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Experiences applying Experiences applying Ecosim Ecosim in the Gulf of Alaska in the Gulf of Alaska Sheila JJ Heymans, Sylvie Sheila JJ Heymans, Sylvie Guénette Guénette Villy Christensen, Andrew Villy Christensen, Andrew Trites Trites UBC FISHERIES CENTRE INCOFISH WP 4 Meeting INCOFISH WP 4 Meeting Cape Town Cape Town 11-16 September 2006 11-16 September 2006

Experiences applying Ecosim in the Gulf of Alaska

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UBC FISHERIES CENTRE. Experiences applying Ecosim in the Gulf of Alaska. Sheila JJ Heymans, Sylvie Guénette Villy Christensen, Andrew Trites. INCOFISH WP 4 Meeting Cape Town 11-16 September 2006. Aims. - PowerPoint PPT Presentation

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Page 1: Experiences applying Ecosim in the Gulf of Alaska

Experiences applying Experiences applying EcosimEcosim

in the Gulf of Alaskain the Gulf of AlaskaSheila JJ Heymans, Sylvie GuénetteSheila JJ Heymans, Sylvie Guénette

Villy Christensen, Andrew TritesVilly Christensen, Andrew Trites

UBCFISHERIESCENTRE

INCOFISH WP 4 Meeting INCOFISH WP 4 Meeting Cape TownCape Town

11-16 September 200611-16 September 2006

Page 2: Experiences applying Ecosim in the Gulf of Alaska

AimsAims• To evaluate how fishing and climate

change have impacted the ecosystem resources of the Northeast Pacific;

• Used two systems: Aleutians and SE Alaska ~ species, notably Steller sea lions and other mammals, have different trajectories.

Page 3: Experiences applying Ecosim in the Gulf of Alaska

ProblemProblem

AleutiansAleutians

SEAKSEAK

Steller sea lion abundance

0

30,000

60,000

90,000

1956 1961 1966 1971 1976 1981 1986 1991 1996

Page 4: Experiences applying Ecosim in the Gulf of Alaska

Study areasStudy areas

Aleutian IslandsAleutian Islands

Southeast AlaskaSoutheast Alaska

Shelf east of 140oW0 - 1,000m depth

91,000 km2

170oW – 170oE0 - 500m depth

57,000 km2

Page 5: Experiences applying Ecosim in the Gulf of Alaska

MethodologyMethodology• Construct models of both ecosystems

(1963);• Driven by fisheries (i.e. using C/B); • Fitting: change vulnerabilities, feeding

time, P/B, etc.;• Estimate forcing function;• Correlate to environmental parameters;• Enter environmental function to fit

model.

