fisheries models: methods, data requirements, environmental linkages
DESCRIPTION
Fisheries Models: Methods, Data Requirements, Environmental Linkages. Richard Methot NOAA Fisheries Science & Technology. PRESENTATION OUTLINE. Assessment Goals What is a “Stock Assessment”? Data Inputs Assessment Methods Role of Environmental Data. Stock Assessment. - PowerPoint PPT PresentationTRANSCRIPT
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Fisheries Models:Methods, Data Requirements, Environmental LinkagesRichard MethotNOAA FisheriesScience & Technology
Stock Assessment Overview
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PRESENTATION OUTLINEAssessment GoalsWhat is a Stock Assessment?Data InputsAssessment MethodsRole of Environmental Data
Stock Assessment Overview
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Stock AssessmentCollecting, analyzing, and reporting demographic information for the purpose of determining the effects of fishing on fish populations.Key Concepts / JargonStock; Population; UnitAbundance; Biomass; Spawning BiomassRecruitment; Yearclass; CohortFisheryFishing mortality (F); Exploitation Rate
Stock Assessment Overview
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STOCK ASSESSMENT PROCESSPOPULATION MODEL:(Abundance, mortality)STOCK STATUSOPTIMUM YIELDCATCHLOGBOOKS,OBSERVERS,AGE/SIZE DATABIOLOGY AGE, GROWTH, MATURITYABUNDANCE TREND RESOURCE SURVEY,FISHERY CPUE, AGE/SIZE DATAADVANCED MODELS HABITAT CLIMATE ECOSYSTEM MANMADE STRESSSOCIOECONOMICS
Stock Assessment Overview
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STOCK ASSESSMENT & ECOSYSTEMOPTIMUM YIELDSINGLE SPECIESASSESSMENTMODELTIME SERIESOF RESULTS BIOMASS,RECRUITMENT,GROWTH,MORTALITYHOLISTIC ECOSYSTEM MODEL CUMULATIVE EFFECTS OF ALL FISHERIES AND OTHER FACTORSINDICATORS ENVIRONMENTAL,ECOSYSTEM,OCEANOGRAPHICRESEARCH ONINDICATOREFFECTS
Stock Assessment Overview
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Assessment ResultsUsed in Fishery ManagementMonitoring / ReactiveExploitation rate is higher than a maximum limit:overfishing is occurring and must be eliminated;biomass is below a minimum level:the stock is overfished (depleted). A rebuilding plan must be prepared to rebuild the stock in as short a time as possible;ProactiveAssessment forecasts provide the technical basis (operational model) for setting and adjusting fishery quotas and other management measures to:implement harvest policiesRebuild depleted stocks
Stock Assessment Overview
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HARVEST CONTROL RULE= OPERATIONAL MODELWhat is the current stock abundance relative to historical and target levels?What level of fishing mortality (F) is the limit (RED) and target (GREEN)?What level of short-term future catch would achieve target?
Stock Assessment Overview
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RELATIVE ABUNDANCE
CATCH
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RELATIVE ABUNDANCE
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Widow
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1975230733329845502150836147731.1955519750.36963521890.84693254650.94774114270.95688085620.77871488060.4641632793
1976212303525444499146592144211.164619760.34010989890.89668328420.92685009690.92995755960.76016024460.452147175
1977197463773143872136605142941.0431419770.31633584850.95968562420.91379058970.86660153650.75346581620.4049912451
1978192363918943959133090137570.94703919780.30816552120.99676976290.91560267440.84430290610.72515945390.367680756
1979184933931644093128211129121.0061419790.296262475810.91839370140.81335126530.6806177850.3906262739
1980175463803242546119927117121.1454819800.28109129940.96734154030.88617191890.76079881750.61736334410.444723979
1981175333225339778117963106001.1742219810.28088303620.82035303690.82851846450.74833949740.55874756210.4558820675
198217131253293691511594998011.172219820.27444289580.64424153020.76888629690.73556298490.51663064680.4550978177
198316464194573420111212382981.8473119830.26375738930.49488757760.71235758470.71129141740.43740445940.7172041884
198415572175923089310924469952.3093919840.24946732670.44745141930.64345670780.69302747520.36872067890.8966032667
198514873170552786610595368732.1599519850.23826917220.43379285790.58040865630.67214986710.36228981080.8385843127
198614388166652395510074366962.0869319860.23049935120.42387323230.49894815770.63909841210.35295978070.8102348479
19871352816481218379495966132.5757119870.21672193650.41919320380.45483326740.60240558770.34858468191
19881280115782227228980760652.4356719880.20507521510.40141418250.47326654310.5697220760.31969848720.9456305252
19891224314978244548536354972.2088619890.19613591580.38096449280.50934160920.54153000960.28975805180.8575732516
19901181413019257078204647342.0181719900.18926322870.33113745040.5354397950.52048746140.24953876970.783539296
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19921159811079269347727233021.5908319920.18580285480.28179367180.56099643830.49020192470.17405513680.6176277609
19931137110632275207574925561.3883819930.18216625820.27042425480.57320197450.48054024220.13473195930.5390280738
1994112509860278497450019621.1970819940.18022780790.25078848310.58005457080.47261677440.1034210110.4647572902
1995110959533278527231718260.94512619950.17774466930.24247125850.58011705650.45876815130.09625217440.3669380481
1996112738985273446910717890.85777519960.18059627370.22853291280.5695361480.4384043950.09430182910.3330246806
1997113958664270336527816440.87685419970.18255074410.22036829790.56305846580.4141137960.08665858420.3404319586
1998115948261267446210014800.79774619980.18573877380.21011801810.55703901190.39395304280.07801381060.3097188736
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POP
WIDOW
CHILI
SABLEFISH
CANARY
HAKE
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FISHING REDUCES LIFETIME EGG PRODUCTION
Stock Assessment Overview
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DIRECT FISHING EFFECTSYield per Recruit and Eggs (Spawning Biomass) per Recruit
Stock Assessment Overview
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Assessment InputsSTOCK STRUCTURE: Spatial limits of demographic unitTOTAL CATCH: total removals due to human activities (due to fishery landings, discarded bycatch, and cryptic mortality due to encounters with fishing gear);SURVEYS: the relative or absolute magnitude of a fish population (by age);LIFE HISTORY: growth, maturation, fecundity, natural mortality, and other characteristics of individual fish.
