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Understanding Risks and Uncertainties in Our Great Lakes Resources

Understanding Risks and Uncertainties in Our Great Lakes Resources. Dave MacNeill Fisheries Specialist New York Sea Grant SUNY Oswego 315-312-3042 dbm4@cornell.edu. high. med. Fish Population Size. ??. low. 0. Now. Past. Future. Time. (In) famous Quotes on Risk and Uncertainty.

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Understanding Risks and Uncertainties in Our Great Lakes Resources

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  1. Understanding Risks and Uncertainties in OurGreat Lakes Resources Dave MacNeill Fisheries Specialist New York Sea Grant SUNY Oswego 315-312-3042 dbm4@cornell.edu

  2. high med Fish Population Size ?? low 0 Now Past Future Time

  3. (In) famous Quotes on Risk and Uncertainty “They couldn’t hit an elephant at this distance… (thud)” General John B. Sedgwick, 1864 “A severe depression like that of 1920-1921 is outside the range of probability.”Harvard Economic Society, 16 November 1929 “No matter what happens, the U.S. Navy is not going to be caught napping.”Frank Knox, 4 December 1941 “The future just ain’t what it used to be.”Yogi Berra

  4. And now, my favorite….. “As we know, there are known knowns. There are things we know we know. We also know there are known unknowns. That is to say we know there are some things we do not know. But there are also unknown unknowns, the ones we don't know we don't know.”— Donald Rumsfeldt, Feb. 12, 2002, Department of Defense news briefing

  5. Theuncertainty: What poker hand will I draw next? Understanding the concepts of risk and uncertainties with a deck of cards?? The Dead Man’s Hand: unlucky for Wild Bill Hickok? The risk: What is the probability of drawing it? (<1%)

  6. But, the deck of cards changes unexpectedly, adding even more risk and uncertainty!! The Risk ??

  7. Uncertainty In The Great Lakes: • Major resource management dilemma from dynamics, complexity, instability of nature, economics, political systems and institutions on a global scale. • Poor ability to predict future environmental conditions, resource sustainability and responses to management actions. • Poor understanding of how nature really works. • Inability to make more effective management decisions. • Future funding to conduct/expand scientific resource assessment, research, development of better decision-making machinery???

  8. Those %$#@*&^ invasive species impacts and what’s next? Fisheries collapses/closures. Competing resource demands. Aggressive PETA anti-fishing/hunting campaigns. Anti-lead in fishing tackle. New environmental standards and regulations. New boat safety regulations. Client injuries. New insurance industry requirements. Meeting demands or expectations of new technologies/trends: here to stay or just a fad? Demographic changes in clientele. “Bird flu” or other pandemic. New political leadership. Economic recessions. Company turnovers, takeovers and closures. Economic effects of another 9/11 incident. Global temperature changes. Another “ice storm from hell.” Oil or contaminant spills. New fish/wildlife health issues. Flooding or low water events Seaway expansion impacts. Uncertainties/Risks facing Coastal Business Owners:

  9. The Uncertainty Toolbox • Modeling/forecasting • Mathematical descriptions of Great Lakes ecosystem that provides information on important relationships and permits trend analysis. • State of the art assessment/analytical tools • Improve the accuracy and precision of data collection process, and how data are analyzed and what data tell us. • Risk assessment • Using data to present managers, the public, local/state federal government and elected officials with probabilistic descriptions of the likely effects of alternative future management actions. • Risk communication • Informing of stakeholders, government, elected officials and managers of potential risks. • Human dimensions. • Risk management • Making decisions concerning risks/uncertainties and selecting a management option that provide optimal benefits. • Economic valuations • Information on $$ cost/benefits of management actions.

  10. GLOS is a subset of IOOS, the Integrated Ocean Observing System • An integrated, interdisciplinary system of remote observations; • Observations linked to modeling/ analytic machinery & communications. • Provides current and predicted data on ocean & Great Lakes conditions; • user-friendly data/information for decision-makers. • Partnerships: federal/state agencies, private sector and academia. • GLOS is one of 10 regional systems.

  11. Goals of IOOS and GLOS • Improve predictions of weather/climate change and effects on coastal communities and the nation; • Improve the safety/efficiency of maritime operations; • Mitigate the effects of natural hazards more effectively; • Reduce public health risks; • Protect/restore healthy coastal ecosystems more effectively; and • Enable the sustained use of ocean/coastal resources. The GLOS Project web site: www.glc.org/glos

  12. Example: Two fisheries management options Option 2. A. No uncertainty Option 1. Now, allow data to vary within normal bounds and run 1000 computer simulations using all possible parameter values (include uncertainty) for each management option: Option 2. 60% 80% Option 1. B. With uncertainty: option 1 C. With uncertainty: option 2

  13. Government Models “ingredients” Mother Nature Scientific knowledge Stakeholder interests Management goals Field Data $$ Management Decisions:Which one to pick?? The “best decision?” Decision analysis: “pros & cons” Decision-making “Machine” The “worst decision?”

  14. Making Decisions under UncertaintyAn Example of Decision Analysis: How do we select a new new jet fighter??

  15. How to decide on which of 5 jet fighters to buy: 5 fighters 4 Criteria 10 Attributes Top speed Operating altitude Maximum payload Range Performance Maneuverability Survivability Handling A good fighter Reliability Maintainability Serviceability Purchasing cost Operating cost Economics

  16. Data Used for Evaluating Fighters:

  17. Weight Assignment in Choosing a Fighter: 5 fighters 4 Criteria 10 Attributes Top speed 50% Operating altitude 10% Maximum payload 10% Range 20% 20% 4% 4% 12% Performance 40% Handling 30% Maneuverability 30% Survivability 70% 9% 21% A good fighter 100% 12% 8% Reliability 60% Maintainability 40% Serviceability 20% A perfect score 6% 4% Purchasing cost 60% Operating cost 40% Economics 10% 100%

  18. Weighting Data for Evaluating Fighters

  19. Evaluation Score 83.96%82.74% 89.53%84.00%83.23% 3 5 1 2 4

  20. Now the really important questions: • Should we automatically choose fighter #3 based on this process? • Should all decisions be made using such predictive models and decision analysis ?

  21. So,What’s the punch-line,Dave?

  22. The punch lines…… • We need to better integrate public/agency attitudes, goals and visions for Great Lakes. • We need to better assess, understand economic value of Great Lakes resources and integrate $$ into decision-making. • We need much more research!! • Expand monitoring/assessment of Great Lakes resources. • We must draw more attention to Great Lakes issues to get public, government and elected officials support. • We need more effective tools to better manage the Great Lakes. • We need focus more on holistic management the GL ecosystems, instead of separate parts. • We must all keep better informed about what is going on in the Great Lakes!!!

  23. NY Sea Grant Websites: • http://www.nysgextension.org/ • http://www.seagrant.sunysb.edu/

  24. Thank you!

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