Page 6: Experiences applying Ecosim in the Gulf of Alaska

Aleutians biomassAleutians biomass

0

500,000

1,000,000

1,500,000

2,000,000

1963 1968 1973 1978 1983 1988 1993 1998

Arrowtooth Atka Pollock

0

50,000

100,000

150,000

200,000

1963 1968 1973 1978 1983 1988 1993 1998

POP Sablefish

Page 7: Experiences applying Ecosim in the Gulf of Alaska

SE Alaska biomassSE Alaska biomass

0

100,000

200,000

300,000

400,000

500,000

600,000

1963 1968 1973 1978 1983 1988 1993 1998

Salmon Herring POP Sablefish

0

20,000

40,000

60,000

80,000

100,000

120,000

1963 1968 1973 1978 1983 1988 1993 1998

Halibut Pacific cod

Page 8: Experiences applying Ecosim in the Gulf of Alaska

Estimate environmental variationEstimate environmental variation

0.0

0.5

1.0

1.5

2.0

2.5

1963 1968 1973 1978 1983 1988 1993 1998

Aleutians SE Alaska

Page 9: Experiences applying Ecosim in the Gulf of Alaska

Known environmental indicesKnown environmental indices

-3

-2

-1

0

1

2

3

1963 1968 1973 1978 1983 1988 1993 199810

11

12

13

14

15

AO

I, A

LPI,

RI

NPI

Pacific Decadal Oscillation

PDO

Page 10: Experiences applying Ecosim in the Gulf of Alaska

Environmental variationEnvironmental variation

0.7

0.8

0.9

1

1.1

1.2

1.3Ja

n-63

Jan-

66

Jan-

69

Jan-

72

Jan-

75

Jan-

78

Jan-

81

Jan-

84

Jan-

87

Jan-

90

Jan-

93

Jan-

96

Jan-

99

Jan-

02

Inverse PDO

PDO

Page 11: Experiences applying Ecosim in the Gulf of Alaska

Fitting the modelsFitting the models Aleutians - biomass

BiomassPDO

Relative SS = 1

Environ.variation

Relative SS = 0.97

Fishing

Relative SS = 0.99

Steller sea lions

0

2,000

4,000

6,000

8,000

10,000

12,000

1963 1968 1973 1978 1983 1988 1993 1998

Atka mackerel

0

300,000

600,000

900,000

1,200,000

1963 1968 1973 1978 1983 1988 1993 1998

Adult pollock

0

150,000

300,000

450,000

600,000

750,000

1963 1968 1973 1978 1983 1988 1993 1998

Pacific Ocean perch

0

20,000

40,000

60,000

80,000

1963 1968 1973 1978 1983 1988 1993 1998

Sablefish

0

50,000

100,000

150,000

1963 1968 1973 1978 1983 1988 1993 1998

Arrowtooth flounder

0

10,000

20,000

30,000

40,000

50,000

1963 1968 1973 1978 1983 1988 1993 1998

Page 12: Experiences applying Ecosim in the Gulf of Alaska

Fitting the modelsFitting the models Aleutians - catch

Catch

Relative SS = 0.99

Fishing

Relative SS = 0.97

Environ.variation

Relative SS = 1

PDO

Forced catch

Steller sea lions

0

20

40

60

80

100

1963 1968 1973 1978 1983 1988 1993 1998

Atka mackerel

0

35,000

70,000

105,000

140,000

1963 1968 1973 1978 1983 1988 1993 1998

Adult pollock

0

35,000

70,000

105,000

140,000

1963 1968 1973 1978 1983 1988 1993 1998

Pacific Ocean perch

0

4,000

8,000

12,000

16,000

1963 1968 1973 1978 1983 1988 1993 1998

Arrowtooth flounder

0

1,500

3,000

4,500

6,000

7,500

1963 1968 1973 1978 1983 1988 1993 1998

Sablefish

0

1,500

3,000

4,500

1963 1968 1973 1978 1983 1988 1993 1998

Page 13: Experiences applying Ecosim in the Gulf of Alaska

Fitting the modelsFitting the modelsSE Alaska - biomass

Salmon

1963 1968 1973 1978 1983 1988 1993 1998 1963 1968 1973 1978 1983 1988 1993 1998

BiomassEnviron.variation

Relative SS = 1

PDO

Relative SS = 0.8

Fishing

Relative SS = 0.63

Steller sea lions

0

1,000

2,000

3,000

4,000

1963 1968 1973 1978 1983 1988 1993 1998

0

50,000

100,000

150,000

200,000

1963 1968 1973 1978 1983 1988 1993 1998

Herring

0

100,000

200,000

300,000

400,000

500,000

Pacific Ocean perch

0

50,000

100,000

150,000

200,000

250,000

1963 1968 1973 1978 1983 1988 1993 1998

Sablefish

0

20,000

40,000

60,000

80,000

100,000

1963 1968 1973 1978 1983 1988 1993 1998

Halibut

0

20,000

40,000

60,000

80,000

100,000

Page 14: Experiences applying Ecosim in the Gulf of Alaska

Fitting the modelsFitting the modelsSE Alaska - catch

Steller sea lions

0

1

2

3

4

5

6

7

0

15,000

30,000

45,000

1963 1968 1973 1978 1983 1988 1993 1998

10,000

20,000

30,000

40,000

01963 1968 1973 1978 1983 1988 1993 1998

Relative SS = 1

Environ.variation

Relative SS = 0.8

PDO

Catch

Forced catch

Relative SS = 0.63

Fishing

1963 1968 1973 1978 1983 1988 1993 1998

Salmon

0

70,000

140,000

210,000

280,000

350,000

1963 1968 1973 1978 1983 1988 1993 1998

Herring

Pacific Ocean perch

01963 1968 1973 1978 1983 1988 1993 1998

Sablefish

0

3,000

6,000

9,000

12,000

15,000

18,000

1963 1968 1973 1978 1983 1988 1993 1998

Halibut

3,500

7,000

10,500

14,000

Page 15: Experiences applying Ecosim in the Gulf of Alaska

Fishing

1000 0 1000 2000 3000 4000 KilometersN

Competitive Interactions

Fishing

Ocean Climate Change

Predation

Steller sea lionSteller sea lion declinedecline

Aleutian Islands

Guenette, Heymans, Christensen & Trites (in prep)

1960 1980 20000

10,000

20,000

30,000

40,000

Abu

ndan

ce Competitive Interactions

Predation

Page 16: Experiences applying Ecosim in the Gulf of Alaska

ConclusionsConclusions• Both external forces (fishing & climate change) have

caused the changes in these two ecosystems;• Fishing important for POP, herring and sablefish;• Environmental forces such as PDO combined with

fishing important for Steller sea lions, halibut and pollock;

• Sea lion decline explained by climate and predation• Unable to fit salmon as effects are larger scale than

these models.