Stock Assessment Overview
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STOCK ASSESSMENT PROCESS
POPULATION MODEL:(Abundance, mortality)
STOCK STATUS
OPTIMUM YIELD
CATCHLOGBOOKS,OBSERVERS,AGE/SIZE DATA
BIOLOGY AGE, GROWTH, MATURITY
ABUNDANCE TREND RESOURCE SURVEY,FISHERY CPUE, AGE/SIZE DATA
ADVANCED MODELS HABITAT CLIMATE ECOSYSTEM MANMADE STRESS
SOCIOECONOMICS
Stock Assessment Overview
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What is a Stock?A group of individuals of the same species that:inhabit the same geographic region;interbreed when mature;have sufficiently high levels of diffusion/mixingNorthern StockSouthern StockHigh mixing withinLow mixing between
Stock Assessment Overview
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Pillar I - Catch DataFisheries Information SystemCommercial fishing effort, catch, and valueDealer reports Vessel trip reportsRecreational fishing effort and catchTelephone surveysShoreside sampling surveysSize and age structure of catchCommercial catch sampling surveysRecreational catch sampling surveys Electronic dissemination of dataServes stock assessment, economic analysis, and fishery monitoring needs
Stock Assessment Overview
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Fishery ObserversSince 1972 NOAA Fisheries has deployed fishery observers to collect catch and bycatch data from US and foreign commercial fishing and processing vessels.Today, 42 fisheries all around the nation are monitored by observer programs logging over 60,000 observer days at sea.Data support fish stock assessment, fishery monitoring, protected species mortality monitoring, and other conservation and management programs.
Stock Assessment Overview
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Pillar II - Abundance IndexFishery-Independent SurveysCatch/Effort = q * AbundanceSurvey sampling units (effort) is highly standardized;Sampling follows a statistical design;Assert that q is sufficiently constant;Sometimes, q can be measured directly, so survey catch rate can be transformed directly to measure of abundance
Stock Assessment Overview
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Fishery-Independent Surveys10 NOAA ShipsPlus 1768 charter DAS
Stock Assessment Overview
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Fishery CPUE as Abundance IndexFishery Catch = q * Effort * AbundanceSoCatch/Effort = q * Abundance
Unfortunately,Fishing effort is very hard to standardize, so the effective q may not be constant;Fishing tends to occur where abundance is high, not where abundance is average.
