A Complex Systems Study of the Implications of Anthropogenic Perturbations of the Global Biogeochemi

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A Complex Systems Study of the Implications of
Anthropogenic Perturbations of the Global
Biogeochemical CyclesA PhD
Presentation by Nicola Smith23 May 2008
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During the 20th century the worlds population
quadrupled, the global economy expanded 14-fold,
energy use increased 16 times, and the control
of world biomass increased to about 40 percent
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Overview of Presentation

• Describe research topic and key aims
• Provide context to the proposed research a
  summary of five existing contributions
• Propose a broad conceptual framework
• Describe the economic components of the research
• Summary of key challenges

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Overview of Research

• Key task is to develop an integrated model of the
  Earth system that captures insights from both the
  natural and social sciences
• Focus is on
• Natural systems - biogeochemical cycles
• Socio-economic systems - economy, demographics
• The interactions within and between these
  components
• Research will pick up on contributions already
  made by Murray Patterson and Garry McDonald
• Research will be undertaken at a global level

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Key Research Aims

• To develop a method for modelling the world
  economy as it is embedded within the global
  biogeochemical cycles, that
• Achieves a high level of integration of natural
  and human components
• Captures important feedbacks, non-linearities and
  lags
• To identify the anthropogenic disturbance regimes
  and perturbations that matter at the global level
• The human mind is not well-adapted to
  interpreting the behaviour of our complex earth
  system characterised by multiple non-linear
  feedbacks Jay Forrester
• To identify sustainable pathways for the global
  economy

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What are Sustainable Pathways?

• A steady state economy - in terms of physical
  input and output
• Minimizing energy throughput (entropy law)
• A sustainable economy is one characterised by
  minimized and consistent physical exchanges
  between human society and the environment, with
  internal material loops driven by renewable
  energy
• Maintaining a constant stock of (natural) capital
  (some natural capital is critical)
• Maintain life-support services and assimilative
  capacity of the environment
• Ensuring the Earth system does not transcend to a
  new stable state

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Overview of Other Models

• Integrated global modelling originates from the
  1970s with the World2 and World3 models
• Nearly all models begin with a strong emphasis on
  either natural or human parts of the earth system
  truly integrated models still rare
• Five models have been selected for review to help
  provide a context to the proposed research
• Mackenzie, GBCM, World Model, GUMBO and TARGETS

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Mackenzie Model

• Mackenzie et al. (1993)
• Strengths
• Attempt to integrate biogeochemical cycles (C, N
  and P) at a global level
• Relatively simple and easy to understand
• Limitations
• Few connections and feedbacks between cycles
• Largely driven by perturbations in P cycle only
• Almost every process controlled by first order
  rate equation
• eg

fAO flux of C from atmosphere to ocean, k
constant, A C stock in atmosphere
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Global Biogeochemical Cycling Model (GBCM)

• Strengths
• Very high degree of integration and feedback
  between the biogeochemical cycles
• eg phytoplankton N fixation
• Limitations
• Every process driven by a selected donor stock
• Does not include anthropogenic processes

C cycle
H cycle
P cycle
S cycle
N cycle
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GBCM Example of CO2 Increase
My model will extend the stoichiometric approach
to the economy
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Leontiefs World Model

• What is input-output analysis?

• Allows for easy consideration of economy
  structure, direct indirect effects, industrial
  metabolism

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Leontiefs World Model (continued)

• First created by Leontief colleagues in mid
  1970s
• Extended in other studies eg Duchin and Lange
  (1994)
• Strengths
• Describes economy with high level of detail (c50
  sectors, 16 regions)
• Recognises the industrial metabolism of the
  economy (6 resource inputs and 3 residuals)
• Limitations
• Mostly linear relationships, few feedbacks
• No internal description of natural systems

• Highlights the difficulty of technology change

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GUMBO Model

• Connects social, economic and biophysical systems
• Focus is on ecosystem services
• Strengths
• Many aspects of the Earth system included
• C, N and H2O cycles, climate, capital formation,
  GWP, land use, energy use, population
• Recognises the industrial metabolism of economy
• Considers role of the natural systems in economic
  growth
• Limitations
• Entire economy aggregated to 1 sector

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TARGETS Framework
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TARGETS Framework (continued)

• Strengths
• Extensive coverage of the Earth system
• C, N, S, P hydrological cycles, climate,
  agriculture, land use change, energy use,
  population, health
• Some feedbacks from environment to socio-economic
  systems
• eg impact of CO2 fertilization on agricultural
  production
• Incorporation of cultural dimensions
• Limitations
• Complexity has led to a loss of transparency
• Limited representation of the economy, only 2
  sectors industries and services (but sub-models
  for agriculture and energy)

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Summary
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The Economic System (static)

• Starting point is monetary input-output table
• Next step is to extend the framework to a static
  model of mass and energy flows
• Like other physical input-output tables this
  will
• Account for the metabolism of the economy
• Recognize the law of conservation of mass
• The model will be unique as materials will be
  recorded as biogeochemical species

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The Economic System (static, continued)
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The Economic System (dynamic)

• A particularly challenging component of the
  research
• Key factors to consider
• Population change
• Change in capital
• Technology change
• Feedbacks from the environment
• No existing modeling approach entirely
  satisfactory

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Modelling Economic Dynamics

• Scenario-Based
• How do we incorporate feedbacks?

• Input-Output

• Economic Growth Theory

• CGE Models
• Assumption of equilibrium

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Conclusion Key Challenges

• Breadth of topic
• Scale and aggregation
• How do we model dynamic growth of the economy?
• How do we incorporate technological change?
• Complexity and comprehensiveness vs easily
  digestible outputs