spatial and temporal variability in atka mackerel (pleurogrammus monopterygius) female maturity at...

Spatial and temporal variability in Atka mackerel (Pleurogrammus

monopterygius) female maturity at length and age.

A component of NPRB project 0522: Reproductive ecology of Atka mackerel, Pleurogrammus

monopterygius, in Alaska.

Daniel Cooper and Susanne McDermott Fisheries Interaction

Team (FIT), AFSCJames Ianelli, AFSC, SSMA

Introduction

• Maturity at age/length used to estimate spawning biomass

• Maturity varies temporally and spatially in some other species– Growth differences

• Temperature• Population density

– Decreases caused by fishing pressure

• Maturity estimates in ecological studies

Introduction – Atka mackerel maturity

• Previous Atka mackerel maturity estimates (McDermott and Lowe 1997)– Maturity at age constant (Age 50% maturity ~3.6

years– Maturity at length decreases from East to West– Atka mackerel growth decreases from East to West– Growth differences hypothesized to explain spatial

maturity differences

• Temporal maturity variability unknown• Some strong year classes

Questions

1. Does maturity vary spatially and/or temporally?

2. Is maturity determined by length or age?

3. Does growth affect maturity?

4. How do large year classes affect maturity?

EastWest

Collection sites

No genetic difference found using microsatellites(Ingrid Spies, AFSC, unpublished data)

Methods – New Data

• Platform was tag recovery cruises East: 2002, 2003, 2004

West: 2002, 2003

• Ovaries from 5 females randomly collected per trawl haul

• Histology completed

• Fish aged by AFSC age and growth program

Methods (cont.)

• Maturity determined using histology plus visual ID of remnant ova

• Maturity determined for some females from presence of POFs* alone (Saborido-Rey and Junquera 1998, Narimatsu et al. 2005)

*Post-Ovulatory Follicles

Remnant ovapersist at least one year (Not present in all mature females)

Remnant Ova and POF

Post-ovulatory follicle(unknown persistance time)

Methods (Cont.)

• GLM applied geographic area and time period as factors

Where Y = Proportion mature, x = length or age, α,β are parameters

• Chi-squared approximation used to test significance of GLM terms

)(1

1xe

Y

Results: Maturity at age

0

0.5

1

2 3 4 5 6 7 8 9 10 11 12 13 14

East dataWest dataCombined expected

Area not significant p=0.4

Age (years)

Pro

port

ion

mat

ure

Results: Maturity at length by area

0

0.5

1

20 25 30 35 40 45 50

East data

East expected

West data

West expected

Fork length (cm)

Pro

port

ion

mat

ure

Area significant, p<<0.0001

Maturity at length by age

0

0.5

1

25 30 35 40 45 50

Fork length (cm)

Pro

port

ion

mat

ure

3 Year olds

4+ Year olds

Growth Effect

Length at age F

ork

leng

th (

cm)

20

25

30

35

40

1 2 3 4 5

East

West

Age (years)

Affect of growth on maturity at age

0

0.5

1

25 30 35 40 45

Mean Length of 4 YOIn East and West

Mean Length of 3 YOIn East and West

Fork length (cm)

Pro

port

ion

mat

ure

0.08

0.04

Model:Growth affect on maturity at length

• Predicted length determined separately for each area from von Bertalanffy model

• Maturity at age constant for each area

0

0.5

1

20 25 30 35 40 45

East

West

Model:Growth affect on maturity at length

Predicted fork length (cm)

Pro

port

ion

mat

ure

Year class strength effect

Results: Maturity at length over time (East)

0

0.5

1

25 30 35 40 45 50

Fork Length (cm)

Pro

po

rtio

n M

atu

re

1994

2002

2003

2004

Results: Maturity at length over time (West)

0

0.5

1

25 30 35 40 45 50

Fork Length (cm)

Pro

po

rtio

n M

atu

re

1993-1994

2002

2003

2002

0

10

20

30

25 30 35 40 45

Age-6+

Age-5

Age-4

Age-3

Age-2

2003

0

20

40

60

25 30 35 40 45

Age-6+

Age-5

Age-4

Age-3

Age-2

Num

ber

of F

emal

es

Fork length (cm)

Maturity at length by age

0

0.5

1

25 30 35 40 45 50

Fork length (cm)

Pro

port

ion

mat

ure

3 Year olds

4+ Year olds

Year Class Effect Model

• Constant maturity at age • Constant growth (age/length key)• Numbers at age vary according to stock

assessment estimates

Model resultsMaturity at length changes due to year class strength

0

0.5

1

20 25 30 35 40 45 50

Pro

port

ion

mat

ure

Fork length (cm)

Discussion

• Atka mackerel maturity determined more by age than length (although length has effect)

• Growth affects maturity at length (McDermott and Lowe 1997)

• Year class strength affects annual maturity at length (4 cm expected variability)

0

25

50

0 2 4 6

Maturation trade-off (Stearns 1992)

Age

Siz

e

X

0

25

50

0 2 4 6

Maturation trade-off (Stearns 1992)

Age

Siz

e

X

Constant size = mortality risk

Constant age = fecundity loss

XX

Closer to constant maturity at age

• Mortality risk relatively high. M~0.3.

• Lowered fecundity risk mitigated by nest guarding.

Mortality risk

Lowered fecundity risk

Discussion

• Atka mackerel spawning biomass estimates robust to growth changes (stock assessment uses maturity at age)

• Stock assessments should incorporate maturity at length or age based on what controls maturity for each species

• Growth changes in a trend (climate trends) would cause consistent bias

0

25

50

0 2 4 6

Error of using constant length for maturity when age is appropriate

Age

Siz

e

XX

X

Stock assessment assumes

Actual

Error in Length of maturity

0

25

50

0 2 4 6

Actual

Stock assessment assumes

X

Error of using constant age when length is appropriate

Age

Siz

e X X

Error in maturity at age

Acknowledgements

• Field collections by Barney Baker, Eric Dobbs, Allen Harvison, Elaine Herr, Justin Keesee, Scott McKillip, Sandi Neidetcher, James Nimz, Kimberly Rand, Ty Yasenak, Ingwar

• Kimberly Rand,Peter Munro, Liz Conners, Bing Shi, Sandra Lowe

• Cascade fishing, F/T Seafisher• NPRB (Project 0522)