Introduction to and Measurement of ComplexityFRST 532C – Complex Adaptive SystemsLorea Coronado-Garcia

Readings

Levin, S (2005) Self-organization and the emergence of complexity in ecological systems. BioScience 55: 1075-1079.

Parrot L (2010) Measuring ecological complexity. Ecological Indicators 4: 85-92.

Self-organization and the emergence of complexity in

ecological systems

Described by physical and biological mechanisms that are well understood

Given an initial soup on which these mechanisms can act

No invocation of ecosystem-level selection or intelligent design is needed or justified

Gaia

Proposed by James Lovelock

Postulates that biota self regulate conditions for levels it needs for survival system, species and environment co-evolve, the two are inseperable

Extreme: Teleological Gaia

Biosphere is a superorganism selected for its macroscopic properties in order to serve the biota

Problem: macroscopic regularities in the biosphere in terms of selection acting upon the whole system

Lovelocks imposes optimization argumets. E.g., puddle in a hole.

Not useful for repairing the damage we cause

Self-organized Criticality (SOC)

Question

How do modularity and heterogeneity arise in this context, how are they maintained, and what are the implications for maintaining the robustness of ecosystems and the biosphere?

Biosphere and ecosystem as compex adaptive

systemsPattern emerges from individual agents

Feed back to affect individual agents

Develop cycle to provide the regulation of local environments

Truth between extremes

Move towards From models that recognize the heterogeneity of systems

Intermediate levels: forging mutualisms, coalitions, and even multicellular assemblages

The domain of science to explain how such complexity can arise from local interactions

Self Organization

Autocatalytic networks

Agent-based approaches to understanding all aspects of biospheric organization

Tinkerer rather than master craftsman

Measuring Ecological Complexity

Differentiate simple from complex system

Lies at the edge of chaos

Linked to concept of ecosystem diversity, resilience, integrity

Two Types

Type 1 Increases linearly with increasing disorder in

the system

Type 2 Convex function

Measures

Temporal

Spatial

Spatiotemporal

Structural

Temporal Measures

Use symbols

Assigned probability

+founded in tradition of information-based measures

- loss of information pre-treatment of the series

Type 1: Mean Information Gain, Recurrence Quantification Analysis

Type 2: Fluctuation Complexity

Spatial Measures

Characterize, ordered, random and complex two-dimensional patterns

Type 1: Fractal Dimensions

Type 2: Number of points required to trace boundaries

Spatiotemporal Measures

Typically used in 2D

3D: Blobs in space-time

Structural Measures

Describes organization and relationships between components of a system

Represented with nodes and connecting edges

Non-random, irregular structure: characterized by short diameters

Implication: robust to random loss of nodes, but highly vulnerable to the loss of hubs (possible keystone).

Ecological Complexity as an Ecological

OrientorFew examples

Can use to identify priority areas for conservation (by degree of maturity of complexity)

Apply to remote sensing and flux tower data

Type 2: Contribute to the idea of a local optimum

Work should focus on distinguishing subtle differences between similar ecosystems in different stages of development

Questions

What makes a system complex? What distinguishes a complex adaptive system from a complex one?

What is the atmosphere (just complex, or complex adaptive)? The biosphere?

How specific should we aim to be with our measurements?

Can you imagine additional applications from the development of measurements other than what was suggested in the readings?