1. The intersection of natural and social sciences as a source of innovative ideas for policy U. Rashid Sumaila Fisheries Economics Research Unit Fisheries Centre, University of British Columbia r.sumaila@fisheries.ubc.ca Keynote at FAME, University of Southern Denmark June 6, 2007

3. Peter’s Café in the Azores

4. General comments on interdisciplinary research Cross pollination is the mother of creativity; When you step into an intersection of fields, disciplines or cultures you can combine existing concepts into a large number of extraordinarily ideas; Johansson actually claims that innovation will be easier if we just focus on an intersection point.

5. Examples of innovation from intersection points Evolutionary biologist Charles Dawkins: –found an intersection point when he connected the field of genetic evolution with that of cultural evolution, suggesting that ideas evolve and propagate like genes; –He called the building blocks ‘memes’ and that notion today is the basis for marketing strategies seeking to ignite fads that might spread like viruses in the population of minds.

6. Examples of innovation from intersection points Marcus Samuel, the star chef at Aquavit in NY: –did it by combining Swedish culinary building blocks such as seafood, fresh ingredients and game with food from elsewhere in the world; –The results has been delicacies such as tandoori smoked salmon, sea urchin sausage & lemon grass yogurt; –Samuel achieved this by breaking the associative barriers between different fields of cooking, thereby stretching his ideas exponentially.

7. Thinking outside the box People who break down their associative barriers: –have generally exposed themselves to a range of cultures (geography, ethnicity, class, profession or organization); –are aware that there are multiple ways of approaching a problem, promoting divergent thinking and have a willingness to break the rulebook; –Samuel for example was born in Ethiopia; adopted by a Swedish couple; his adoptive father was a geologists who traveled a lot with him; –Not lucky to have Samuel’s experience – to break your associative barriers resort to reverse thinking!

8. Medici effect recommended Johansson spends time in his book to explaining to develop: –such transformative ideas; –how to overcome the difficulty of leaving your traditional network to mobilize the new idea; – how to break past the fear that such risky new ideas involve.

9. Eco(nomics/logy) The coincidence of the prefixes is thoroughly appropriate; The Greek root means household, and it signifies an interacting set of individual activities, both complementary and competitive with each other (for e.g.): –predator-prey in ecology; – economic growth in a country in economics.

10. Field of resource economics built on a 50+ yr model The Gordon-Schaefer model (1954); This model emerged from the interaction between an economist (H. Scott Gordon) and an ecologist (Milner Bailey Schaefer); What is the main implication of the G-S model?

11. To solve the problem of resource use We need cooperation among stakeholders; Environmental psychologists and experimental economists have shown that: –peoples’ behaviour not based only on monetary payoffs but also on non-economic factors such as reputation & social acceptance; –Games designed in non-economic situations lead more to cooperation. Implication: we need interdisciplinary studies to promote the needed cooperation.

12. The nature of things How time plays out

13. Concepts of value Ecologists: –An objective property of the resources. Economists: –An instrumental and marginal concept of values. Policy makers: –A combination of both(?)

14. Fish for today; fish for tomorrow Ecology wants (wild) fish forever; Does economics want the same? Does society, or should society, want the same? Is this goal achievable?

15. Should society want the same? “The Earth and the fullness of it belongs to every generation, and the preceding one can have no right to blind it up from posterity” (Adam Smith, 1766 Lecture on Jurisprudence). Photo: NASA

16. Is this an achievable goal?

18. Newfoundland cod

19. Fish biomass and fishing intensity Biomass; Fishing intensity. Fishing Intensity 1900 1999 Biomass Courtesy V. Christensen 1.8-2.5 1.5-1.8 1.2-1.5 0.9-1.2 0.7-0.9 0.6-0.7 0.4-0.6 0.3-0.4 0.2-0.3 0.1-0.2 0-0.1 0-0 Biomass t·km -2

20. North West Africa: Changes in key fisheries variables

21. State of fish stocks over time Source: Froese and Pauly (2004).

22. Can economics alone help? 1 st order problem: –Open access/common property. 2 nd order problem: –Sole ownership not sufficient: Why?

23. 2 nd order problem: Sole ownership … Will not necessarily capture all fish values (or total economic value; TEV); May suffer what I term the ‘frontloading’ problem.

24. The valuation problem The economic theory of valuation calls for the computation of TEVs made up of both use & non-use (market & non-market) values from fish; In theory it seems economics and ecology converge but do they in practice?

