BioComplexity: Rivers, BioComplexity: Rivers, Roads, and PeopleRoads, and People

EY592 BioComplexity SeminarEY592 BioComplexity Seminar

Spring 2004Spring 2004

Characteristics of Characteristics of ComplexityComplexity

nonlinear or chaotic behavior interactions that span multiple spatial and temporal

scales or levels unpredictable behavior (hard to predict) 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 the neighborhoods and industries of urban centers.

Goals of Biocomplexity Goals of Biocomplexity ResearchResearch

“understanding how components of the global ecosystem interact—biological, physical, chemical, and the human dimension—in order to gain knowledge of the complexity of the system and to derive fundamental principles from it” (Colwell, 2000).

Requirements of Requirements of BioComplexity ResearchBioComplexity Research

“examining the self-organization, hierarchical structure, and dynamics of communities and ecosystems over time and space requires new approaches and a new generation of nonlinear modeling, designed by collaborators in the natural, social, and computational sciences” (Covich, 2000).

Complex SystemsComplex Systems

Complex systems are often hierarchic Complex systems are often hierarchic (Pattee 1973, Allen and Star 1982).(Pattee 1973, Allen and Star 1982).

Simple laws or simple rules of behavior Simple laws or simple rules of behavior may generate complex behavior (Gleick may generate complex behavior (Gleick 1987; Wolfram 1984a,b). Thus, a 1987; Wolfram 1984a,b). Thus, a complex system does not necessarily complex system does not necessarily require a complex, long description (it require a complex, long description (it does not have to be ‘complex’ in the does not have to be ‘complex’ in the algorithmic sense). A complex pattern algorithmic sense). A complex pattern may be generated by simple may be generated by simple mechanisms, hiding an order that can be mechanisms, hiding an order that can be expressed in a compressed form.expressed in a compressed form.

In physics such phenomena are In physics such phenomena are exemplified by phase-transitions, broken exemplified by phase-transitions, broken symmetries, dynamical instabilities and symmetries, dynamical instabilities and self-organization (Anderson 1972, 1991). self-organization (Anderson 1972, 1991). Time-asymmetric self-organization -- Time-asymmetric self-organization -- from small and meso-scale phenomena from small and meso-scale phenomena to the cosmic scale, from the time of the to the cosmic scale, from the time of the big bang (with its simplicity and big bang (with its simplicity and featurelessness) to the present -- is a real featurelessness) to the present -- is a real phenomenon of the physical universe. phenomenon of the physical universe.

Complex SystemsComplex Systems

Complexity is a genuine historical phenomenon Complexity is a genuine historical phenomenon (Mayr 1982; Gould 1989), it takes long (Mayr 1982; Gould 1989), it takes long evolutionary time to generate complex patterns, evolutionary time to generate complex patterns, in nature as well as in formal systems (cf. Bennett in nature as well as in formal systems (cf. Bennett 1986; Lloyd and Pagels 1988).1986; Lloyd and Pagels 1988).

For complex living systems there are special and For complex living systems there are special and not fully understood relations betweennot fully understood relations between natural selection (which is non-directively ‘tracking’ the natural selection (which is non-directively ‘tracking’ the

environment as it changes randomly)environment as it changes randomly) developmental and other ‘constraints’ on natural developmental and other ‘constraints’ on natural

selection (Maynard Smith et al. 1985), andselection (Maynard Smith et al. 1985), and generation of organization ‘for free’ due to general generation of organization ‘for free’ due to general

principles of self-organization (Kauffman 1993). principles of self-organization (Kauffman 1993).

Complex SystemsComplex Systems

Complex emergent phenomena can be simulated (if Complex emergent phenomena can be simulated (if not realized, cf. Pattee 1989) by a computer, often by not realized, cf. Pattee 1989) by a computer, often by emulating an architecture of massive parallel emulating an architecture of massive parallel information processing, (i.e., information processing, (i.e., cellular automatacellular automata). The ). The computer is a prime instrument for studying computer is a prime instrument for studying complexity (e.g., Wolfram 1984a, Knudsen et al., complexity (e.g., Wolfram 1984a, Knudsen et al., 1991).1991).

For living beings, complexity reflects the genotype-For living beings, complexity reflects the genotype-phenotype duality and the crucial dependence on an phenotype duality and the crucial dependence on an informational mode of working of the system (von informational mode of working of the system (von Neumann 1966; Pattee 1977; Hoffmeyer 1996).Neumann 1966; Pattee 1977; Hoffmeyer 1996).

