Complexity in Fisheries Ecosystems

David Schneider

Ocean Sciences Centre, Memorial University

St. John’s, Canada

ENVS 6202 – 26 Sept 2007

Complexity in Fisheries Ecosystems•Definition(s) of Complexity

•Examples

•Several criteria

•Implications of Complexity

Definition of ComplexityEcological Society of America Fact Sheet

Common characteristics of complexity include:* Nonlinear or chaotic behavior

* Interactions that span multiple levels or spatial and temporal scales

* Hard to predict (e.g. the weather)

* Must be studied as a whole, as well as piece by piece

* Relevant for all kinds of organisms – from microbes to human beings

* Relevant for environments that range from frozen polar regions and volcanic vents to temperate forests and agricultural lands as well as

neighborhoods and industries or urban centers.

Definition of Complexity

Murray Gell-Mann:

Complexity refers to phenomena

that show scaling (power laws),

due to non-linear interactions.

Complexity – Canonical ExampleThe Bak Sandpile

Add sand to a pile, one grain at a time

Record the size of the avalanches

Result: Many small, few large avalanches.

Construct a frequency distribution of avalanche sizes

The distribution fits a power law.

# Patc

hes

Power Law Phenomena

Eelgrass Habitat of Juvenile Cod. Analysis by Miriam O

Patch Size

ß = Korchak Dimension

# Patches k (PatchSize)

A CASI image of eelgrass was analyzed at a resolution of 16m2

Patch size was defined by contiguous pixels at this resolution.

Result:Power law relation of patch frequency to patch area.But is this due to complex dynamics ?

ß

# Patc

hes 16m2

-1.6

-1.4

-1.2

-1

-0.8

-0.6

-0.4

-0.2

0

2 2.5 3 3.5 4 4.5 5 5.5 6 6.5

64m2 144m2 256m2 400m2

Complexity of Eelgrass Habitat of Juvenile Cod. Analysis by Miriam O

Korchak dimension ß found to be a power law function of resolution

Avalanches

Earthquake magnitudeFire frequency

Fire size

Tree fall area in the tropicsStock market fluctuations

More Examples of Power Laws

A: Antagonistic rates, one acting episodically

with respect to the other.

Q: What do these phenomena have in common?

River discharges

Watershed evolution

FrontsJetsEddiesLangmuir cells

HurricanesENSO

Fish Population DynamicsStable------Cyclic-------Chaotic

Fisheries EconomicsStable? Cyclic? or Build/Collapse?

Episodically Antagonistic Rates – More Examples

A: Antagonistic rates, one acting episodically

with respect to the other.

Q: What do these phenomena have in common?

Definition of Complexity

Criteria: Power laws

Episodically antagonistic rates

Non-linear interactions

Fish and the Environment in the Pacific

Hsieh et al 2005

Power laws? -Unknown

Episodically antagonistic rates -Possibly

Non-linear interactions -Fish – Yes

-Physics – No

Common Characteristics of Complexity

* Interactions that span multiple levels or spatial and temporal scales

* Hard to predict (e.g. the weather)

* Must be studied as a whole, as well as piece by piece

* Relevant for all kinds of organisms – from microbes to human beings

What are the Implications?

Implications of Power Laws

Fisheries scientists are used to the idea of limits on prediction set by high variance. But what if uncertainty has a heavy left tail ? What if there is usually a larger rare event, lying outside of past experience?

* Hard to predict (e.g. the weather)

* Interactions that span multiple levels or spatial and temporal scales

Implications of Power Laws

How many regime shifts are in this time series?

Are regime shifts low frequency events due to complex dynamics?

Implications of Power Laws* Hard to predict (e.g. the weather)

* Interactions that span multiple levels or spatial and temporal scales

Discussion of Implications

Wilson 1994

Fogarty 1995

Wilson 2002

Goals Coasts under Stress

To identify the important ways in which changes in society and the environment interact.

To identify how these changes have affected, or will affect, the health of people, their communities, andthe environment in the long run.

Interaction of Environmental Complexity with Human Organizational Complexity

Natural Science

Social Science

History Matters!

Health: Environment, Individuals,

Communities

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Interaction of Biocomplexity (e.g., Catch) with Organizational Complexity (e.g., Investment)

Implications of Complexity* Must be studied as a whole, as well as piece by piece

* Relevant for all kinds of organisms – from microbes to human beings

Health: Environment, Individuals,

Communities

Investment

Catch

1955 1965 197515

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SummaryComplexity in Fisheries EcosystemsA new way of thinking about fisheries and fisheries ecosystems.

Applies to organisms, schools, populations, habitats, ecosystems.

Several criteria, from loose to strict.

Cannot rely on: Euclidean geometry,

Newtonian mechanics,

Equilibrium dynamics.