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OVERVIEW

Indian Ocean East Indian Ocean West Pacific Center West Pacific South Pacific North West Pacific Center East Atlantic Center East Atlantic North Others. P a. a. Harvest H a S a = R a - H a. b. R a = q R. S a. Spawn R = F ( S,b ). S. R. S a + S b. S +. Harvest H b

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OVERVIEW

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  1. Indian Ocean East Indian Ocean West Pacific Center West Pacific South Pacific North West Pacific Center East Atlantic Center East Atlantic North Others Pa a Harvest Ha Sa = Ra- Ha b Ra = q R Sa Spawn R = F(S,b) S R Sa + Sb S+ Harvest Hb Sb = Rb- Hb a Rb = (1-q)R Sb q b b Pb n = (b,q) Coop Coop Coop Hb = Pb(S,xb). Policy: Harvest Ha = Pa(S,xa), Coop Cost / price Cost / price Cost / price Annual Payoff: - schooling density: p - landing price, qa – catchability, 1998, Nov The Implications of Incomplete and Imperfect Information for Multinational Management of Transboundary Marine Fisheries: A Cooperative Research Project Robert McKelvey – U. Montana : Kathleen Miller – National Center for Atmospheric Research:Peter Golubtsov – Moscow State University, Russia SPLIT STREAM MODEL RESULTS OVERVIEW APPLICATION: MULTINATIONAL TUNA MANAGEMENT EEZ’s in the WCPO The Dynamic Imperfect Information Split Stream Harvesting Model • The Project: Setting and Program • Harvested marine fish stocks have been depleted worldwide. • The Culprit: Common Harvest of a breeding fish stock by non-cooperating fleets--The Tragedy of the Common • The Remedy: Central management by a governmental regulatory authority, to restrain and allocate harvests among fleets. • Complications: • Transboundary fish stocks, which migrate across zones of national authority, requiring multilateral cooperative management. • Stochastic stock demographics, due to oceanic environmental variability • (e.g. El Nino episodes.) • Inability to predict environmental regime shifts accurately, and in a timely way, so as to make current harvesting decisions optimally. • *** • The program: Examine alternative management institutions through case studies and game-theoretic modeling. Tuna Fisheries Worldwide: A Comparative Study • Species of tuna are found is all of the world’s oceans, in a wide variety of oceanographic, ecological, socioeconomic, and political circumstances. The goal here is to understand the implications of these differing conditions. • All tuna stocks are highly migratory, and thus their ranges may intersect the EEZs of many coastal nations. Furthermore, oceanic climates are often quite variable, so that the sites of high concentrations of a tuna stock may move great distances from year to year. Hence fish concentrations within any particular EEZ may fluctuate substantially. • Tuna are valuable market fish, and while some high-value species have been over-harvested, most stocks are not yet severely depleted. Thus, fishing fleets from many distant-water nations are attracted to all major tuna fisheries. • These circumstances complicate cooperative management, since there are a great many stakeholders, with differing rights and playing differing roles in the fishery. • The strategic model is designed to explore the impact of all these circumstances on effective fishery management, and the interrelations among the stake-holders. • Both the stock-recruitment parameter b and the stock-split parameter q are random and imperfectly observed. • Each fleet’s objective is to maximize the discounted sum of its annual payoffs to the time horizon T. Pacific Tuna Catch and the El Nino 3 Index 1995-1998 Influence of harvesting cost/price ratio for different knowledge structures.Symmetric game. Global Tuna Fisheries are Big Business • The Stochastic Imperfect Information Split-stream Game • A generic game, adjustable to describe various species-types, e.g. salmon, migrating along coastlines and small schooling species (sardines, anchovies) which are easily over-harvested and subject to large annual demographic variations. • A migratory stock splits into two sub-streams, each accessible to only one of two competing harvesting fleets. After harvest, the residual sub-streams reunite to form the brood-stock for the subsequent generation. • The new generation grows to maturity and once again splits into sub-streams. The growth and subsequent split processes both are stochastic, and imperfectly observed by the fleets. The process repeats annually. • Each fleet chooses its harvest policy to maximize the expected discounted sum of annual net payoffs over time, in response to the policy of its competitor. Thus it harvests to optimize the balance of immediate net return and its expected share of anticipated future returns. • The model demonstrates that, in non-cooperative harvesting, enhancing the quality of the fleets’ information may actually be destructive to