Age and Growth of Pacific Sardine in California During a Period of Stock Recovery and Geographical Expansion By Emmanis Dorval Jenny McDaniel Southwest.

Slides:



Advertisements
Similar presentations
Modeling Recruitment in Stock Synthesis
Advertisements

Detecting changes in von Bertalanffy growth parameters (K, L ∞ ) in a hypothetical fish stock subject to size-selective fishing Otoliths (ear bones) from.
Science Behind Sustainable Seafood Age Matters! Alaska Fisheries Science Center.
  Multiple years of sampling to mark and recapture individuals completed between 2006 and 2008   Despite significant effort, population estimates were.
Sheng-Ping Wang 1,2, Mark Maunder 2, and Alexandre Aires-Da-Silva 2 1.National Taiwan Ocean University 2.Inter-American Tropical Tuna Commission.
1 Ecological and Economic Considerations in Management of the U.S. Pacific sardine Fishery Samuel F. Herrick Jr NOAA Fisheries Southwest Fisheries Science.
Spatial and temporal variability in Atka mackerel (Pleurogrammus monopterygius) female maturity at length and age. A component of NPRB project 0522: Reproductive.
An Overview of the Key Issues to be Discussed Relating to South African Sardine MARAM International Stock Assessment Workshop 1 st December 2014 Carryn.
Determining relative selectivity of the gulf menhaden commercial fishery and fishery independent gill net data Southeast Fisheries Science Center Amy M.
Growth in Age-Structured Stock Assessment Models R.I.C. Chris Francis CAPAM Growth Workshop, La Jolla, November 3-7, 2014.
C3: Estimation of size-transition matrices with and without molt probability for Alaska golden king crab using tag–recapture data M.S.M. Siddeek, J. Zheng,
FMSP stock assessment tools Training Workshop LFDA Theory.
The current status of fisheries stock assessment Mark Maunder Inter-American Tropical Tuna Commission (IATTC) Center for the Advancement of Population.
Stock Structure of Pacific Sardine (Sardinops sagax), an ongoing question John R. Hyde Southwest Fisheries Science Center, La Jolla.
Sardine: a fable of six blind men and two elephants Paul E. Smith NOAA-Fisheries Southwest Fisheries Science Center, La Jolla, California CMD La Jolla.
Case Study - Dover Sole Range from Baja California to the Bering Sea. On mud or muddy-sand, at 35 to 1400 m depths. Feed on polychaete worms, shrimp, brittle.
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,
How many conditional age-at-length data are needed to estimate growth in stock assessment models? Xi He, John C. Field, Donald E. Pearson, and Lyndsey.
Recruitment success and variability in marine fish populations: Does age-truncation matter? Sarah Ann Siedlak 1, John Wiedenmann 2 1 University of Miami,
Fishery Management Fishing is extractive – Removes choices organisms- “ fine-ing ” – Changes food web structure The human condition provides little incentive.
Revisiting Stock-Recruitment Relationships Rainer Froese Mini-workshop on Fisheries: Ecology, Economics and Policy CAU, Kiel, Germany.
Methods: Collection of Blue Catfish Otoliths
Gary D. Marty 1, Peter-John F. Hulson 2, Sara E. Miller 2, Terrance J. Quinn II 2, Steve D. Moffitt 3, Richard A. Merizon 3 1 School of Veterinary Medicine,
Maximum likelihood estimates of North Pacific albacore tuna ( Thunnus alalunga ) von Bertalanffy growth parameters using conditional-age-at-length data.
ASSESSMENT OF BIGEYE TUNA (THUNNUS OBESUS) IN THE EASTERN PACIFIC OCEAN January 1975 – December 2006.
Use of multiple selectivity patterns as a proxy for spatial structure Felipe Hurtado-Ferro 1, André E. Punt 1 & Kevin T. Hill 2 1 University of Washington,
Lecture 4 review Most stock-recruitment data sets show the pattern predicted by Beverton and Holt when they assumed cohorts die off at rates dN/dt=-MN,
Guidance for modelling the variability of length-at-age: lessons from datasets with no aging error C.V. Minte-Vera (1)*, S. Campana (2), M. Maunder (1)
Revisiting the SSC Decision to Use all Available Data to Calculate Average Landings/OFLs/ABCs Southeast Fisheries Science Center.
FTP Yield per recruit models. 2 Objectives Since maximizing effort does not maximize catch, the question is if there is an optimum fishing rate that would.
Kevin T. Hill Fisheries Resources Division Southwest Fisheries Science Center.
GIANNOULAKI M., SOMARAKIS S., MACHIAS A., SIAPATIS A., PAPACONSTANTINOU C. Hellenic Centre for Marine Research, PO Box 2214, Iraklion 71003, Greece Department.
USING INDICATORS OF STOCK STATUS WHEN TRADITIONAL REFERENCE POINTS ARE NOT AVAILABLE: EVALUATION AND APPLICATION TO SKIPJACK TUNA IN THE EASTERN PACIFIC.
Fisheries 101: Modeling and assessments to achieve sustainability Training Module July 2013.
TRINATIONAL SARDINE FORUM Since th ANNUAL MEETING Otolith workshop Sumner Auditorium,SIO TPC, Southwest Fisheries Science Center La Jolla, California,