Stock Assessment Overview
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Advanced TechnologyAutonomous Underwater VehicleContains cameras, sensors, acousticsReach into habitats inaccessible to other survey tools
Stock Assessment Overview
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Pillar III - Fish Biology / Life HistoryEase: Length > Weight >> Age > Eggs & Maturity >>> Mortality
Stock Assessment Overview
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STOCK ASSESSMENT LOGICEstimating AbundanceHow big must stock have been if:We saw a relative decline of X% per year in the survey index;While Y tons of catch were removed per year;And the stocks biology indicates that natural changes in abundance are only +/-Z% per year
Stock Assessment Overview
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BASIC ASSESSMENT APPROACHESIndex MethodsIs stock abundance:Increasing, decreasing, or stable?Equilibrium MethodsOn average, is fishing mortality: too high, too low, or just right?Dynamic Population MethodsEstimates time series of stock abundance and mortalityForecast stock abundance and catch level that maintains mortality targetCan be biomass-based, but age & size structure provide more detail, especially for forecastingChoice depends on data availability and complexity of management questions
Stock Assessment Overview
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Trend in Survey Abundance IndexLack of fit due to:Sampling variability of the observationsEnvironmental data can improve stratification and adaptive samplingUnknown changes in the calibration, qEnvironmental data can inform about changes in availability of fish to the surveyOther Data in Model:Recruitment index for some yearsProportion at each age in the fisheryTotal catch
Stock Assessment Overview
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INTEGRATED ANALYSISAbility to use various age, length, abundance data to calibrate modelSmoothly transitions from pre-data era, to data-rich era, to forecast.Produces estimates of model uncertainty
Stock Assessment Overview
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MODEL PROCESSESCONSTANT
Assert, Believe!, Hope!! To Be Stable Over TimeTraditional Data Provide Little Information To Estimate VariabilityExamples:Natural MortalitySurvey CatchabilityAverage Spawner-Recruitment RelationshipVARIABLE
Expected To Vary Over TimeData Are Informative About FluctuationsExamples:Fishing MortalityAnnual RecruitmentGrowth and Maturity Changes
Stock Assessment Overview
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PRODUCTIVITYHigh productivity stocks maintain high recruitment levels even as stock abundance declines. They rebuild quickly as fishing mortality is reduced.Low productivity stocks can sustain only low fishing mortality rates. They require multiple generations to rebuild from low biomass levels.Short-term (annual) environmental variability obscures these ecological relationshipsLong-term (decadal) environmental and ecosystem shifts are confounded with relationships
Stock Assessment Overview
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ENVIRONMENTAL DATA &VARIABLE PROCESSESIncluding environmental component in model can:Reduce alias in estimate of biomass linkage caused by long-term environmental patterns;Provide additional information on historical fluctuations during data-poor periods;Provide early indicators of upcoming fluctuations.Similar situation for environmental effects on body growthEcosystem effects are harder!Recruitment = f(biomass, environment, ecosystem) + e
Stock Assessment Overview
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ENVIRONMENTAL DATA &CONSTANT PROCESSESNew Information About Changes In Constant ProcessesNeed Validation Outside ModelEXAMPLES:Predators Affect Natural MortalitySpatial Distribution Affects CatchabilityThermocline Depth Affects CatchabilityPDO Regime Affects Average Recruitment
Stock Assessment Overview
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Fisheries And The Environment
FATEA NOAA Fisheries Oceanographic Program
Supporting NOAAs mission to ensure the sustainable use of US fishery resources under a changing climate
Stock Assessment Overview
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A FATE Ecosystem Indicator Peterson et al.; Northwest Fisheries Science CenterThis function can be used to predict returns of salmon the following year; copepod anomalies from 2001 predict that about 10% of the juvenile salmon that went to sea in spring 2001 will return to spawn in fall 2002.
Stock Assessment Overview
