Size based indicators rjan stman Dept. Aquatic Resources, regrund - - PowerPoint PPT Presentation

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Size based indicators rjan stman Dept. Aquatic Resources, regrund - - PowerPoint PPT Presentation

Jun 26, 2023 147 likes •299 views

Size based indicators rjan stman Dept. Aquatic Resources, regrund SLU What fish size indicate? Diet size dependend the ecological function of a stock/community depends on size distributions High mortality or selective

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SLIDE 1

Size based indicators

Örjan Östman

  • Dept. Aquatic Resources, Öregrund

SLU

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SLIDE 2

What fish size indicate?

  • Diet size dependend – the ecological function of a

stock/community depends on size distributions

  • High mortality or selective mortality results in few large

fishes

  • Poor feeding conditions result in slow growth
  • Swedish Agency for Marine and Water Mangement has

”natural size distributions” of stocks as a primary goal

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SLIDE 3

Can size based indicators be used for ecological assessment?

  • Size, i.e. body length, readily

available in Swedish monitoring data

  • What indicators to use?
  • Which asepects?
  • Drivers of size distributions?
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SLIDE 4

Potential indicators

  • Some property of the size

distribution, e.g. mean, median quantile (Q90)

  • Easy, just measure length
  • Mean length of mature fish (mLmat)
  • r proportion fish expected to be

mature (%Mat)

  • Must know maturity pattern, sex and

site specific

  • Can be few/low proportion
  • Mean length in relation to length at

maturity (mL/Mat) or number of fish expected to be mature (#Mat)

% Size Median Mean Quantile #Ind Size Mature

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SLIDE 5

Perch (key species) & Pike, pikeperch, whitefish (large fish group)

  • Perch ubiquitous along the Swedish

Baltic Sea coast, diet shift around 15-20 cm, mature earlier in Gulf of Bothnia (females 15 cm) than in BS Proper (females 25 cm)

  • Pike, pikeperch and whitefish lumped

into one generic group of large fishes. Mature (90%) at 35 cm

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SLIDE 6

High redundancy among indicators across sites

  • 2
  • 1

1 2

  • 1.0

0.0 0.5 1.0

Variables factor map (PCA)

Dim 1 (48.33%) Dim 2 (20.70%) p_mL p_MedianL p_mLmat p_P_Mat p_mL_M90 p_cpue_m90 p_L90 np_mL np_MedianL np_mLmat np_P_Mat np_mL_M90 np_cpue_m90 np_L90 p_mL p_MedianL p_mLmat p_P_Mat p_mL_M90 p_cpue_m90 p_L90 np_mL np_MedianL np_mLmat np_P_Mat np_mL_M90 np_cpue_m90 np_L90 p_mL p_MedianL p_mLmat p_P_Mat p_mL_M90 p_cpue_m90 p_L90 np_mL np_MedianL np_mLmat np_P_Mat np_mL_M90 np_cpue_m90 np_L90 p_mL p_MedianL p_mLmat p_P_Mat p_mL_M90 p_cpue_m90 p_L90 np_mL np_MedianL np_mLmat np_P_Mat np_mL_M90 np_cpue_m90 np_L90 p_mL p_MedianL p_mLmat p_P_Mat p_mL_M90 p_cpue_m90 p_L90 np_mL np_MedianL np_mLmat np_P_Mat np_mL_M90 np_cpue_m90 np_L90 p_mL p_MedianL p_mLmat p_P_Mat p_mL_M90 p_cpue_m90 p_L90 np_mL np_MedianL np_mLmat np_P_Mat np_mL_M90 np_cpue_m90 np_L90 p_mL p_MedianL p_mLmat p_P_Mat p_mL_M90 p_cpue_m90 p_L90 np_mL np_MedianL np_mLmat np_P_Mat np_mL_M90 np_cpue_m90 np_L90 p_mL p_MedianL p_mLmat p_P_Mat p_mL_M90 p_cpue_m90 p_L90 np_mL np_MedianL np_mLmat np_P_Mat np_mL_M90 np_cpue_m90 np_L90 p_mL p_MedianL p_mLmat p_P_Mat p_mL_M90 p_cpue_m90 p_L90 np_mL np_MedianL np_mLmat np_P_Mat np_mL_M90 np_cpue_m90 np_L90

  • 2
  • 1

1 2

  • 1.0

0.0 0.5 1.0

Variables factor map (PCA)

