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Geoffrey West Predictive Science of Cities Speed February 2012Atlas iedc san_antonio_geoffrey_west_slides

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Geoffrey West's Predictive Science of Cities Speech, given at the International Economic Development Council's Leadership meeting in San Antonio, Texas.

Geoffrey West's Predictive Science of Cities Speech, given at the International Economic Development Council's Leadership meeting in San Antonio, Texas.

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  • Emphasis on tot inc rate
  • Transcript

    • 1. IS A QUANTITATIVE, PREDICTIVE, SCIENCE OFCITIES CONCEIVEABLE? WHATCAN WE LEARN FROM PHYSICS & BIOLOGY? GEOFFREY WEST SANTA FE INSTITUTE SAID BUSINESS SCHOOL, OXFORD UNIVERSITY
    • 2. WE LIVE IN AN EXPONENTIALLY EXPANDING SOCIO-ECONOMIC (URBANISED) UNIVERSE!!1800 < 4% OF THE US POPULATION WAS URBAN2011 > 80%2006 > 50% WORLD’S POPULATION URBANISED2050 > 75% EVERY WEEK FROM NOW TILL 2050 OVER ONE MILLION PEOPLE ARE BEING ADDED TO OUR CITIES
    • 3. SOCIO-ECONOMIC ENTROPY!!
    • 4. NEED A SCIENCE OF CITIES “GRAND UNIFIED THEORY OF SUSTAINABILITY”ARE THERE UNIVERSAL, QUANTIFIABLE PRINCIPLES?COMPLEMENT TO TRADITIONAL (QUALITATIVE) THEORIES AND MODELS
    • 5. ARE CITIES AND COMPANIES JUST VERY LARGE ORGANISMSSATISFYING THE LAWS OF BIOLOGY? WHY DO ALL COMPANIES DIE WHEREAS ALMOST ALL CITIES SURVIVE?
    • 6. • METABOLISM• GROWTH• AGING/DEATH• EVOLUTION• SLEEP/REPAIR• DISEASE/CANCER
    • 7. THE SEARCH FOR UNDERLYING LAWS AND PRINCIPLES LEADING TO A QUANTITATIVE PREDICTIVE (COARSE-GRAINED) CONCEPTUAL FRAMEWORK [ENERGY & RESOURCES (METABOLISM) vs. INFORMATION (GENOMICS)]
    • 8. INTERSPECIFIC SIZE DISTRIBUTION All species in a Malaysian Rainforest 3 1947 2.5 N =log number of trunks 62 D- 1981 2.07 2 N = 55 D-1.95 1.5 1 0.5 1.5 0.5 2.5 1 2 3 log trunk diameter (cm)
    • 9. SCALABILITYRESILIENCE
    • 10. Mammals vary in size by8 orders of magnitude Shrew Elephant 2g 2,000,000g Blue Whale 200,000,000g
    • 11. 300 240Weight (g) 180 120 60 0 0 60 120 180 240 300 360 Age (day)
    • 12. SLOPE = ¾ < 1 SUB-LINEAR
    • 13. EXTRAORDINARY SYSTEMATICECONOMY OF SCALE (THE BIGGERYOU ARE, THE LESS NEEDED PER “CAPITA”)SIMILAR SCALING HOLDS TRUE FOR ALL PHYSIOLOGICALPROCESSES AND LIFE HISTORY EVENTS OVER THE ENTIRE SPECTRUM OF LIFE
    • 14. Metabolic rate sets the pace of lifesmall animals live fast and die young heart rate scales as -1/4 power of body mass
    • 15. NETWORKS!!!
    • 16. Relation between number andsize of branches within a tree
    • 17. INCOMING METABOLISED ENERGY  MAINTENANCE (of existing cells) + GROWTH (of new cells)
    • 18. BIOLOGY (LIFE)a) DOMINATED BY NON-LINEAR (UNIVERSAL) 1/4 - POWER SCALINGb) EXTRAORDINARY ECONOMIES OF SCALE (THE BIGGER YOU ARE, THE LESS YOU NEED PER “CAPITA”)c) PACE OF LIFE SYSTEMATICALLY SLOWS WITH INCREASING SIZE;d) GROWTH IS SIGMOIDAL REACHING A STABLE SIZE AT MATURITYe) NETWORKS
    • 19. ARE CITIES (AND COMPANIES)SCALED VERSIONS OF EACH OTHER? DO THEY MANIFEST “UNIVERSALITY”?
    • 20. Kuhnert, Helbing & West, Physica A363, 96-103 (2003)
    • 21. Example of scaling relationshipsa) Total WAGES per MSA in 2004 for theUSA vs. metropolitan population.b) SUPERCREATIVE employment perMSA in 2003, for the USA vs. metropolitanpopulation. SUPER-LINEAR SCALING
    • 22. Innovation measured by Patents
    • 23. TOTAL CRIME (JAPAN) Slope = 1.21 [1.08, 1.35]
    • 24. UNIVERSALITY
    • 25. THE GOOD, THE BAD & THE UGLY DOUBLING THE SIZE OF A CITY SYSTEMATICALLY INCREASES INCOME, WEALTH, NUMBER OF PATENTS, NUMBER OF COLLEGES, NUMBER OF CREATIVEPEOPLE, NUMBER OF POLICE, CRIME RATE, NUMBER OF AIDS & FLUCASES, AMOUNT OF WASTE,……….. ALL BY APPROXIMATELY 15% REGARDLESS OF CITY
    • 26. NETWORK DYNAMICS DETERMINES THE PACE OF LIFEIF THE SLOPE IS < 1 PACE OF LIFE SLOWS DOWNIF THE SLOPE IS > 1 PACE OF LIFE SPEEDS UP
    • 27. Pace of biological life vs. Pace of social lifeHeart Rate vs. Walking Speed vs. Body Size
