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When to adapt or when to transform? Using network controllability to assess
how manageable are regime shifts!!
Juan-Carlos Rocha
Regime Shifts Transformations
Figures from Arctic Resilience Assessment Interim Report 2012
• Systems can be represented as a network of interacting elements
• Identifying controlling nodes is possible using only structural information of the network:
• # of driving nodes correlates with degree distribution
• driver nodes tend to avoid high-degree nodes
• Heterogeneous networks (most real) are difficult to control. Homogeneous dense networks are more controllable = fewer driving nodes
Liu et al, 2012
Are regime shifts controllable? To what extent can we manage them?
• Critics to Liu et al.:
• Topology is not enough
• Internal dynamics
• “We argue that more important than issues of structural controllability are the questions of whether a system is almost uncrontrollable, whether it is almost unobservable…”
Cowan et al, 2012
• Focus on edge dynamics: heterogeneous and sparse networks have more controllable edge dynamics than homogeneous dense networks.
• Contradictory results?
Are regime shifts controllable? To what extent can we manage them?
Driver… is any natural or human-
induced factor that directly or indirectly causes a change in
an [eco]system. A direct driver unequivocally influences ecosystem processes. An
indirect driver operates more diffusely by altering one or
more direct drivers.
Bivalves collapse
Bivalvesabundance
Dissolved oxigen
Biodiversity
Habitat structuralcomplexity
Local watermovements
+
+
+
+
+
Fishing
Plankton andfilamentous algae
-
Water turbidity
-
-
B
B
R
R
Nutrients input
Agriculture Urbanization
SewageFertilizer Use
Deforestation
+
+
+
+
+
Demand forfood & fibre
+
mid-predator fish
-
-
+
+
B
Filtration+
-
Erosion+
+
Nutrients in water-+
+
+
+
Logging+
+
Flooding
+
Disease
-
+
sedimentation
+
-
Shellfish harvest
-
+
+ B
B
Urban StormWater Runoff
+
+
PrecipitationVariability
+
+
Aquaculture
+
+
Hurricane
-
+
My own critiques• Unmatched nodes change if the
periphery of the causal networks change - The limits of the system blur
• Unmatched nodes change when joining causal networks to understand cascading effects.
• I believe there is opportunities to combine network science and resilience science to answer the question: When do we build resilience and where do we need transformational change? Causal Loop Diagrams for
19 regime shifts around the world
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Thank you!
Does it make sense?? Ideas, tomatoes or opportunities for collaboration:
e-mail: [email protected] twitter: @juanrocha slides: http://criticaltransitions.wordpress.com/ | data: www.regimeshifts.rog
