American Samoa Commercial Fisheries Biosampling Program

Rose AtollManu’a

Tutuila

Independent Samoa

Vailulu’uSeamount Tongan Trench

The Samoan Archipelago

Congress funds NMFS to expand data requirements consistent with Magnuson-Stevens Act

Fisheries Science initiatives has funded Commercial Fish Biosampling

Goals of Biosampling: (1) to obtain life history data (2) size and age-specific population structure; (3) stock identity data

Philosophy: (1) non-aggressive; (2) minimal impact; (3) non-competitive

Background

U.S. Department of Commerce| National Oceanic and Atmospheric Administration |NOAA Fisheries | Page 5

Stock Assessment computer model:Pounds of fish next yr =

Pounds of fish this yr + Recruits + Growth – Death (natural fishery)

ABUNDANCE• Fishery data

(CPUE)• Non-fishery data

BIOLOGY• Includes life

history

CATCH• Commercial• Recreational• Subsistence

How many fish can we catch next year, based on the biology of the fish?Stock assessment also describes current and past abundance & stock status.

Challenges of AS creel programs Very limited species level identification Limited staff capacity for species ID, management

issues Creel survey protocol implementation issues ‘Representative’ sampling issues Low fisheries participation, esp. night spearfishing L-W coefficients were not AS specific Very limited life history data collections, analyses

A.

Age (years)

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Fork

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Model coral reef fishes

Acanthurus nigricans / A. Samoa: sex-specific Von Bertalanffy growth model

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Age (years)

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VB parameters: Females: n = 318, Linf = 169.6, K = 1.14, to = -0.165Males: n = 174, Linf = 163.2, K = 1.19, to = -0.165

Ctenochaetus striatus

Acanthurus nigricans

Life History Data for pone Ctenochaetus striatus

Lab Biosampling provides life history data such as growth rate, longevity, timing of spawning and length-at-first maturity.

a. Recruits

Substratum Regression

coefficient (β)

p

Rubble 0.32 <0.01*

b. Juveniles

Substratum Regression

coefficient (β)

p

Algae - 0.26 <0.05*

c. Adults

Substratum Regression

coefficient (β)

p

Coralline Algae 0.27 < 0.05*

Relationship between the abundance of (a) recruits, (b) juvenile, (c) adult and percent cover of each substratum type.

Recruits Juveniles Adults

Recruits -

Juveniles 0.17 -

Adults -0.23* -0.03

Spearman rank correlation analysis of the Ctenocheatusstriatus size categories. Significant correlations are highlighted in bold (p < 0.05).

Size and Age Data for Cephalopholis urodeta

(Ochavillo et al., in prep)

0.00

2.00

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Ofu-Olosega Tau Tutuila

Islands

Age

(yea

rs)

Cephalopholis urodeta

0102030405060708090

100110120130140150160170180190200210220230240250260

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18

Age

Tota

l len

gth Female

Female VBGFMaleMale VBGF

Fast early growth, asymptotic

Relatively low longevity

Inter-island demographic differences

Hire and capacitate a staff member to identify the catch to species level

Develop and field-test logistics to collect length-and-weight-data from commercial fisheries (Field Biosampling)

Develop a protocol for collecting and processing otolith, gonads and fin clips (Lab Biosampling)

Regularly evaluate lessons learned and make recommendations for improvement

Objectives of Biosampling

Biosampling Program Timeline August 2009, the PIFSC and the Council organized a

biosampling workshop at the Guam Fisherman’s Co-op Association (GFCA) in Hagatna, Guam.

In an October 2010 workshop held at the LHP Lab in Aiea, Hawaii

Biosamplers in American Samoa began regular sampling of reef and bottom fish at the FagatogoMarket in Pago Pago, October 2010

In Feb-March 2012, fish ID workshop in Bishop Museum

Milestones We have 7 DMWR staff trained to identify fish

species ID of catch

We work with 15 spearfishermen, 6 bottomfishingboats, and 2 handlining fishermen.

Measured over 216,000 fish lengths, over 209,000 lbs fish

Collected almost almost 4,000 otoliths and gonads from 10 fish species for life-history data; and over 200 fin slips for barcode of life project.

