spatial and temporal variability in atka mackerel (pleurogrammus monopterygius) female maturity at...
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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No genetic difference found using microsatellites(Ingrid Spies, AFSC, unpublished data)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)