Dim 3 (11.06%) Dim 4 (6.92%) p_mL p_MedianL p_mLmat p_P_Mat p_mL_M90 p_cpue_m90 p_L90 np_mL np_MedianL np_mLmat np_P_Mat np_mL_M90 np_cpue_m90 np_L90 p_mL p_MedianL p_mLmat p_P_Mat p_mL_M90 p_cpue_m90 p_L90 np_mL np_MedianL np_mLmat np_P_Mat np_mL_M90 np_cpue_m90 np_L90 p_mL p_MedianL p_mLmat p_P_Mat p_mL_M90 p_cpue_m90 p_L90 np_mL np_MedianL np_mLmat np_P_Mat np_mL_M90 np_cpue_m90 np_L90 p_mL p_MedianL p_mLmat p_P_Mat p_mL_M90 p_cpue_m90 p_L90 np_mL np_MedianL np_mLmat np_P_Mat np_mL_M90 np_cpue_m90 np_L90 p_mL p_MedianL p_mLmat p_P_Mat p_mL_M90 p_cpue_m90 p_L90 np_mL np_MedianL np_mLmat np_P_Mat np_mL_M90 np_cpue_m90 np_L90 p_mL p_MedianL p_mLmat p_P_Mat p_mL_M90 p_cpue_m90 p_L90 np_mL np_MedianL np_mLmat np_P_Mat np_mL_M90 np_cpue_m90 np_L90 p_mL p_MedianL p_mLmat p_P_Mat p_mL_M90 p_cpue_m90 p_L90 np_mL np_MedianL np_mLmat np_P_Mat np_mL_M90 np_cpue_m90 np_L90 p_mL p_MedianL p_mLmat p_P_Mat p_mL_M90 p_cpue_m90 p_L90 np_mL np_MedianL np_mLmat np_P_Mat np_mL_M90 np_cpue_m90 np_L90 p_mL p_MedianL p_mLmat p_P_Mat p_mL_M90 p_cpue_m90 p_L90 np_mL np_MedianL np_mLmat np_P_Mat np_mL_M90 np_cpue_m90 np_L90

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SLIDE 7

I chose…

  • Length at 90 percentile (L90)
  • Mean length relative size-at-

maturation (mL/M90)

  • Catch per unit effort of mature

fish (cpue_m90)

  • Differ between gears and

latitude

  • 10
  • 5

5

  • 6
  • 4
  • 2

RDA1 RDA2

p_mL p_MedianL p_mLmat p_P_Mat p_mL_M90 p_cpue_m90 p_L90 np_mL np_MedianL np_mLmat np_P_Mat np_mL_M90 np_cpue_m90 np_L90

Lat mTemp TOTP

  • 1

1 GearKÖ GearNL GearNN GearTN

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SLIDE 8

Temporal drivers?

  • At three long-term

monitoring sites (Holmön and Forsmark, Coastal nets, Kvädö and Vinö, Net links)

  • Negative associations with

nutrient loadings over time

  • mL/M90 for both perch and

large fish positive with salinity?

  • 2
  • 1

1 2 3 4

  • 3
  • 2
  • 1

1 2

L90 NonPerch N load

  • 2
  • 1

1 2 3 4

  • 3
  • 2
  • 1

1 2

CPUE M90 NonPerch N load

  • 3
  • 2
  • 1

1 2 3 4 5

  • 3
  • 2
  • 1

1 2 3

mL/M90 NonPerch P load

  • 3
  • 2
  • 1

1 2 3

  • 2.5
  • 1.5
  • 0.5

0.5 1.5 2.5

L90 Perch Salinity

  • 2
  • 1

1 2 3 4

  • 3
  • 2
  • 1

1 2 3

CPUE M90 Perch P load

  • 4
  • 3
  • 2
  • 1

1 2 3 4

  • 2.5
  • 1.5
  • 0.5

0.5 1.5

mL/M90 Perch P load

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SLIDE 9

Cont

  • Several indicators negative

associations with temperature

  • Perch positive autocorrelation

Driver variable Perch L90 Perch CPUEm90 Perch mLm90 Non- perch L90 Non- perch CPUEm90 Non- perch mLm90 AICc 471.0 448.1 447.6 451.1 478.0 418.7

  • Adj. R2

0.09 0.10 0.20 0.10 0.07 0.14 φ(t-1)

  • 10.0
  • 3.1
  • 16.2

+1.8 +1.2 +1.3 Hydro- climate variables Temp +1.5

  • 2.2 (+)
  • 6.0 (-)
  • 11.2(-)
  • 11(-)
  • 1.8 (-)

Salinity

  • 2.4(+)

+2.0

  • 0.6 (+)

+1.8 +1.2

  • 4.2(+)

BSI +0.6 +1.9 +0.4 +1.9 +0.6 +1.8 Anthropo

  • genic

divers Secchi +0.6 +1.3 +0.6 +0.4

  • 1.2(-)

+1.2 Nload +2.0 +0.9 +2.0 +0.1

  • 7.2(-)

+2.0 Pload +1.5

  • 0.6(-)
  • 4.2 (-)
  • 15.7(-)

+1.6

  • 18 (-)

DIN +1.4 +1.3 +0.7 +1.8 +0.8 +1.5 DIP +0.7 +0.6 +0.1 +2.0 +1.5 +1.9 Landing s +0.9 +0.2 +0.8 +1.9 +1.7 +0.9