Collected AS specific L-W coefficients

Species level fish catch summaries

Protocol (Field Biosampling) For spearfishing, sampling was conducted bet 4 to 7

AM For bottomfishing, sched is more variable Saturdays is always covered Each fisherman is the sampling unit Separated trolling vs bottomfishing in mixed fishing Each fish and inverts ID to species and measured Staff used audio recorders, recoded to computer Audio files are archived following PIFSC protocols Ice supplied, documentation

Protocol Fish and inverts measured to nearest cm For octopus-head length; for lobsters-carapace length L-W measurements; eventually L only if ‘enough’ data Data entry/management customized PIFSC-WestPACFIN maintained software, database,

support Field Biosampling Database and Lab Biosampling

Database Labeling, preservation, and archival protocols for

extracted gonads and otoliths

Lab Protocol (Lab Biosampling) Species, length, weight, sex, gonad weight, tag Specimen labeled (A=American Samoa, 3 letters for

tech name, sequence number) Visual gonad categorization (male, female, unid) Gonad weight to 0.01 g X-section of central gonad or whole gonad preserved Sagittae otoliths extracted (2, 1.5, 1, 0.5, 0 categories) Otoliths stored in vials with cotton balls Targeted 20 specimens per species per month Target sizes: sizes represented; opportunistic on large

sizes; small sizes from focused collections

Lab Protocol (Fin clips) 5 specimen per species Fishing ground, length, weight 2 digital photos taken from each specimen Photo taken with fish atop measuring board Fish facing left Fins spread as much as possible Specimen labeled following protocols (A=American

Samoa, 3 letters for tech name, sequence number)

Life history species for AS Lethrinus xanthochilus Lethrinus rufolineatus Lutjanus gibbus Myripristis berndti Myripristis amaena Myripristis murdjan Naso unicornis Sargocentron spiniferum Sargocentron tiere Scarus rubroviolaceus Criteria: Top species landing, preference, available size

ranges

What Biosampling Data Are Collected:

Name of fishermanDateArea fishedNumber of hours fishingCar or boat?How many fisherman in boatHow much bait used (bottomfishing)How much fuel usedHow much ice (supplied)All species (length, weight)Gonads and otoliths of target species

Top fish species caught (number) by commercial spearfishing

Species Total %1 Acanthurus lineatus 79,305 54.92 Ctenochaetus striatus 6,554 4.53 Naso lituratus 5,573 3.94 Sargocentron tiere 5,300 3.75 Chlorurus japanensis 4,555 3.26 Naso unicornis 3,563 2.57 Scarus rubroviolaceus 3,179 2.28 Panulirus pencillatus 2,975 2.19 Scarus oviceps 2,590 1.8

10 Myripristis berndti 2,177 1.511 Acanthurus nigricans 2,153 1.512 Epinephelus melanostigma 1,674 1.213 Myripristis amaena 1,664 1.214 Acanthurus guttatus 1,662 1.115 Panulirus sp. 1,648 1.1

species %1 Acanthurus lineatus 28.32 Parrotfishes 25.33 Ctenochaetus striatus 8.94 Unicornfishes 7.65 Panulirus penicillatus 6.26 Reef fishes (unknown) 6.07 Inshore groupers 4.58 Squirrelfishes 2.89 Acanthurus xanthopterus 2.2

10 Acanthurus nigrofuscus 0.711 Naso lituratus 0.6

Creel SurveyBiosampling

Top fish species caught (number) by commercial bottomfishing

Species Grand Total %1 Lutjanus kasmira 5558 27.1 2 Lethrinus rubrioperculatus 4102 20.0 3 Lethrinus xanthochilus 1974 9.6 4 Lutjanus gibbus 1879 9.2 5 Aprion virescens 865 4.2 6 Variola albimarginata 821 4.0 7 Lutjanus rufolineatus 529 2.6 8 Lethrinus harak 302 1.5 9 Sphyraena forsteri 280 1.4

10 Lethrinus amboinensis 229 1.1 11 Pristipomoides flavipinnis 225 1.1 12 Sargocentron spiniferum 191 0.9 13 Aphareus rutilans 173 0.8 14 Lutjanus fulvus 170 0.8 15 Lutjanus monostigma 166 0.8