both—thus contradicting the maxim that information transparency is always advantageous. • (Details on the far-right panel.) Thousand US $ Cur = full current knowledge, both fleets Min = minimum current knowledge (only probability distribution) both Cur-Min a = outcome for fleet a when it has full knowledge and fleet b has only minimal knowledge Cur-Min b = corresponding outcome for player b Knowledge structure: Effects of an El Niño All alternatives competitive unless marked Coop = cooperative Note Information Inversions i.e. enhancing information yields inferior outcomes Harvest of tuna by zones (1950-1997) Application to small schooling pelagics(e.g. sardines-anchovies) • Multilateral Management of Highly Migratory Stocks through a Regional Fisheries Management Commission (RFMC) • The RFMC Strategic Game Model assumes M countries with fleets and N coastal countries whose extended economic zones (EEZs) intersect the range of a highly migratory harvested fish-stock. Here M,N may be large, and while they may intersect, usually differ. • All of these stake-holding countries are members of the RFMC. The Commission makes long term policy for the fishery, gradually lowering the overcapacity of the fleets and thereby raising the brood-stock level for sustainability and profitability. It does this by negotiating annually the distribution of harvest capacity among the fleets and/or vessel days of harvest among the coastal states. • With these regulatory rules, it sets up annually a sequence of single-season competitive sub-games among the fleets and coastal states. Thus each coastal state sets its harvest-access royalties and allocates it’s vessel-days of harvest among the fleets, and each fleet allocates its vessel distribution among coastal sites. • The Tropical-Pacific tuna case, displayed on the central panel, illustrates the management issues to be addressed through this modeling analysis.(Currently the strategic model is being fine-tuned.) • Specifies symmetry in information but erratic temporal changes in stock growth and distribution. (Figures show mean values over time) • Usually the growth rate is high, and stock-split favors the a-site, but rarely the growth rate is small, with stock almost exclusively at b-site. The tight schooling favors over-harvesting. • The cooperative solution based on bargaining which is responsive to the asymmetries in the fleets’ competitive strengths. Note dominance of Pacific Center Region (i.e. Tropical Pacific) and the dominance of Pacific Center West over Pacific Center East • Management issues in the • Tropical Western Pacific • The new Western and Central Pacific Tuna Commission treaty came into effect in late 2004, with substantive debate in 2005. Unusually, the island states have been working together closely, especially the 8 “haves” (parties to the Nauru Agreement”). Their interests deviate from those of the 7 “sometimes haves” at the opposite pole of the El Nino cycle, plus Australia and New Zealand. • The harvesting nations do not cooperate, but instead compete with one another for access to the island state’s EEZs. Nevertheless, they retain the lion’s share of the returns from harvest. • The island states hope that, by further cooperation, they will achieve a higher share of harvest returns. To this end, they insisted on a voting system within the RFMC which gives them, collectively, a veto over its decisions. They also have insisted that the regulatory controls allocate vessel-days of harvest to them, rather than allocating harvesting capacity to the fleets. • Our RFMC model is designed to examine the effectiveness, and societal implications of these circumstances Varying the Fleets’ Risk Attitude Tropical Tuna in the Western Pacific: Specific Circumstances • Stock ranges are huge, and contain an unusually large number of coastal states, mainly island states, within the stocks’ range. Further most tuna are harvested within their EEZs rather than on the high seas. • However stock concentrations move about from year to year, across vast distances, following the loci of food concentrations, as determined by ocean currents and surface temperatures. • These tuna stocks are the largest and most valuable in the world, attracting many distant-water fleets (DWFs) worldwide. Few coastal states have substantial fleets of their own, and the DWFs take 85% of the catch. • Over time, stock-harvest has expanded dramatically, with total fleet size becoming excessive, so that stocks are increasingly vulnerable to over-harvest. • Risk attitude: risk averse for d < 1, risk neutral at d = 1; risk accepting for d > 1 • Note small inversion on left (where fleets highly risk averse), but not on right (where fleets mildly risk averse or mildly risk accepting) • As risk aversion increases (i.e. d→ 0) then competitive outcomes merge with cooperative outcomes.

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