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Sablefish Recruitment VariabilityMichael J. Schirripa and Jim J. ColbertNorthwest Fisheries Science Center, Oregon State University
Recruitment is fit to stock biomass as well as annual deviations in the Spring sea level anomalies. This made possible estimates of current year-class strengths
Stock Assessment Overview
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P < 0.0001R-squared = 0.436
1997 El Nino
2003
1999
Q2 North Sea Level (Z-score)
Rec Dev
Iy = (SL*0.393)-0.016
Sheet1
CV =0.060.63make ENVmake INDEX
YearQ2CoastalSeaLvlNorZ-scoreEst RecruitsyearseasonZ-sealevelyearseasonfleetvaluecvYearQ2CoastalSeaLvlNorZ-Scoredev4SERecruitswt est devnc_run_noenv
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19391.33900-0.0818410894.1540011193411.413996919391410894.150.2019881.309330.130860.2105620.08768113982.60.05309138670.289101
19401.356000.136139467.6160012193510.34554231940149467.620.2019891.29442-0.165050.3450420.09023915749.30.18204268830.43457
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19541.412300.857974743.2578026194912.40552271954144743.260.2020031.327500.49124-2.48680.88807729.974-0.10395545-1.64832
19551.33900-0.0818410894.154002719501-0.174154019551410894.150.2020041.30050-0.044370.129453610.12945361
19561.420500.963114055.1630028195110.70026921956144055.160.2020051.367801.29074-0.4523573736-0.4523573736
19571.393900.622066287.2754029195210.39768291957146287.280.20
19581.458671.45246852.4453330195310.5421380195814852.450.20
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19821.31667-0.3681912768.233330.251915419771-1.581949719821412768.230.20
19831.371830.339138138.977671.351555519781-0.45508631983148138.980.20
19841.33083-0.1865511579.451670.534295619791-1.363984919841411579.450.20
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19921.33025-0.1940311628.401500.522666419871-0.934466219921411628.400.20
19931.448001.315701747.528002.869806519881-0.46220931993141747.530.20
19941.30075-0.5722614103.86450-0.065366619891-0.653462719941414103.860.20
19951.30542-0.5124313712.265830.027666719901-0.477167719951413712.270.20
19961.33942-0.0765010859.189830.705396819911-1.048790919961410859.190.20
19971.399830.698135789.385671.909686919921-0.19402721997145789.390.20
19981.33158-0.1769311516.516170.5492470199311.315699119981411516.520.20
19991.25208-1.1962418187.67917-1.035457119941-0.572260119991418187.680.20
20001.30942-0.4611413376.609830.107397219951-0.512426720001413376.610.20
20011.22950-1.4857920082.73700-1.485607319961-0.076497220011420082.740.20
20021.23400-1.4280919705.12400-1.3959074199710.698132320021419705.120.20
20031.32750-0.2292911859.165000.467857519981-0.176931920031411859.170.20
20041.30050-0.5754714124.84300-0.070357619991-1.196237620041414124.840.20
20051.3678020.287448477.262971.271197720001-0.4611409
7820011-1.4857888
1.345387920021-1.4280922
8020031-0.2292862
8120041-0.5754655
200510.2874440
Sheet1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Year
Sea Level Z-Score
Sheet2
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Sea Level
Number of Recruits
Sheet3
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Year
Number of Recruits
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
00
RecDev = 11.37 + (SL*-8.64)P < 0.0001R-squared = 0.436
1997 El Nino
2003
1999
Q2 North Sea Level (m)
Rec Dev
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Sea Level Z-score
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Sea Level Z-score
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
RecDev = (SL*-0.3933)-0.0163P < 0.0001R-squared = 0.436
1997 El Nino
2003
1999
Q2 North Sea Level (Z-score)
Rec Dev
HEREARENEWANDIMPROVEDESTIMATES
X1X2X3Estimated
YearMissingMoApr-MayMay-JunApr&JunQ2
192761.3915
1.384548
19295
1.41151.406714
19324
1.469
1.44956
19334
1.384
1.379392
193861.3995
1.392013
194361.4465
1.435874
19464thru6
DISCUSS
195061.335
1.331822
19525
1.37951.3764
19545
1.41751.412398
195661.43
1.420476
195751.3981.393925
-
Evan Howell and Jeff Polovina, Pacific Islands Fishery Science Center
Stock Assessment Overview
-
1981 cohortSTD Growth rateGrowth yearUsing variables related to oceanic conditions* we can fit growth rates for individual California cohorts and the probability that a cohort will mature after the third ocean winter at sea.
*e.g. Wind Turbulence,Upwelling, Sea Level Height, Sea Surface Temperature.
Proportion maturing after 3 OWBrood year (cohort)CA Chinook Growth and Maturation Vary with the EnvironmentB. Wells, C. Grimes, J. Field, C. Reiss; Southwest Fisheries Science Center
Stock Assessment Overview
Chart3
-0.068218606-0.172669218