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SLIDE 10

No-take areas/refererence area

Perch L90 Perch CPUEm90 Perch mLm90 Non-perch L90 Non-perch CPUEm90 Non-perch mLm90 Licknevarp NN (2013) NTA Kvädö 32 cm (26 cm) 8.5 (1.5) 96% (80%) 49 cm (39 cm) 0.55 (0.14) 105% (66%) Lännåker NN (2012-2015) NTA Before 30 cm (31 cm) 1.5 (3.75) 84% (92%) 32 cm (40 cm) 0.34 (0.14) 53% 62% Lännåker TN (2012-2015) NTA Before 27 cm (30 cm) 8.6 (20.2) 82% (94%) 73 cm (71 cm) 3.0 (1.6) 105% (115%) Storjungfrun NN (2013-2015) Before NA NA NA 43 cm (30 cm) 0.32 (0) 104% Kalvhararna NN (2013-2015) Before 33 cm (28 cm) 0.84 (0.48) 170% (166%) 39 cm (37 cm) 0.19 (0.03) 95% (92%)

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SLIDE 11

GES bounadries reference areas

Long time-series Perch L90 Perch CPUEm90 Perch mLm90 Non-perch L90 Non-perch CPUEm90 Non-perch mLm90 Kvädö Net link 22 cm (3) 0.3 (2) 72% (1) 38 cm (4) 0.10 (2) 73% (7*) Kvädö Nordic Net 24 cm (3) 0.75 (2) 77% (2) 35 cm (1) 0.05 (1) 59% (2*) Vinö Net link 21 cm (1) 0.5 (1) 71% (1) 39 cm (1) 0.14 (3) 71% (1) Forsmark Coast net 24 cm (2) 2 (3) 75% (3) 31 cm (3) 0 (0) 57% (2) Forsmark Nordic Net 26 cm (1) 1.7 (0) 79% (2) 25 cm (1) 0 (0) 49% (3) Holmön Coast Net 23 cm (3) 30 (1) 125% (3) 38 cm (3) 0.04 (4) 80% (2) Holmön Nordic net 25 cm (2) 11 (1) 125% (1) 35 cm (3) 0.05 (3) 85% (3)

(Years below boundary, n = 22-28 for Net link/ Coastal nets, n = 15 for Nordic nets) CS, NL: 22-23 cm NA 70% 38 cm 0.05? 70% NN: 24 cm NA 75% 35 cm 0.05? 70%

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SLIDE 12

Nordic nets spatial comparison

Gulf of Bothnia Perch L90 Perch CPUEm90 Perch mLm90 Non-perch L90 Non-perch CPUEm90 Non-perch mLm90 MPA (N = 4) 28.5 ± 1.2 7.7 ± 5.2 135 ± 17 42 ± 2.2 0.11 ± 0.05 96.3 ± 1.8 REF (N = 6) 25.7 ± 0.7 11.4 ± 2.2 123 ± 8.1 43 ± 2.9 0.13 ± 0.03 70.2 ± 4.4 URB (N = 3) 26.3 ± 1.2 12.2 ± 2.6 136 ± 3.9 33.7 ± 3.5 0.27 ± 0.10 69.7 ± 9.8 Baltic Sea Proper EUT (N = 4) 26 ± 1.2 1.0 ± 0.4 80.5 ± 1.2 36.5 ± 2.4 0.46 ± 0.07 66.6 ± 1.8 MPA (N = 5) 24.75 ± 1.9 1.45 ± 0.5 80.6 ± 3.5 47 ± 1.9 0.36 ± 0.03 109 ± 12 NOT (N =3) 29.7 ± 1.2 3.65 ± 2.4 86.9 ± 4.8 57.3± 16 0.35 ± 0.1 102 ± 27 OTH (N =7) 26.3 ± 0.7 1.4 ± 0.3 81.1 ± 1.6 41.8 ± 1.1 0.30 ± 0.06 84 ± 3.8 REF (N = 15) 24.9 ± 0.4 1.6 ± 0.3 78.6 ± 0.8 41.25 ± 2.0 0.11 ± 0.03 70.4 ± 5.9 URB (N = 4) 27.3 ± 0.6 1.7 ± 0.5 83.6 ± 1.3 57.5 ± 3.9 0.25 ± 0.02 105 ± 6.3

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SLIDE 13

Summary pros

  • Size based indicators use readily (in Sweden) available information
  • Associated with nutrients and temperature in time-series
  • Respond positively to no-take areas
  • Identify non-site specific boundaries for L90 seem possible
  • Maybe non-site specific boundaries for mL/M90 as well
  • Good complement to abundance based indicators
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SLIDE 14

Summary cons

  • Gear specific
  • Some human impacted sites show quite good status based on size

distributions

  • Need size distributions
  • Would need more/better site-speific life-history data
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SLIDE 15

Summary