up Analysis of 2 vs. 3 Decimals ERCOT Load Profiling Department June 26, 2007.
Simulated data sets Extracted from:. The data sets shared a common time period of 30 years and age range from 0 to 16 years. The data were provided to.
Effects of grey seals on the herring population in the Baltic Sea area. Teija Aho, Anna Gårdmark, Karl Lundström and Jukka Pönni Swedish Board of Fisheries,
WP 3.1 Simulation Studies of Issues Associated with Filling Zeros in VPA Tuning Indices Chris Legault and Al Seaver The great appeal of the doctrine that.
Extending length-based models for data-limited fisheries into a state-space framework Merrill B. Rudd* and James T. Thorson *PhD Student, School of Aquatic.
Estimation of growth within stock assessment models: implications when using length composition data Jiangfeng Zhu a, Mark N. Maunder b, Alexandre M. Aires-da-Silva.
1 Federal Research Centre for Fisheries Institute for Sea Fisheries, Hamburg Hans-Joachim Rätz Josep Lloret Institut de Ciències del Mar, Barcelona Long-term.
Using distributions of likelihoods to diagnose parameter misspecification of integrated stock assessment models Jiangfeng Zhu * Shanghai Ocean University,
Errors. Random Errors A random error is due to the effects of uncontrolled variables. These exhibit no pattern. These errors can cause measurements to.
1 Climate Change and Implications for Management of North Sea Cod (Gadus morhua) L.T. Kell, G.M. Pilling and C.M. O’Brien CEFAS, Lowestoft.
Some Insights into Data Weighting in Integrated Stock Assessments André E. Punt 21 October 2015 Index-1 length-4.
Lecture 10 review Spatial sampling design –Systematic sampling is generally better than random sampling if the sampling universe has large-scale structure.
A bit of history Fry 1940s: ”virtual population”, “catch curve”
Dr Marion Burkimsher Universities of Geneva and Lausanne Visualisation of fertility trends: Switzerland as a case study.
UALG Statistical catch at age models Einar Hjörleifsson.
PMT time offset calibration (not completed) R.Sawada 27/Dec/2007.
Data weighting and data conflicts in fishery stock assessments Chris Francis Wellington, New Zealand CAPAM workshop, “ Data conflict and weighting, likelihood.
Influence of selectivity and size composition misfit on the scaling of population estimates and possible solutions: an example with north Pacific albacore.
Gulf of Maine cod SCAA/ASPM vs ADAPT-VPA Doug Butterworth and Rebecca Rademeyer __________________________________________________________________ Marine.
Definition Slides Unit 2: Scientific Research Methods.
Definition Slides Unit 1.2 Research Methods Terms.
Is down weighting composition data adequate to deal with model misspecification or do we need to fix the model? Sheng-Ping Wang, Mark N. Maunder National.
Gulf of Maine/Georges Bank Atlantic Herring Assessment Update – 2009.
Using Scientific Measurements.
FISHING EFFORT & CPUE.
ASAP Review and Discussion
Scientific Notation Scientific notation takes the form: M x 10n
Using Scientific Measurements.
الأستاذ المساعد بقسم المناهج وطرق التدريس
Selectivity.
RAM XI Training Summit October 2018
Effects of Catch-at-Age Sample Size on Gulf of Mexico Gray Triggerfish Spawning Stock Biomass Estimates Jeff Isely SEFSC Miami.
Uncertainty and Error
Summer Flounder, Scup, Black Sea Bass and Bluefish Update
Presentation transcript:

George Bank Cod Base –Similar to GARM2005 assessment Fleet_dome Survey_dome Survey_and_Fleet_dome Purpose: test models ability to estimate correctly when doming occurs

GB cod basic setup Years (27 years) Ages 1-25, 10+ Lengths cm 3 market categories 3 surveys (CVs 20%, 30%, 25%) CV on landings 5% Growth stdevs 5.0 initial, 2.0 projection Von B params 148.2, , % Mature ~42 cm Selectivity flat-topped, 50% selected 64 cm M = 0.2 F high ( ) then reduced in final years (0.48, 0.35)

GB cod test cases Fleet_dome –Moved ascending limb of selectivity curve left to allow for nearly full selectivity at peak of dome

GB cod test cases Survey_dome –Each survey mirrored for descending limb of selectivity curve at age 7

Georges Bank Cod BASEFleet Dome Survey Dome Fleet&Surv. Dome AIM SSB: strong bias F: -40% to+20% ASPICOne way trip problem SCALE SSB: 5-30% + F: ~30% - VPA SSB: slightly + F: slightly - ASAP SSB: slightly + F: slightly -

AIM Issues with low (or no) sampling in some years

Georges Bank Cod BASEFleet Dome Survey Dome Fleet&Surv. Dome AIM SSB: strong bias F: -40% to+20% Division by zero problem ASPICOne way trip problem SCALE SSB: 5-30% + F: ~30% - VPA SSB: slightly + F: slightly - ASAP SSB: slightly + F: slightly -

Georges Bank Cod BASEFleet Dome Survey Dome Fleet&Surv. Dome AIM SSB: strong bias F: -40% to+20% Division by zero problem ASPICOne way trip problem SCALE SSB: 5-30% + F: ~30% - Low simulated length sampling obscured the effect we were testing for VPA SSB: slightly + F: slightly - ASAP SSB: slightly + F: slightly -

SCALE Issues with very low sampling in some years

Georges Bank Cod BASEFleet Dome Survey Dome Fleet&Surv. Dome AIM SSB: strong bias F: -40% to+20% Division by zero problem ASPICOne way trip problem SCALE SSB: 5-30% + F: ~30% - Low simulated length sampling obscured the effect we were testing for VPA SSB: slightly + F: slightly - slightly - slightly + Same as base (‘E.coast way’) Same as “Fleet Dome” ASAP SSB: slightly + F: slightly -

VPA (SSB) Poor performance for ages>6

VPA (FAA) Poor performance for ages>6

Georges Bank Cod BASEFleet Dome Survey Dome Fleet&Surv. Dome AIM SSB: strong bias F: -40% to+20% Division by zero problem ASPICOne way trip problem SCALE SSB: 5-30% + F: ~30% - Low simulated length sampling obscured the effect we were testing for VPA SSB: slightly + F: slightly - slightly - slightly + Same as base (‘E.coast way’) Same as “Fleet Dome” ASAP SSB: slightly + F: slightly - slightly - Same as base (‘E.coast way’) Same as “Fleet Dome”

ASAP

VPA vs ASAP (NAA)

Precision (SSB and F) AIM: ~ 0.1, did not vary by case SCALE: (increased with retros) VPA*: (poor ages>6), did not vary ASAP: <0.05, did not vary *VPA CVs are for age-specific SSB, F

GB Cod Conclusions Simulation set-up precluded model comparisons for AIM, ASPIC, and SCALE Between VPA and ASAP, bias was similar, but VPA estimates at age degraded faster than ASAP; ASAP more precise Dome not an issue for survey because of age- specific indices (rather than age comp. for total N index) Dome effect in fleet probably minimized because of large simulated F (fewer older fish, so misspecifying those selectivities added little bias)

VPA PR BaseFleet Dome

VPA Fleet Dome Retro

VPA q “East Coast Style” Survey DomeBase