0.07633170940.0727257414
-0.284557147-0.370439794
0.02983462760.1119483415
Predicted
MODELEDGROWTHRATE
these are built from age and environment models uses data title modeledgrowthrate.txt
systembroodyrgrowthyr_TYPE__FREQ__STAT_GROWTHRATEannuluswidth
REDW1978197803MEAN0-0.142239811
REDW1978197903MEAN-0.051906354-0.105150937
REDW1978198003MEAN-0.021589851-0.453028729
REDW1978198103MEAN0-0.113273188
REDW1978198201MEAN0-0.157317646
REDW19791979018MEAN00.0248490778
REDW19791980017MEAN0.05428576770.0647274948
REDW19791981017MEAN0.02169024790.0234418595
REDW1979198201MEAN00.1063268124
REDW19801980014MEAN00.0529601889
REDW19801981015MEAN0.08424539020.0414290634
REDW1980198209MEAN-0.121953631-0.071984284
REDW1980198302MEAN0-0.291723188
REDW19811981016MEAN0-0.127639811
REDW19811982016MEAN0.0458598939-0.06690927
REDW19811983010MEAN-0.049794878-0.176478729
REDW19811984010MEAN00.0574968124
REDW19821982037MEAN00.0052574862
REDW19821983037MEAN0.0090959436-0.038727513
REDW19821984036MEAN0.04622625310.1894629379
REDW1983198308MEAN0-0.058502311
REDW1983198408MEAN-0.0041799980.01095323
REDW1983198503MEAN0.0072002434-0.055795395
REDW1983198603MEAN00.1359268124
REDW19841984037MEAN0-0.003772244
REDW19841985035MEAN0.00905221540.1026814443
REDW19841986035MEAN-0.0073264860.0626969855
REDW1984198702MEAN0-0.093823188
REDW19851985011MEAN00.0491783707
REDW19851986011MEAN0.04131362580.0238611846
REDW1985198705MEAN-0.005170442-0.157908729
REDW1985198804MEAN0-0.042573188
REDW19861986029MEAN00.0339912234
REDW19861987028MEAN0.0194897382-0.01225927
REDW19861988027MEAN0.018299464-0.084162062
REDW1986198906MEAN0-0.023123188
REDW19871987022MEAN0-0.039089811
REDW19871988022MEAN0.0229537236-0.027806997
REDW19871989019MEAN-0.012025299-0.133028729
REDW1987199002MEAN0-0.101773188
REDW1987199102MEAN0-0.005117646
REDW19881988022MEAN00.0716647343
REDW19881989021MEAN-0.039220363-0.111493794
REDW19881990016MEAN-0.025691567-0.069491229
REDW19881991014MEAN00.1039053838
REDW19891989014MEAN00.0211101889
REDW19891990015MEAN-0.062415424-0.18006427
REDW19891991015MEAN-0.035518575-0.004862062
REDW1989199206MEAN0-0.071806521
REDW1989199301MEAN0-0.016517646
REDW1990199005MEAN0-0.081339811
REDW1990199105MEAN0.0083186824-0.03776427
REDW1990199203MEAN0.0370869795-0.139128729
REDW1990199301MEAN0-0.219673188
REDW1991199104MEAN00.0331601889
REDW1991199204MEAN0.09078103670.06961573
REDW1991199302MEAN-0.0299615220.2870712712
REDW1992199202MEAN00.4269101889
REDW1992199302MEAN0.010485060.28536573
Mill1977197704MEAN0.0473106859-0.060529218
Mill1977197804MEAN-0.377576759
Mill1977197904MEAN-0.081623128
Mill1977198004MEAN0.06838018660.0110566748
Mill19781978029MEAN-0.020590425
Mill19781979029MEAN-0.095842276
Mill19781980029MEAN0.0953178719-0.022018817
Mill1978198104MEAN0.09401666970.1226316748
Mill1978198201MEAN00.1765126491
Mill19791979031MEAN-0.104675186MILL
Mill19791980031MEAN0.12344074130.1277587252
Mill19791981029MEAN-0.0216201020.0463501481
Mill1979198204MEAN0.11161089240.1567816748
Mill19801980020MEAN0.13883422850.0836607822
Mill19801981020MEAN0.07273386420.1122432414
Mill19801982018MEAN-0.10507703-0.176987017
Mill1980198303MEAN-0.107897292-0.374534992
Mill19811981040MEAN-0.068218606-0.172669218
Mill19811982040MEAN0.07633170940.0727257414
Mill19811983036MEAN-0.284557147-0.370439794
Mill19811984012MEAN0.02983462760.1119483415
Mill19821982055MEAN-0.061940082-0.113909672
Mill19821983055MEAN-0.124995997-0.14376585
Mill19821984053MEAN0.08878833580.1862377213
Mill1982198505MEAN0.11536346590.2953116748
Mill19831983026MEAN-0.132912897-0.135192679
Mill19831984026MEAN0.13363421440.1386847798
Mill19831985026MEAN-0.0146786050.1045826415
Mill1983198601MEAN0.0549146185-0.067268325
Mill19841984044MEAN0.0846962760.1509753277
Mill19841985044MEAN0.04777859460.1371391505
Mill19841986037MEAN0.0355019160.0839478182
Mill1984198708MEAN0.03699600720.0124191748
Mill19851985078MEAN0.08547562890.1673611668
Mill19851986078MEAN0.09848037840.1122104209
Mill19851987073MEAN-0.005362946-0.065741963
Mill1985198808MEAN0.0227380822-0.063268325
Mill19861986013MEAN0.09969622830.2570265514
Mill19861987013MEAN0.07079613560.014438626
Mill1986198809MEAN0.0441878573-0.146431461
Mill1987198707MEAN0.0583871408-0.008118504
Mill1987198806MEAN0.0281363044-0.098343425
Mill1987198906MEAN0.0220883385-0.277081461
Mill1987199004MEAN-0.001799888-0.276843325
Mill1987199101MEAN0-0.349587351
Mill19881988015MEAN0.14832635650.0473957822
Mill19881989015MEAN0.0145576077-0.043476759
Mill19881990015MEAN-0.072310221-0.283218128
Mill1988199106MEAN0.08838970760.1829483415
Mill19891989023MEAN0.1254959349-0.015939
Mill19891990023MEAN-0.05120175-0.246924585