Species Pounds Price/Lb. Value

BMUS

Blue lined snapper 427 $2.73 $1166

Ruby snapper (ehu) 374 $4.41 $1649

Flower snapper (gindai) 41 $2.75 $113

Gray jobfish 200 $3.42 $684

Pink snapper (opakapaka) 265 $3.02 $802

Silverjaw jobfish (lehi) 71 $3.37 $240

Longtail snapper (onaga) 146 $2.82 $412

Goldflag jobfish 51 $3.70 $188

Yellow-edged lyretail 3 $3.00 $9

Redgill emperor 389 $3.40 $1323

Black jack 79 $2.94 $231

Giant trevally 18 $3.50 $64

BMUS SUBTOTALS 2064 $3.33 $6882

OTHER

Bottomfishes (unknown) 10987 $2.88 $31695

Yellow margined snapper 8 $3.75 $28

Brown jobfish 33 $2.95 $99

Humpback snapper 975 $3.44 $3356

Onespot snapper 117 $3.75 $438

Twinspot/red snapper 44 $2.95 $130

Groupers 125 $3.27 $409

Flagtail grouper 2 $3.75 $7

Peacock grouper 20 $3.75 $74

Emperors 1059 $3.70 $3918

Species Weight SummariesSpeciesName Total (lbs)

1 Acanthurus lineatus 101,856

2 Scarus rubroviolaceus 9,026

3 Naso unicornis 8,005

4 Chlorurus japanensis 5,666

5 Naso lituratus 4,612

6 Panulirus pencillatus 4,293

7 Lethrinus xanthochilus 3,948

8 Lethrinus rubrioperculatus 3,706

9 Ctenochaetus striatus 3,575

10 Aprion virescens 3,281

11 Panulirus sp. 3,160

12 Lutjanus gibbus 3,133

13 Lutjanus kasmira 2,633

14 Scarus oviceps 2,473

15 Chlorurus microrhinos 1,924

16 Sargocentron tiere 1,912

17 Epinephelus melanostigma 1,662

18 Scarus frenatus 1,549

19 Actinopyga mauritiana 1,398

20 Acanthurus xanthopterus 1,314

Sargocentron tiereFish Sampled in American Samoa March 2011-January 2013

AirportAloauAmouliAuasiAunuu

Avau-NuuuliFagaaluFagasaFailoloFogagogoLauliiMasefauTulaVaitogi

Distinct spear fishing areas

Multivariate statistical analyses of fish species assemblages indicated that these are highly distinct fishing grounds.

TaputapuAunuuFagaaluLauliiTula

Distinct bottomfishing areas

Multivariate statistical analyses of fish species assemblages indicated that these are highly distinct fishing grounds.

"Var1"; LS MeansWilks lambda=.37655, F(104, 1381.3)=2.0240, p=.00000

Effective hypothesis decompositionVertical bars denote 0.95 confidence intervals

AirportAloau

AmouliAuasi

AunuuAvau-Nuuuli

FagaaluFagasa

FailoloFogagogo

LauliiMasefau

TulaVaitogi

Var1

-2

-1

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1

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uliru

s pe

nici

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"Var1"; LS MeansWilks lambda=.37655, F(104, 1381.3)=2.0240, p=.00000

Effective hypothesis decompositionVertical bars denote 0.95 confidence intervals

AirportAloau

AmouliAuasi

AunuuAvau-Nuuuli

FagaaluFagasa

FailoloFogagogo

LauliiMasefau

TulaVaitogi

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"Var1"; LS MeansWilks lambda=.37655, F(104, 1381.3)=2.0240, p=.00000

Effective hypothesis decompositionVertical bars denote 0.95 confidence intervals

AirportAloau

AmouliAuasi

AunuuAvau-Nuuuli

FagaaluFagasa

FailoloFogagogo

LauliiMasefau

TulaVaitogi

Var1

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Biosampling statistics

Coral reef fishery stock assessmentWhat are the exploitation rates for various species?

Species mean length k maximum min Lmax Linfinity M ZExploitati

on

(cm) age (yrs) Rate (%)

Acanthurus lineatus 19 0.7 18 10 22 25 0.23 0.42 44.2

Acanthurus nigricans 17.5 1.7 25 10 24 26 0.17 1.34 87.4

Ctenochaetus striatus 18 0.9 34 10 17 22 0.12 0.45 72.4

Chlorurus microrhinos 36.6 0.3 17 18 59 65 0.25 0.38 35.0

Scarus rubroviolaceus 34.8 0.59 8 21.5 55 61 0.53 1.00 47.3

Naso unicornis 34.7 0.49 30 17 83.5 90 0.14 1.50 90.6

Size limits can also be derived from yield-per-recruit analyses using M, k, lc, Linf.