Flexible estimation of growth transition matrices: pdf parameters as non-linear functions of body length Richard McGarvey and John Feenstra CAPAM Workshop,
An MSE for Pacific Sardine Lecture 15. Fisheries Management (or what goes up must…) 2 Murphy (1966) & Hill et al. (2009)
Supplementation using steelhead fry: performance, interactions with natural steelhead, & effect of enriched hatchery environments Christopher P. Tatara.
Regional differences in Pacific sardine populations determined by otolith morphology Barbara Javor, SWFSC.
M.S.M. Siddeeka*, J. Zhenga, A.E. Puntb, and D. Pengillya
Ecosystem Approach and Assessment of Small Pelagic Fisheries in the Mediterranean Sea MariFish 7 th Work Package Meeting Athens, February Designs.
West Atlantic bluefin tuna Executive Summary. Biology Continued progress in knowledge of bluefin biology, but the complex behaviour of this species means.
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.
Citizen Science as an Integral Component of Reef Fish Research and Monitoring Efforts Along Florida's Atlantic Coast Justin J. Solomon, Russell G. Brodie,
Atlantic bluefin tuna Two management units since 1981 Complex spatial dynamics with mixing between both stocks (investigated by BFT-SG since 2001) Spatial.
1 Federal Research Centre for Fisheries Institute for Sea Fisheries, Hamburg Hans-Joachim Rätz Josep Lloret Institut de Ciències del Mar, Barcelona Long-term.
Analysis of flathead catfish population parameters using spine versus otolith age data Jeffrey C. Jolley, Peter C. Sakaris, and Elise R. Irwin Alabama.
Using distributions of likelihoods to diagnose parameter misspecification of integrated stock assessment models Jiangfeng Zhu * Shanghai Ocean University,
Proposed Regulations for the Commercial Herring Fishery Proposed Regulations for the Commercial Herring Fishery Presented by The Department.
CAN DIAGNOSTIC TESTS HELP IDENTIFY WHAT MODEL STRUCTURE IS MISSPECIFIED? Felipe Carvalho 1, Mark N. Maunder 2,3, Yi-Jay Chang 1, Kevin R. Piner 4, Andre.
Incorporation of Climate-Ocean Information in Short- and Medium Term Sprat Predictions in the Baltic Sea Acknowledgements: ICES Baltic Fish. Assess. WG.
Empirical comparison of historical data and age- structured assessment models for Prince William Sound and Sitka Sound Pacific herring Peter-John F. Hulson,
Market Squid Fishery Management Plan CA Department of Fish and Game December 15, 2011 Fish and Game Commission.
CBSAC 2012 Blue Crab Advisory Report Figures. Figure 1. Winter dredge survey index of total blue crab abundance (density of males and females, all sizes.
PARTICIPANTS NCMR (Responsible Institute), IMBC [Greece] IREPA[Italy] U. Barcelona, U. Basque, UPO[Spain] EFIMAS MEETING NICOSIA CRETE 2004 APRIL
For 2014 Show the line of R producing SSB, and SSB producing R, and how they would spiderweb to get to equilibrium R. Took a long time, did not get to.
Data requirement of stock assessment. Data used in stock assessments can be classified as fishery-dependent data or fishery-independent data. Fishery-dependent.
Population Dynamics and Stock Assessment of Red King Crab in Bristol Bay, Alaska Jie Zheng Alaska Department of Fish and Game Juneau, Alaska, USA.
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.
Time of Death: Modeling Time-varying Natural Mortality in Fish Populations Phil Ganz 1 Terrance Quinn II 1 Peter Hulson 2 1 Juneau Center, School of Fisheries.
Proposed Regulations for the Commercial Herring Fishery Proposed Regulations for the Commercial Herring Fishery Presented by the Department.
PRINCIPLES OF STOCK ASSESSMENT. Aims of stock assessment The overall aim of fisheries science is to provide information to managers on the state and life.
Fish stock assessment Prof. Dr. Sahar Mehanna National Institute of Oceanography and Fisheries Fish population Dynamics Lab November,
Matthew Donaldson , and J. Read Hendon
Sardine Two-Stock Hypothesis: Results at the Posterior Mode
An MSE for Pacific Sardine
NMFS Report SWFSC Activities Coastal Pelagic Species
Age and Growth in Fishes
Models used for stock recruits and parent stock
BIOMASS PER RECRUIT MODEL
Presentation transcript:

Age and Growth of Pacific Sardine in California During a Period of Stock Recovery and Geographical Expansion By Emmanis Dorval Jenny McDaniel Southwest Fisheries Science Center Dianna Porzio California Department of Fish and Game

Pacific Sardine Sardinop sagax

Background Patterns of individual fish growth rate After population decline: o Following low population level due to exploitation (or to other events), individual fish growth rate is expected to increase (Le Cren et al. 1972, Botsford 1981). o Following low population level, individual fish growth rate may be several times higher than normal growth rate (i.e., pre-decline or pre-exploitation level ), Le Cren et al. (1972).