Mill19891991020MEAN0.03455688760.2832668722
Mill1989199203MEAN0.0262808636-0.179534992
Mill1989199301MEAN0-0.073387351
Mill1990199007MEAN0.1186822214-0.198218504
Mill1990199107MEAN0.11301549310.0627232414
Mill1990199205MEAN-0.338433556-0.136918128
Mill1990199303MEAN-0.113357541-0.165268325
Mill19911991018MEAN0.0588278429-0.047598662
Mill19911992018MEAN-0.100848049-0.102815648
Mill19911993018MEAN-0.095781176-0.085614794
Mill1991199405MEAN0.09478457160.3679316748
Mill19921992013MEAN-0.120034871-0.147181141
Mill19921993013MEAN-0.0324058560.0898617029
Mill19921994012MEAN-0.072401030.1287102056
Mill19931993028MEAN-0.009283176-0.006647075
Mill19931994028MEAN0.02659110410.1173518128
Mill19931995026MEAN-0.158640567-0.119713512
Mill19931996012MEAN0.0658169070.0740733415
Mill19941994024MEAN0.01526921650.1886999489
Mill19941995024MEAN-0.001522987-0.072401759
Mill19941996024MEAN-0.004488167-0.124381461
Mill1994199706MEAN-0.1276829240.0862816748
Mill19951995027MEAN-0.047689481-0.083378292
Mill19951996027MEAN0.06211185180.0963602784
Mill19951997024MEAN-0.169963578-0.060039794
Mill1995199806MEAN0.0452623045-0.016718325
Mill1995199901MEAN0-0.124587351
Mill19961996022MEAN0.054078525-0.037690581
Mill19961997022MEAN-0.120210082-0.054904031
Mill19961998020MEAN-0.117676376-0.182558128
Mill1996199908MEAN0.17805244960.0357441748
Mill19971997037MEAN-0.065154709-0.066160975
Mill19971998037MEAN0.01679389580.0116529711
Mill19971999035MEAN0.0762889529-0.059658128
Mill1997200002MEAN0.04911572360.0849816748
Mill19981998025MEAN-0.068102266-0.072084218
Mill19981999025MEAN0.17833002260.0718672414
Mill19982000014MEAN-0.0063463030.077816158
Mill1998200103MEAN0.0836869670.0292650081
Mill19991999026MEAN-0.147807828-0.064358064
Mill19992000026MEAN0.08849352630.084188626
Mill19992001017MEAN-0.0257116080.1180842252
Mill2000200001MEAN-0.091001162-0.059404218
Mill2000200101MEAN0.0526954840.4391232414
MODELEDGROWTHRATE
00
00
00
00
Predicted
1980
00
00
00
00
Predicted
00
00
00
00
Predicted
1982
00
00
00
00
Predicted
1983
00
00
00
00
Predicted
1984
00
00
00
00
Predicted
1985
00
00
00
Predicted
1986
00
00
00
00
00
Predicted
1987
00
00
00
00
Predicted
1988
00
00
00
00
00
Predicted
1989
00
00
00
00
Predicted
1990
00
00
00
00
Predicted
1991
00
00
00
Predicted
1992
00
00
00
00
Predicted
1994
00
00
00
00
00
Predicted
1995
00
00
00
00
Predicted
00
00
00
00
Predicted
1997
0-0.142239811
-0.051906354-0.105150937
-0.021589851-0.453028729
0-0.113273188
0-0.157317646
Predicted
1978
00.0248490778
0.05428576770.0647274948
0.02169024790.0234418595
00.1063268124
Predicted
1979
00.0529601889
0.08424539020.0414290634
-0.121953631-0.071984284
0-0.291723188
Predicted
1980
00
00
00
00
Predicted
1981
00.0052574862
0.0090959436-0.038727513
0.04622625310.1894629379
Predicted
1982
0-0.058502311
-0.0041799980.01095323
0.0072002434-0.055795395
00.1359268124
Predicted
1983
0-0.003772244
0.00905221540.1026814443
-0.0073264860.0626969855
0-0.093823188
Predicted
1984
00
00
00
00
Predicted
1985
00.0339912234
0.0194897382-0.01225927
0.018299464-0.084162062
0-0.023123188
Predicted
1986
0-0.039089811
0.0229537236-0.027806997
-0.012025299-0.133028729
0-0.101773188
0-0.005117646
Predicted
1987
00.0716647343
-0.039220363-0.111493794
-0.025691567-0.069491229
00.1039053838
Predicted
1988
00
00
00
00
00
Predicted
1989
0-0.081339811
0.0083186824-0.03776427
0.0370869795-0.139128729
0-0.219673188
Predicted
1990
00.0331601889
0.09078103670.06961573
-0.0299615220.2870712712
Predicted
1991
00
00
00
00
Predicted
1992
00
00
00
00
Predicted
1997
MBD000301FD.xls
Chart8
-0.053314819-0.08482216
0.0659507970.0863556233
0.12585564850.0980796919
0.10523222520.0338525224
Predicted
MODELEDGROWTHRATE
these are built from age and environment models uses data title modeledgrowthrate.txt
systembroodyrgrowthyr_TYPE__FREQ__STAT_GROWTHRATEannuluswidth
REDW1978197803MEAN0-0.142239811
REDW1978197903MEAN-0.051906354-0.105150937
REDW1978198003MEAN-0.021589851-0.453028729
REDW1978198103MEAN0-0.113273188
REDW1978198201MEAN0-0.157317646
REDW19791979018MEAN00.0248490778
REDW19791980017MEAN0.05428576770.0647274948
REDW19791981017MEAN0.02169024790.0234418595
REDW1979198201MEAN00.1063268124
REDW19801980014MEAN00.0529601889
REDW19801981015MEAN0.08424539020.0414290634
REDW1980198209MEAN-0.121953631-0.071984284
REDW1980198302MEAN0-0.291723188
REDW19811981016MEAN0-0.127639811
REDW19811982016MEAN0.0458598939-0.06690927
REDW19811983010MEAN-0.049794878-0.176478729
REDW19811984010MEAN00.0574968124
REDW19821982037MEAN00.0052574862
REDW19821983037MEAN0.0090959436-0.038727513
REDW19821984036MEAN0.04622625310.1894629379
REDW1983198308MEAN0-0.058502311