    • 28. I. FINANCIAL MARKETS, ECONOMIES, GLOBAL WARMING, ENVIRONMENT, URBANISATION, HEALTH, CRIME, POLLUTION,………. ARE NOT INDEPENDENTTHEY ARE ALL HIGHLY COUPLED, INTER- RELATED COMPLEX ADAPTIVE SYSTEMS
    • 29. UNIVERSALITY OF SOCIALNETWORKS (CLUSTERING HIERARCHIES)
    • 30. II. ACCELERATION OF THREATS TOSUSTAINABILITY HAS ORIGIN IN SUPER -EXPONENTIAL URBANISATION
    • 31. III. NEED A NEW PARADIGM, A NEWINTEGRATED CONCEPTUAL FRAMEWORK:SYSTEMIC, HOLISTIC, QUANTITATIVE,PREDICTIVE
    • 32. CITIES AND URBAN LIFEa) SUPER-LINEAR DOMINATED BY INNOVATION & WEALTH CREATION THE BIGGER YOU ARE, THE MORE YOU GET PER CAPITA OF EVERYTHING FROM INCOME AND INNOVATION TO CRIME, POLLUTION AND DISEASE - ALL TO THE SAME DEGREE (~15% FOR EVERY DOUBLING OF SIZE)b) SYSTEMATIC INCREASE OF PACE OF LIFEc) UNBOUNDED GROWTH vs COLLAPSE
    • 33. Growth Equation
    • 34. N(t) N(0) tb<1 (SUB-LINEAR) BOUNDED GROWTH
    • 35. b >1 (SUPER-LINEAR)SUPER-EXPONENTIALUNBOUNDED GROWTH COLLAPSE
    • 36. UNBOUNDED GROWTH N(t) REQUIRES ACCELERATING CYCLES OF INNOVATION TO AVOID COLLAPSE N(t) N3(0) . N2(0) . N(t) N1(0) .N(t) N(0) t t tc
    • 37. UNBOUNDED GROWTH LEADING TO“FINITE-TIME SINGULARITY” & COLLAPSEUNLESS INNOVATIONS (SYSTEMATICALLY)OCCCUR FASTER AND FASTERCONTINUOUS TENSION BETWEEN:INNOVATION & WEALTH CREATION vsECONOMIES OF SCALE
    • 38. Population growth for New York City 1790 - 2003
    • 39. Successive cycles of superlinear innovation reset the singularity and postponeinstability and subsequent collapse. The relative population growth rate of NewYork City over time reveals periods of accelerated (super-exponential) growth.Successive shorter periods of super exponential growth appear, separated bybrief periods of deceleration. (Inset) tc for each of these periods vs. populationat the onset of the cycle. Observations are well fit with β = 1.09 (green line).
    • 40. Average “idealised, universal”characteristics of cities of a given size(constrained by underlying principles anddynamics of network structures -manifested in scaling laws)vs.Characteristics of specific cities asmeasured by deviations from scalinglaws representing their individuality andlocal environment and conditions
    • 41. 2003 Patenting Rankings5 Cornwallis, OR (1)4 SanJose (4)3 Bosto (107) n2 Pho i x (155) en10-1 Den (206) ver-2 NewY o (272) rk-3-4 Abilen (359) e-5 1 14 27 40 53 66 79 92 10 5 11 8 13 1 14 4 15 7 17 0 18 3 19 6 20 9 22 2 23 5 24 8 26 1 27 4 28 7 30 0 31 3 32 6 33 9 35 2
    • 42. Public sculptures cast in metal are being substituted with cheap plastic replicas to prevent them being stolen by thieves feeding the voracious appetite for commodities in China and India. 1 September 2011The Historic HousesAssociation said thisweekend that many statelyhome owners were puttingantique garden statues intostorage and displayingplastic copies instead.
    • 43. OUR “NATURAL” METABOLIC RATE ~ 90 wattsOUR SOCIAL METABOLIC RATE ~ 11,000 watts !!!WE ARE EQUIVALENT TO A 30,000 Kg GORILLA !!!REPRODUCTION RATE OF ~ ONE OFFSPRING PER 15 years
    • 44. JAMES BROWN (UNM/SFI) BRIAN ENQUIST (U. ARIZONA) WOODY WOODRUFF (LANL) VAN SAVAGE (HARVARD) JAMIE GILOOLLY (U. FLORIDA) DREW ALLEN (UCSB)MICHELLE GIRVAN (U. MARYLAND) ALEX HERMAN (UCSF) CHRIS KEMPES (MIT)
    • 45. LUIS BETTENCOURT (LOS ALAMOS/SFI - PHYSICS)JOSE LOBO (CORNELL/ASU - URBAN ECONOMICS)DEBORAH STRUMSKY (HARVARD/UNC - ECONOMICS)HYEJIN YOUN (SFI)MARCUS HAMILTON (SFI/UNM)NATHANIEL RODRIGUEZ (SFI)DIRK HELBING (ETH ZURICH - TRANSPORT/PHYSICS)ERICH RAUCH (PHYSICS/BIOLOGY - MIT/PRINCETON)DAVID LANE (U. REGGIO - STATISTICS/ECONOMICS)SANDER van der LEEUW (PARIS/ASU - ANTHROPOLOGY)DENISE PUMAIN (PARIS - URBAN GEOGRAPHY)SPYROS SKOURAS (ECONOMICS - U. ATHENS)
    • 46. PATRONS:NATIONAL SCIENCE FOUNDATIONGENE & CLARE THAW CHARITABLE TRUSTBRYAN & JUNE ZWAN FOUNDATIONROCKEFELLER FOUNDATIONMcDONNELL FOUNDATION

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