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Quantitative support tools to implement EBFM: decision-support systems and gaming technology. Villy Christensen University of British Columbia. On the Ground & In the Water: Ecosystem-based Fisheries Management in Practice 2009 Bevan Symposium on Sustainable Fisheries.
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Quantitative support tools to implement EBFM: decision-support systems and gaming technology Villy Christensen University of British Columbia On the Ground & In the Water: Ecosystem-based Fisheries Management in Practice 2009 Bevan Symposium on Sustainable Fisheries
http://celebrating200years.noaa.gov/breakthroughs/welcome.htmlhttp://celebrating200years.noaa.gov/breakthroughs/welcome.html NOAA celebrates 200 year
Numerous EwE models have in recent years produced credible fit to historical data made plausible policy predictions requires inclusion of environmental as well as fisheries impact 1950 2000 1950 2000 Fitting to time series: learning from ecosystem history
Modeling process: fitting & drivers Formal estimation Fishing Ecosystem model (predation, competition, mediation, age structured) Search for minimi-zation (Diet0) Log Likelihood Predicted C, B, Z, W, diets (Z0) (BCC/B0) Observed C,B,Z,W, diets Nutrient loading Habitat area Climate Judgmental evaluation Choice of parametersto include in final estimation (e.g., climate anomalies) Errorpattern recognition Christensen & Walters 2005
The models are widely used • Questionnaire responses from EwE users: 325 models constructed or under construction • 42% ecosystem structure; • 30% fisheries management; • 11% theoretical ecology; • 6% protected area evaluations Morisette 2007
But haven’t really had much impact on actual management • Partly because of lack of experience with EBFM • Partly because fisheries management is not EB • But, • Do we provide what’s needed? • Do we communicate in a comprehensible form?
Ocean Summits • How do you make the new Minister of Finance understand that selling licenses to foreign fleets or giving subsidies to increase the national fishing capacity may lead to lower catches, less income, higher cost, and social unrest? • We are developing an approach based on best available science, and incorporating realistic simulations of the ecosystem and its socio-economic environment
Challenge • Predicting the reactions of the ecosystem, economy and society to potential management actions represent a major challenge • We meet the challenge by designing a scenario-testing and -visualization gaming environment where alternative outcomes can be evaluated in a scientifically credible manner
Lenfest Ocean Futures Project Sherman Lai Mike Pan Jeroen Steenbeek Robyn Forrest Joe Buszowski Will and Carl Walters Villy Christensen Fang Gao Dalai Felinto Joe Hui Carie Hoover Four year project funded by the Lenfest Ocean Program
Ocean Summits Procedure Management procedure Operating model Climate model Assessment module (ecological, economical, social) Indicators Status Hydrographic model Policy scenarios Ecosystem – value chain model Strategy Visualization The strategy is set by the participants; arrows indicate flow of information
Ocean Summits methodology • Required elements • Redevelop EwE • Get models to talk together • The value chain • Spatial optimizations • Decision-support methodology • Visualizations • Communication
EwE6 overview Source code (live) available for download through cvs
Linking vs. Coupling • Connect using • Plug-in • .NET client • TCP-IP protocol Hydrographic model t =0 t = 1 . . . . T = n Hydrographic model t = 0 … n EwE model t =0 t = 1 . . . . T = n EwE model t = 0 … n file file
Model coupling: cooperative activities • Issues to tackle • Scale • Time • CSIRO: Atlantis • CEFAS: GOTM-BFM • OGS, Trieste: BGC • CSIRO: MSE framework • ROMS and climate models • NOAA GFDL/Princeton • FLEM/CBREEM linking • GAMS linking
Value chain modeling • Models the economic flow linked to thefood web • from sea to plate • Accounts for social aspects • jobs, salaries, dependents, … • detailed revenue and cost accounting • Handles aquaculture and non-extractive use, (e.g., whale watching)
Spatial optimizations • Ability to handle conservation layers (similar to Marxan)
Communicating the science We’re good with spreadsheets and graphs
Visualizations & decision-support • How has the system changed in historic time? • What is the current state • How may the system react to human impact and climate change? • Science aspects • How to visualize numbers • How to facilitate human-computer interaction • How to develop a cooperative environment
Visualizations - renderings • ‘Finding Nemo’ is rendered, image by image • We use a 3D gaming engine, Blender • We use rendering to make documentaries • Chesapeake Bay: 6 min’s video • Baltic Sea: planned
Visualizations - gaming • Real-time rendering • We have connected Ecosim to Blender • Currently used for two ‘games’ • Single player fishing game • Multi player decision support ‘game’
Multi player ‘game’ • Foundation for Ocean Summits • Two-way communi-cation!