REDW1983198408MEAN-0.0041799980.01095323
REDW1983198503MEAN0.0072002434-0.055795395
REDW1983198603MEAN00.1359268124
REDW19841984037MEAN0-0.003772244
REDW19841985035MEAN0.00905221540.1026814443
REDW19841986035MEAN-0.0073264860.0626969855
REDW1984198702MEAN0-0.093823188
REDW19851985011MEAN00.0491783707
REDW19851986011MEAN0.04131362580.0238611846
REDW1985198705MEAN-0.005170442-0.157908729
REDW1985198804MEAN0-0.042573188
REDW19861986029MEAN00.0339912234
REDW19861987028MEAN0.0194897382-0.01225927
REDW19861988027MEAN0.018299464-0.084162062
REDW1986198906MEAN0-0.023123188
REDW19871987022MEAN0-0.039089811
REDW19871988022MEAN0.0229537236-0.027806997
REDW19871989019MEAN-0.012025299-0.133028729
REDW1987199002MEAN0-0.101773188
REDW1987199102MEAN0-0.005117646
REDW19881988022MEAN00.0716647343
REDW19881989021MEAN-0.039220363-0.111493794
REDW19881990016MEAN-0.025691567-0.069491229
REDW19881991014MEAN00.1039053838
REDW19891989014MEAN00.0211101889
REDW19891990015MEAN-0.062415424-0.18006427
REDW19891991015MEAN-0.035518575-0.004862062
REDW1989199206MEAN0-0.071806521
REDW1989199301MEAN0-0.016517646
REDW1990199005MEAN0-0.081339811
REDW1990199105MEAN0.0083186824-0.03776427
REDW1990199203MEAN0.0370869795-0.139128729
REDW1990199301MEAN0-0.219673188
REDW1991199104MEAN00.0331601889
REDW1991199204MEAN0.09078103670.06961573
REDW1991199302MEAN-0.0299615220.2870712712
REDW1992199202MEAN00.4269101889
REDW1992199302MEAN0.010485060.28536573
Mill1977197704MEAN0.0307706327-0.07326716
Mill1977197804MEAN-0.363088377
Mill1977197904MEAN-0.025436865-0.061359594
Mill1977198004MEAN0.19612126330.0156441891
Mill19781978030MEAN-0.043975493
Mill19781979030MEAN0.0273365159-0.07606171
Mill19781980030MEAN0.0349128927-0.033684594
Mill1978198105MEAN0.24624148080.1445191891
Mill1978198201MEAN00.143972972
Mill19791979031MEAN-0.041582573-0.117413127MILL
Mill19791980031MEAN0.18427876610.1422471071
Mill19791981029MEAN0.1464047930.066613682
Mill1979198204MEAN-0.1931803720.1613691891
Mill19801980021MEAN-0.0590992490.0665197451
Mill19801981021MEAN0.17395050.139225909
Mill19801982019MEAN-0.213914002-0.167313541
Mill1980198304MEAN-0.232377421-0.471155811
Mill1980198401MEAN00.076172972
Mill19811981041MEAN-0.076566757-0.181947038
Mill19811982042MEAN0.00325745840.078775909
Mill19811983038MEAN-0.294971615-0.333450383
Mill19811984014MEAN0.05986745410.0521334748
Mill19821982056MEAN-0.087856342-0.129143945
Mill19821983055MEAN-0.074018398-0.129277468
Mill19821984053MEAN0.08580865790.2065012552
Mill1982198505MEAN-0.0136546630.2998991891
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Mill19851985079MEAN0.10338761490.15480341
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Mill19851987074MEAN-0.000435199-0.046606215
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MODELEDGROWTHRATE
00
00
00
00
00
Predicted
00
00
00
00
Predicted
1981
00
00
00
00
Predicted
1982
00
00
00
00
00
Predicted
1983
00
00
00
00
Predicted
1984
00
00
00
00
Predicted
1985
00
00
00
00
Predicted
1986
00
00
00
00
00
Predicted
1987
00
00
00
00
Predicted
1988
00
00
00
00
00
Predicted
00
00
00
00
00
Predicted
1990
00
00
00
00
Predicted
1991
00
00
00
00
00
Predicted
1992
00
00
00
00
Predicted
1994
00
00
00
00
00
Predicted
1995
00
00
00
00
Predicted
1996
00
00
00
00
Predicted
1997
00
00
00
00
Predicted
00
00
00
00
00
Predicted
1978
00
00
00
00
Predicted
1979
00
00
00
00
Predicted
1980
00
00
00
00
Predicted
1981
00
00
00
Predicted
1982
00
00
00
00
Predicted
1983
00
00
00
00
Predicted
1984
00
00
00
00
Predicted
1985
00
00
00
00
Predicted
1986
00
00
00
00
00
Predicted
1987
00
00
00
00
Predicted
1988
00
00
00
00
00
Predicted
1989
00
00
00
00
Predicted
1990
00
00
00
Predicted
1991
Chart1
0.8333333330.8438591269
0.6666666670.596626707
0.9056603770.8659000356
0.9615384620.8592621374
0.7837837840.8494425575
0.8904109590.8326431925
10.8153035899
0.3333333330.8573579599
0.60.834581045
0.850.8761986272
0.40.5302070585
0.7222222220.6783999191
10.7865543135
0.5384615380.6787403856
0.750.7955721504
0.750.7447664222
0.60.652641875
0.9428571430.9539767356
Observed
predicted
Sheet1
GrowthZonebroodyrratio3_totratio4_totratio5_totratio3_no_2predRESIDpred2RESIDbroodyrLengthOceanTotalLengthReturnYrOceanTotalGrowthZoneGROUPyearBPrin1Prin2Prin3Prin4Prin5predRESIDbrood year
319800.750.1500.8333333330.60444785380.2288854792896.9772941217.4227058851978914.431977219773.6110910003-1.370984850.5756061557-0.3593327-0.750534699
319810.60.300.6666666670.56335201010.1033146569896.9772941230.1227058851978927.13197821978
319820.8727272730.09090909100.9056603770.86975389280.0359064842896.9772941242.8227058851978939.831979219791.6128470721-0.4584376181.7295064991-2.0723232931.4636383264