Background Patterns of individual fish growth rate After population rebuilding: o Individual fish growth rate is generally expected to decline toward normal growth rate (i.e., pre-decline or pre- exploitation level ). o However, the extent of this decline may depend on the strength of regulating factors that are in play; and/or on how much the environment/habitat of this species been modified compared to pre-decline or pre-exploitation level.

Background Patterns of individual sardine growth rate In the historical fishery ( ): o Length-at-first annulus formation: 101 – 131 mm (Marr 1960) During the recovery of the stock (1990s – 2000s) o Butler et al. (1996) o Hill et al. (2007, 2009, 2011)

Background Patterns of individual sardine growth rate P. sardine growth curve Butler et (1996) Fish samples o Daily Egg Production Method (DEPM): April - May 1994 o Ensenada fishery landings Von Bertallanfy growth model o L ∞ = ± 1.6 o k = 1.19 ± 0.04 o t 0 = 0 (fixed ) Birthdate: January 1

Background Patterns of individual sardine growth rate P. Sardine growth curve Hill et al. (2011) Fish samples o Daily Egg Production Method (DEPM): April – May: o Ensenada/California fishery landings: o Pacific Northwest fishery landings: Birthdate: July 1 L 0.5yr = 114 mm L ∞ = 242 mm k = 0.364

Background Sardine growth rate: current issues o Density -dependent changes in growth rates or reproduction have not been identified nor evaluated (Hill et al. 2011). o Combining fishery-dependent and fishery-independent data may not be the most reliable way to detect density-dependent. o A single growth model is derived in stock assessment model and applied to all fisheries (i.e., Ensenada and/or California, Pacific Northwest). o There are no known aged-fish: it is difficult to estimate age-reading bias and imprecision from multiple readings of otoliths.

Research Objectives Develop methods to estimate and compare growth rates in the California spawning stock: o During the recovery of the stock in California (1980s-1990s). o During the recovery and expansion of the stock from California into the Pacific Northwest and British Columbia (1990s – present). Determine how fish migration and fishing development may affect sardine growth rate in the California spawning stock.

Methods Sample collection o DEPM April survey: o California: San Diego – San Francisco Age estimation o Annual increment from whole otolith, i.e. unpolished otolith, Yaremko (1996) o Birthdate assumption: July 1 o Age-readers: 3

Methods

Methods Growth model o Von Bertalanffy growth model (Beverton and Holt, 1954) o Maximum likelihood estimation of parameters o Mixed-effect model Lt ~ Age | Reader L ∞ (random factor ) k (fixed factor) t 0 (random factor)

Methods Age-1 + sardine biomass Growth comparison between: Year-classes: Year-classes:

Preliminary results Butler et al Least-squares based model (Reader best ages) L ∞ = mm k = 1.19 t 0 = 0 (fixed)

Preliminary results Least-squares based model (Reader best ages) Mixed -effect model Length ~Age | Reader L ∞ =283 mm ± 9 k=0.22 ± 0.01 t 0 = ± 0.5 L ∞ = 328 mm k = 0.14 t 0 = -3.13

Preliminary results Mixed effect model Length ~Age | Reader Mixed -effect model Length ~ Age | Reader L ∞ =263 mm ± 10 k =0.26 ± 0.01 t 0 = -3.11± 0.68 L ∞ =294 mm ± 10 k =0.19 ± 0.01 t 0 = ± 1.31

Summary Compared to previous study, i.e. Butler et al. (1996), sardine growth rate in the spawning stock appears to have decreased. However, early age and growth data may need to be re-analyzed so that comparison can be based on most recent age-reading and statistical methods. Growth rate of sardine in the and in the year-classes are significantly different. However, comparison of these year-classes may need to be based on data that include similar age-classes.

Summary We will continue to age our historical sardine otolith samples to address these concerns. We will include age-reading errors in future models, so that all model assumptions can be met.

Acknowledgement This study is an ongoing research collaboration project between the California Department of Fish and Game (CDFG) and the Southwest Fisheries Science Center (SWFSC). We thank all CDFG staff that participated in the age-reading of sardine otoliths, specially Valerie Taylor. We tank all SWFSC staff that participated in the collection and management of sardine otolith samples, specially Beverly Macewicz.