Complex SystemsComplex Systems

Hence, with the study of complex phenomena, time-Hence, with the study of complex phenomena, time-asymmetry, chance, irreversibility, and as a consequence, asymmetry, chance, irreversibility, and as a consequence, historyhistory has entered hard science (Prigogine and Stengers has entered hard science (Prigogine and Stengers 1984).1984).

Complex phenomena exhibit collective behavior on the Complex phenomena exhibit collective behavior on the

macro level, and involves often "spontaneous pattern macro level, and involves often "spontaneous pattern formation". These patterns can be seen as formation". These patterns can be seen as emergentemergent properties that are new (not pre-existing), properties that are new (not pre-existing), not trivially not trivially predictablepredictable, and , and characteristic of the whole, not its partscharacteristic of the whole, not its parts (Goodwin 1994; Baas 1994).(Goodwin 1994; Baas 1994).

It is conceivable (though controversial) that the emergent It is conceivable (though controversial) that the emergent

large-scale patterns can re-influence the small-scale large-scale patterns can re-influence the small-scale interactions that generated them, by a sort of ‘interactions that generated them, by a sort of ‘downward downward causationcausation’ (Campbell 1974; Andersen et al, in prep.).’ (Campbell 1974; Andersen et al, in prep.).

BioComplexityBioComplexity

Complexity is located between Complexity is located between high physical orderhigh physical order and and high high physical randomnessphysical randomness (Hogg & Huberman 1985), ‘on the (Hogg & Huberman 1985), ‘on the edge of chaos’, i.e., near the chaotic zone (in the sense of edge of chaos’, i.e., near the chaotic zone (in the sense of chaotic attractors in dynamical systems) where the system chaotic attractors in dynamical systems) where the system is sufficiently flexible and able to store, transmit and is sufficiently flexible and able to store, transmit and transform (‘compute’) information (Bak et al. 1988; Langton transform (‘compute’) information (Bak et al. 1988; Langton 1992; though see Mitchell et al. 1994).1992; though see Mitchell et al. 1994).

Complexity may need explanations of another type than Complexity may need explanations of another type than

simple reductionist ones; complex multi-level systems with simple reductionist ones; complex multi-level systems with biologic functions or with consciousness may need both biologic functions or with consciousness may need both effective, functional, form-like and intentional explanatory effective, functional, form-like and intentional explanatory modes (Kant 1790; Rosen 1985; Popper 1982; Emmeche modes (Kant 1790; Rosen 1985; Popper 1982; Emmeche et et alal. 1997).. 1997).

BioComplexity Research - BioComplexity Research - QuestionsQuestions

How do systems with living components respond and adapt to stress?

Are biological adaptation and change predictable in a changing environment?

How will climate change affect species’ ranges across multiple trophic levels?

Can we forecast the combined effects of climatic and socioeconomic change?

How does diversity (species, genetic, cultural) affect system sustainability?

BioComplexity Research - BioComplexity Research - ThemesThemes

universal scaling laws for biodiversity mathematical and biological modeling of

cell polarization dynamics of introduced and invasive

species, including diseases self-organization in planktonic ecosystems complex human–environmental

interactions, including the basis for land-use decision making

BioComplexityBioComplexity

IntegrationistIntegrationist ReductionistReductionist Multiple scalesMultiple scales

BioComplexityBioComplexity

Scaling lawsScaling laws

BioComplexityBioComplexity

Non-linear Non-linear Hydrosphere – Hydrosphere – Biosphere Biosphere interactionsinteractions

BioComplexityBioComplexity

Complexity at the Complexity at the edge of chaosedge of chaos

Self Organized CriticalitySelf Organized CriticalityStream NetworksStream Networks

Fractal drainage Fractal drainage networksnetworks

Optimality in Optimality in energy expenditure energy expenditure principlesprinciples

Optimal channel Optimal channel networksnetworks

Downstream Downstream hydraulic geometryhydraulic geometry

Self Organized CriticalitySelf Organized CriticalityStream NetworksStream Networks

FIG. 1: The Full Hack distribution for the Kansas, (a), and Mississippi, (b), river basins. Area a and length l are in m2 and m respectively. For each value of a, the distribution has been normalized along the l direction by max l P(a; l) [49].

Complexity - NetworksComplexity - Networks

World Wide WebWorld Wide Web