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IMPROVING THE NOAA NMFS

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Title: IMPROVING THE NOAA NMFS


1
IMPROVING THE NOAA NMFS ICCAT ATLANTIC BLUEFIN
TUNA FISHERIES MANAGEMENT DECISION SUPPORT SYSTEM
Mitchell A. Roffer, Ph.D. Roffers Ocean Fishing
Forecasting Service, Inc. West Melbourne,
Florida, U.S.A. (WWW.ROFFS.COM) 321.723.5759
NASA Biodiversity And Ecological Forecasting Team
Meeting, NYC, NY, May 07, 2009
THANK YOU NASA EARTH SCIENCE NASA Grant
NNX08AL06G
2
ADDITIONAL AUTHORS
  • John T. Lamkin - Co-PI (NOAA, NMFS, SEFSC, Miami
    Lab. Miami FL)
  • Frank Muller-Karger - Co-PI (Univ. Mass. SMAST,
    New Bedford, MA /Univ. South Florida IMaRS, St.
    Petersburg, FL)
  • Barbara Muhling (NOAA, NMFS, SEFSC, Miami Lab.
    Miami FL)
  • G. Walter Ingram, Jr. (NOAA, NMFS, SEFSC,
    Pascagoula Lab. Pascagoula, MS)
  • Gregory J. Gawlikowski, Mathew A. Upton, Daniel
    C. Westhaver (Roffers Ocean Fishing Forecasting
    Service, Inc. West Melbourne, FL)
  • Sennai Habtes (Univ. Mass. SMAST, New Bedford,
    MA)

This is a decision support system project with
government managers, academic and industry
partners NOAA 25 days research cruise
500K
3
ATLANTIC BLUEFIN TUNATHUNNUS THYNNUS THYNNUS
  • ONE OF THE WORLDS LARGEST VERTEBRATES (900 KG -
    3 M) WARM BLOODED FISH
  • TRANS-ATLANTIC MIGRATIONS
  • HIGH PRICES IN SUSHI MARKETS (173,688)
  • HIGHLY POLITICAL
  • MANAGED INTERNATIONALLY BY INTERNATIONAL
    COMMISSION FOR THE CONSERVATION OF ATLANTIC TUNAS
    - ICCAT
  • U.S. NOAA NATIONAL MARINE FISHERIES SERVICE
  • RESEARCH AT NMFS, SEFSC, MIAMI, FL

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OVERFISHED
6
STOCK ASSESSMENT
  • VIRTUAL POPULATION ANALYSIS
  • PRIMARILY FISHERY DEPENDENT
  • CATCH/EFFORT qN
  • FISHERY INDEPENDENT DATA TUNES
  • LARVAE SURVEYS
  • EXTENSIVE 1977 - PRESENT
  • AERIAL SURVEYS
  • LIMITED TIME SERIES
  • LIMITED GEOGRAPHICALLY
  • NOT FUNDED EXTENSIVELY
  • ACOUSTIC SURVEYS
  • NONE

7
NMFS SEAMAPICHTHYOPLANKTON SURVEYS
  • 1982 - PRESENT

8
EVER CHANGING WORLD
9
WEEKLY CHL CDOM SST APR. 11- JUNE 11, 2008
NASA MODIS(ROFFS/USF_IMARS)
  • HISTORICALLY THE RESEARCH CRUISE TIME VARIED,
    STATIONS (BONGO OR NEUSTON) VARIED WHICH ADDS TO
    VARIANCE ISSUES

10
CRUISE TIME VARIES
11
BACKGROUND
  • Fishery independent indices of spawning biomass
    of bluefin tuna in western North Atlantic Ocean
    utilize NOAA Fisheries ichthyoplankton survey
    data collected from 1977 through the present in
    the Gulf of Mexico.
  • Indices were developed using similarly
    standardized data from which previous indices
    were developed from water sampled with bongo net
    gear.
  • (i.e. abundance of larvae with a first daily
    otolith increment formed per 100 m2 of water
    sampled).
  • Indices are also developed from standardized data
    collected with neuston gear
  • (i.e. abundance of 5-mm larvae (i.e.
    seven-day-old larvae) per 10 minute tow).

U.S.A. NOAA NMFS SEFSC SCIENTISTS-PARTNERS IN
RESEARCH
12
STATISTICS
  • Fish larvae in many cases are over-dispersed as
    a result of the spawning behavior of adults
    and/or physical oceanographic processes,
    resulting in catch data which is not normally
    distributed.
  • Samples taken from such over-dispersed
    populations contain many small or zero values and
    few very large values.
  • Simple estimates of mean abundance from sample
    data may either be too low, if many low values
    are included, or too high, if very large values
    are included.
  • Such zero-inflated CPUE data is prolific in
    fisheries biology and becoming more important as
    fish stocks decline and rare species become more
    difficult to detect.
  • Great challenge in population assessment of fish
    and others.