Page 17: Experiences applying Ecosim in the Gulf of Alaska

Total systems throughputTotal systems throughput

3500

4500

5500

6500Ja

n-63

Jan-

66

Jan-

69

Jan-

72

Jan-

75

Jan-

78

Jan-

81

Jan-

84

Jan-

87

Jan-

90

Jan-

93

Jan-

96

Jan-

99

Jan-

02

Aleutians

SEAK

Page 18: Experiences applying Ecosim in the Gulf of Alaska

Network Analysis IndicesNetwork Analysis Indices

• Finn cycling index: relative amount of cycling in the ecosystem as a percentage of the total systems throughput (Finn 1976).

• Ascendency: indicator of the specialization and organization in the ecosystem (Ulanowicz, 1986).

• Redundancy: Internal flow overhead is an indication of the internal redundancy in the system (Mageau et al. 1998).

Page 19: Experiences applying Ecosim in the Gulf of Alaska

Information theoryInformation theory

Ulanowicz 1986

Organization & Specialization

Info

rmat

ion

CΦ A

Φ = C - A

Page 20: Experiences applying Ecosim in the Gulf of Alaska

Finn cycling indexFinn cycling index

0.5

1.0

1.5

2.0

2.5

3.0

3.5

Jan-

63

Jan-

66

Jan-

69

Jan-

72

Jan-

75

Jan-

78

Jan-

81

Jan-

84

Jan-

87

Jan-

90

Jan-

93

Jan-

96

Jan-

99

Jan-

02

0.6

0.7

0.8

0.9

1.0

1.1

1.2A

leut

ians

SEA

K

0

0.3

0.6

0.9

1.2

1.5

Abs. diff. between value and 5 yr average

Page 21: Experiences applying Ecosim in the Gulf of Alaska

AscendencyAscendencyA

leut

ians

SEA

K

50

55

60

65

70

75

80

Jan-

63

Jan-

66

Jan-

69

Jan-

72

Jan-

75

Jan-

78

Jan-

81

Jan-

84

Jan-

87

Jan-

90

Jan-

93

Jan-

96

Jan-

99

Jan-

02

24

25

26

27

28

29

30

31

32

0

2

4

6

8

10

12

14

16

Abs. diff. between value and 5 yr average

Page 22: Experiences applying Ecosim in the Gulf of Alaska

0

20

40

60

80Ja

n-63

Jan-

65

Jan-

67

Jan-

69

Jan-

71

Jan-

73

Jan-

75

Jan-

77

Jan-

79

Jan-

81

Jan-

83

Jan-

85

Jan-

87

Jan-

89

Jan-

91

Jan-

93

Jan-

95

Jan-

97

Jan-

99

Jan-

01

Ascendency - AleutiansAscendency - Aleutians

FlowExport

Respiration

0

4

8

12

16

Abs. diff. between value and 5 yr average

Page 23: Experiences applying Ecosim in the Gulf of Alaska

RedundancyRedundancy

32

33

34

35

36

37

38

Jan-

63

Jan-

66

Jan-

69

Jan-

72

Jan-

75

Jan-

78

Jan-

81

Jan-

84

Jan-

87

Jan-

90

Jan-

93

Jan-

96

Jan-

99

Jan-

02

44

45

46

47

48

49A

leut

ians

SEA

K

0

1

2

3

4

Abs. diff. between value and 5 yr average

Page 24: Experiences applying Ecosim in the Gulf of Alaska

ConclusionsConclusions• Effects of environmental variation is seen in

the total systems throughput, ascendency and redundancy;

• Finn cycling index shows less direct effects and might be more useful as index of emergent effects;

• Change from the running average increased after regime shift in most indices;

• Difference less in SEAK than in AI;• AI: largest fluctuations in respiration for both

ascendency and overhead.

Page 25: Experiences applying Ecosim in the Gulf of Alaska

AcknowledgementsAcknowledgements• Support from NOAA through the North

Pacific Universities Marine Mammal Research Consortium and the North Pacific Marine Science Foundation

• Colleagues from DFO, ADF&G, NMFS, MMU

• Carl Walters, Steve Martell