Issues and Challenges Biosampling was too successful but filled a gnawing

data gap Competed with existing creel program, highlighted

deficiencies of existing creel Unsustainable, need to explore sustainability Needed regular review Data quality issues (some expected): gonad IDs, length

discrepancies, species IDs Accumulated a lot of high quality data that remain

unanalyzed

Issues and Challenges Biosampling succeeded based on its objectives Biosampling eventually filled in on some other

objectives: Attempt to integrate it to existing creel Data is now used for data-poor methods such as PSA Length-based assessment is largely unexplored but

precedented Data could be used to independently corroborate

existing creel survey data

Fa’afaetai tele lava!

David Hamm and Kimberly Lowe, and staffNOAA Pacific Islands Fisheries Science Center

Bob Humphries

Dr. Ruth Matagi-Tofiga, Director DMWR

TeeJay Letalie, Auvaa Soonaolo, Poasa TofaeonoAlama Tua, Ekueta Schuster, Faleselau Tuilagi

Numerous fishermen who have supported BiosamplingMamani and Talavou

Scientific/Technical Do the laboratory and market sampling programs apply an

appropriate suite of methods to sample collection and analysis? Yes

Are the sample collection and analytical processes of the laboratory sampling program peer-reviewed, efficient, effective and clearly described? The samples collection for the life history could be improved.

Are the territorial field and laboratory teams appropriately trained in the skills necessary for executing the program protocols? Yes. The field ID of gonad sex was expected to be fraught esp for sex-changers. But the histo would correct this.

How are the species collected for life history determined? Are those species appropriate for management purposes? DMWR proposed the species based on criteria.

Data Are the data collection protocols clearly articulated, streamlined,

efficient and appropriate to the data collected? Are there improvements that could be effectively implemented within current resources? For Field Biosampling: it was not clear at what point data was enough. For Lab Biosampling: the size collection probably needed some guidance. For Fin Clips: could be more focused perhaps on problematic species identifications.

Do data confidentiality concerns exist and how are they accommodated? Are data review, quality control, data integrity, transparency, confidentiality, and PII, etc. treated appropriately? This needs improvement. Data review irregular, data quality control could be more improved although program included some flags.

What fisheries management research questions are the data being collected for? Are the samples collected and the analytical process used relevant to the management or research questions being asked? Is the data collection appropriately designed to meet the management needs? Objectives were met but management research questions were not inclusive at the onset.

Communication Are effective working relationships in place with vendors

and fishermen so that staff are able to obtain access to measure and take samples of fish at the landing sites and at vendor sites? Yes, definitely.

Is the communication between, territorial and federal bio-sampling staff effective and at the appropriate level to meeting the needs of territorial and federal mandates? Communication needs to be improved, lapses most probably due to heavy workload of agencies involved.

Are the results of the bio-sampling work communicated to stakeholders and the public? Very limited.

Opportunities Are there existing opportunities for leveraging that

should be pursued but are not currently? E.g., data management systems, training opportunities? The Biosampling Program generated a lot of data that are still unexplored: (a) length-based stock assessment; (b) spatial analyses of CPUE and identifying environmental correlates to coral reef productivity; (c) analyses to determine ‘effective’ sampling; (d) independent corroboration of creel survey data.

Questions to Territorial Agencies Describe your agency’s fisheries management mandates. Assessment of

fisheries and stock status and habitats; catch and size limits What are your agency’s management and monitoring priorities around

meeting those mandates? Creel survey programs and habitat monitoring programs; stock assessments in collaboration with federal agencies; limited resources for life-history projects.

How does the bio-sampling program support those priorities? L-W coeffficients, life-history data (size at maturity, average length, longevity, etc.); average length data

Does the agency currently use data collected in the bio-sampling program and how are those data used? The data are most utilized in data-poor assessments such as PSA at the moment. We expect more data analyses in the future.

Describe your agency’s process or participation in the selection of priority species. We collaborated with PIFSC in species selection.

Describe your agency’s activities, role, and technical capacity in the scientific/technical and data management/analysis aspects of the bio-sampling program, e.g., collecting data, quality control, logistics, man-hours. Activities mainly focused in communicating with fishermen, field sampling, gonad and otolith extraction, data encoding, data quality control, logistics. We expect to be more involved in gonad histology analyses and foresee collaboration in analytics.