13
STATISTICAL MODELS BEING COMPARED FOR BONGO NET
INDICES
  • Delta-lognormal (DL)
  • Zero-inflated delta-lognormal (ZIDL)
  • Multivariate delta-lognormal (MDL)
  • Pennington delta-distribution (PDD)

14
CHALLENGE POPULATION CHANGE DETECTION
  • BONGO NEUSTON NET INDICES
  • COEFFICENT OF VARIATION
  • STANDARD ERROR DIVIDED BY THE MEAN
  • 100 OF THE MEAN AND LARGER

15
NEUSTON
16
MULTIVARIATE INDICES
  • RANGE OF COEFFICIENT OF VARIATION

17
LARVAE SURVEY IS THE ONLY FISHERY INDEPENDENT
DATA SOURCE OVER ANY CONSIDERABLE TIME PERIOD
  • LARGE ERROR DERIVED FROM RELATIVELY SMALL SAMPLE
    SIZES, AND AN INCREASED FREQUENCY OF ZERO CATCH
    STATIONS IN RECENT YEARS
  • THE LARVAE INDICES ARE USED IN THE INTERNATIONAL
    STOCK ASSESSMENT AND MANAGEMENT.
  • THE INDICES ARE THE ONLY TOOL THAT INCORPORATES
    THE FISHERY-INDEPENDENT ESTIMATES OF ABUNDANCE,
    AND THEY ARE CONSISTENT WITH RESULTS OF THE
    VIRTUAL POPULATION ANALYSES

18
NOT TRIVIAL
  • DO WE CONTINUE THESE SURVEYS?
  • SHIP TIME COST gt350K
  • IN THE SAME MANNER?
  • ARE THERE A BETTER WAYS?
  • DIFFERENT SAMPLING
  • TARGETED SAMPLING ADAPTED TO THE OCEAN
    CONDITIONS
  • INCREASE NUMBER OF LARVAE, REDUCE THE VARIANCE BY
    LEARNING THEIR LOCATION, OBJECTIVE REDUCTION OF
    ZERO CATCHES
  • SAME SAMPLING BUT ADVANCED STATISTICS
  • USE ACOUSTIC SURVEYS OF ADULTS

19
DO THEM ALL
  • REDUCE THE VARIANCE
  • OBJECTIVELY REMOVE ZERO CATCHES
  • DEVELOP A PREFERRED HABITAT MODEL
  • WATER TEMPERATURE, SALINITY, THERMOCLINE
  • CHLOROPHYLL, FRONTAL BOUNDARIES
  • STATIONS THAT ARE NOT WITHIN THE PREFERRED
    HABITAT WILL BE DROPPED
  • CATCH MORE LARVAE
  • LEARN WHERE THEY EXIST
  • USE INNOVATIVE STATISTICAL TECHNIQUES
  • DEVELOP CATCHABILITY INDICES FOR LARVAE WITHIN
    THE PREFERRED HABITAT
  • ENSEMBLE MODELS

20
91 of bluefin larvae found where SST is between
23.5 and 27.5C. 98 of larvae found where
temperature at 200m is less than or 20C.
Total stations sampled (1982 to
2004) 2031 Total stations with favorable
habitat 1390 Total stations with unfavorable
habitat 641 Environmental data correctly
predicts bluefin 23 Environmental data
correctly predicts no bluefin 93
WE CAN PREDICT WHERE LARVAE WILL NOT BE, BUT NOT
SO MUCH WHERE THEY WILL BE gt FIRST STEP TO
REMOVING ZERO LARVAE
21
PREDICTING PRESENCE
22
OTHER IMPORTANT ITEMS OCEAN CONVERGENCE ZONES
  • 1) LOCATION AND TIME HISTORY
  • 2) FRONTAL GRADIENT STRENGTH SST AND
    CHLOROPHYLL.
  • 3) SPATIAL COHERENCE OF FRONTS.
  • 4) LOCATION OF THE AXIS AND NORTHERN PENETRATION
    OF THE LOOP CURRENT.
  • 5) NUMBERS OF EDDIES THAT OCCUR IN THE STUDY
    AREA.
  • 6) TYPE OF EDDY (WIDTH, LENGTH, AREA, VELOCITY).
  • 7) SST AND CHLOROPHYLL INSIDE THE EDDIES.

23
2008 FIELD CAMPAIGN
  • TARGETED ADAPTIVE SAMPLING

24
  • ADAPTIVE SAMPLING ATLANTIC BLUEFIN TUNA LARVAE -
    ROFFS/NMFS/UMASS
  • Two areas were identified as potential sampling
    sites one to the west of a warm Loop Current
    eddy, and one between the Loop Current and the
    eastern boundary of the eddy.
  • We decided on the latter, as the oceanography was
    more dynamic, and concentration and enrichment
    processes were more likely to continue to occur
    throughout sampling.
  • Eight transects containing 70 stations were
    sampled with bongo and neuston nets, and CTDs

25
2008 TARGETED ADAPTIVE SAMPLING
  • 4M

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06 MAY 2008 08127 STATIONS
?
28
07 MAY 2008 08128 STATIONS FRONTS
29
MAY 06, 2008 ON FRONT
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SEQUENTIAL IMAGE ANALYSIS TO LOCATE DRIFT PATHS
33
THREE YEAR METRICS
  • NMFS ROUTINELY USE REMOTE SENSING DATA AS PART OF
    DECISION SUPPORT SYSTEM
  • REDUCE COEFFIENT OF VARIANCE 50 OF MEAN
  • INCREASED SHIP TIME
  • CATCH MORE BLUEFIN LARVAE
  • USE OF SATELLITE DATA IN OTHER STOCK ASSESSMENTS
    AND RESEARCH
  • INDICATIONS YES (E.G. ABT MED, MEXICO REEF FISH)
  • INCREASED USE BY OTHER SCIENTISTS
  • NOAA_AOML UNIV. MIAMI FL FISH WILDLIFE
  • MEETING JUNE 01, 2009 NOAA_AOML AND NOAA_NMFS
  • UNIV. SOUTHERN MISSISSIPPI

34
2009 SAMPLING
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21-23 APRIL 2009
38
AQUA/MODIS CHLCDOM
  • APR 21, 09

39
DAILY REVIEW
APR. 23, 2009
APR. 21, 2009
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WORK CONTINUES
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