25. The practice of valuation Survey of 9 leading environmental & resource economics journals (1994-2003): # of articles published: 4705; # articles containing the words ‘non market’ or ‘existence value’ or ‘bequest value’: 43. Sumaila (in press)

26. The ‘frontloading’ problem PresentFuture Future benefits from today’s perspective Value “Egoism is the law of perspectives as it applies to feelings according to which what is closest to us appears to be large and weighty, while size and weight decrease with our distance from things” (attributed to Nietzche, 1844-1900). Discounting in economics

27. Clark and Munro(1975)

28. The optimal population trajectory x = x(t) and optimal population for different discount rates Adapted from a model developed by Clark and Munro (1975) xMxM Time, t Population, x xLxL xHxH x0x0 0 The basic bioeconomic model of Clark and Munro (1975)

29. The optimal population trajectory x = x(t) and optimal population for different discount rates Adapted from a model developed by Clark and Munro (1975) Low disc. rate xMxM Time, t Population, x xLxL xHxH x0x0 0 The basic bioeconomic model of Clark and Munro (1975)

30. The optimal population trajectory x = x(t) and optimal population for different discount rates Adapted from a model developed by Clark and Munro (1975) Medium disc. rate Low disc. rate xMxM Time, t Population, x xLxL xHxH x0x0 0 The basic bioeconomic model of Clark and Munro (1975)

31. The optimal population trajectory x = x(t) and optimal population for different discount rates Adapted from a model developed by Clark and Munro (1975) Medium disc. rate High disc. rate Low disc. rate xMxM Time, t Population, x xLxL xHxH x0x0 0 The basic bioeconomic model of Clark and Munro (1975)

32. Captured by Clark and colleagues Economics of overexploitation (Clark, 1973); Intrinsic growth rate of fish (r); The discount rate (d); d>r, could result in depletion of the stock.

33. Is discounting a problem? Individuals do not discount all future values at the same rate; Studies show that discount rates to be highest for choices involving relatively small amounts (Thaler, 1981; Hausman, 1979); Individuals appear to apply higher discount rates to amounts with a short delay than amounts to be received further into the future (Bonzion et al., 1989); Individual discount rates vary with personal characteristics, e.g., income (Gilman, 1976).

34. Alternative approaches proposed in the literature Zero discount rate: Problematic; Lower discount rate: How low? –Hyperbolic discounting (Ainslie, 1974); –Gamma discounting (Weitzman, 2001); –Intergenerational discounting (Sumaila, 2004; Sumaila and Walters, 2005).

35. Intergenerational discounting (Sumaila, 2004; Sumaila and Walters, 2005). Born out of interaction between economics and ecology; An attempt to integrate the fast and innovative nature of economics and the stabilizing nature of ecology; Links the ecologist ‘fish forever’ with the social scientist ‘ensuring fisheries benefits to future generations’.

36. Flow of 1 unit of benefit in current and discounted value

37. NPV accruing to each generation within 100 years based on conventional discounting

38. NPV accruing to each generation within 100 years based on intergenerational discounting

39. Intergenerational (IG) discounting: Discrete model Sumaila (2004)

40. Total discounted net benefits Status quo CM Restore CM Status quo GM Restore GM

41. Continuous time IG discounting Assumptions: –Present generation discount flows of benefits at standard rate; –New generation of size 1/G enters population each year: they discount at standard rate every year after entry; –Current generation as decision makers discount the interest of future generations at a ‘future generation’ discount rate at the time they enter the population. Sumaila and Walters (2005)

42. IG discounting tableau

43. The IG bioeconomic model Sumaila and Walters (2005)

44. Comments on IG approach AER: Axiom needed;

45. Comments on IG approach AER: Axiom needed; Time inconsistency;

46. Comments on IG approach AER: Axiom needed; Time inconsistency; Property rights to future generations; Rawl’s theory with a time dimension;

47. Comments on IG approach AER: Axiom needed; Time inconsistency; Property rights to future generations; Rawl’s theory with a time dimension; Group of mathematicians have used the IG formula to solved a conjecture; Will be having a lunch meeting with a UBC philosophy professor to discuss the idea;

48. Comments on IG approach AER: Axiom needed; Time inconsistency; Property rights to future generations; Rawl’s theory with a time dimension; Group of mathematicians have used the IG formula to solved a conjecture; Will be having a lunch meeting with a UBC philosophy professor to discuss the idea. Idea attractive to policy makers ….

49. Comments on IG approach AER: Axiom needed; Time inconsistency; Property rights to future generations; Rawl’s theory with a time dimension; Group of mathematicians have used the IG formula to solved a conjecture; Will be having a lunch meeting with a UBC philosophy professor to discuss the idea. Idea attractive to policy makers …;

50. Concluding remarks Scope for collaboration between natural and social scientists is huge;

51. Concluding remarks Scope for collaboration between natural and social scientists is huge; Do not be afraid to jump into the intersection of natural and social sciences because: this is where the most policy relevant research can take place;

52. Concluding remarks Scope for collaboration between natural and social scientists is huge; Do not be afraid to jump into the intersection of natural and social sciences because: this is where the most policy relevant research can take place; the career prospects for researchers in the interaction point is very bright;

53. Concluding remarks Scope for collaboration between natural and social scientists is huge; Do not be afraid to jump into the intersection of natural and social sciences because: this is where the most policy relevant research can take place; the career prospects for researchers in the interaction point is very bright; The career risk of being in the intersection point is decreasing.

54. Thanks for your attention Photo by Asep, TNC