319830.9615384620.03846153800.9615384620.7926701970.168868265896.97729412-7.977294115197888931980219803.1081024303-0.7653210474.97356965980.4908464317-0.373348483
319840.6590909090.18181818200.7837837840.70884284760.0749409364896.97729412-33.377294121978863.63914.4198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.6488238427.7511761651978
319850.8333333330.10256410300.8904109590.73389151790.1565194411896.97729412-33.377294121978863.63927.1198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.6488238440.4511761651978
319860.6923076920010.84083460020.1591653998896.9772941242.8227058851978939.83939.8198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.6488238453.1511761651978
319870.3333333330.50.1666666670.3333333330.7581486773-0.424815344896.97729412-7.97729411519788893889198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.648823842.35117616481978
319880.60.400.60.6638342067-0.063834207896.9772941268.2227058851978965.23863.6198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.64882384-23.048823841978
319890.7391304350.0869565220.0434782610.850.8747640289-0.024764029896.9772941268.2227058851978965.23863.6198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.64882384-23.048823841978
319900.2857142860.42857142900.40.5133631394-0.113363139896.97729412-33.377294121978863.63939.8198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.6488238453.1511761651978
319910.7222222220.27777777800.7222222220.70494942330.0172727987896.97729412-7.97729411519788893889198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.648823842.35117616481978
319920.9230769230010.99152822040.0084717796896.97729412-160.37729411978736.63965.2198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.6488238478.5511761651978
319930.50.42857142900.5384615380.6819552582-0.14349372896.9772941242.8227058851978939.83965.2198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.6488238478.5511761651978
319940.750.2500.750.8715222475-0.121522247896.97729412-33.377294121978863.63863.6198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.64882384-23.048823841978
319950.6666666670.1851851850.0370370370.750.8113213249-0.061321325896.97729412-7.97729411519788893889198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.648823842.35117616481978
319960.5454545450.36363636400.60.6667609713-0.066760971896.9772941217.4227058851978914.43736.6198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.64882384-150.04882381978
319970.8918918920.05405405400.9428571430.87632740070.0665297423896.97729412-7.97729411519788893939.8198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.6488238453.1511761651978
896.97729412-33.377294121978863.63863.6198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.64882384-23.048823841978
896.9772941217.4227058851978914.43889198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.648823842.35117616481978
896.97729412-33.377294121978863.63914.4198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.6488238427.7511761651978
896.97729412-122.27729411978774.73889198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.648823842.35117616481978
896.97729412-109.57729411978787.43863.6198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.64882384-23.048823841978
896.97729412-109.57729411978787.43914.4198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.6488238427.7511761651978
896.9772941268.2227058851978965.23863.6198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.64882384-23.048823841978
918.5839363621.2160636381979939.83774.7198133219813.9024006468-1.4680125511.77458825471.2139847993-0.406521039886.64882384-111.94882381978
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864.45699804-0.8569980391980863.63863.619833321983-3.6826849581.92549775564.5415214923-0.5999048120.6667192177859.574155054.0258449541980
864.45699804-127.8569981980736.631104.919833321983-3.6826849581.92549775564.5415214923-0.5999048120.6667192177859.57415505245.325844951980
864.4569980475.3430019611980939.83660.419833321983-3.6826849581.92549775564.5415214923-0.5999048120.6667192177859.57415505-199.1741551980
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864.45699804-77.056998041980787.43863.619833321983-3.6826849581.92549775564.5415214923-0.5999048120.6667192177859.574155054.0258449541980
864.45699804253.1430019619801117.63736.619833321983-3.6826849581.92549775564.5415214923-0.5999048120.6667192177859.57415505-122.9741551980
815.71307452-53.7130745219817623939.819833321983-3.6826849581.92549775564.5415214923-0.5999048120.6667192177859.5741550580.2258449541980
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