Economic and biological analysis to aid system planning for salmon recovery in the Columbia River Basin

Journal of Environmental Management (1995) 43, 313-331

Economic and Biological Analysis to Aid System Planning for Salmon Recovery in the Columbia River Basin Kris Wernstedt and Charles M. Paulsen Quality of the Environment Division, Resources for the Future, 1616 P Street, NW, Washington, D.C., U.S.A. Received 24 February 1994

Runs of salmon in the Columbia Basin in the north-western United States have declined dramatically over the past 50 years, due to hydropower development, habitat degradation, over-harvest and other causes. This article describes a suite of models that analyze the biological effectiveness and financial costs of strategies designed to meet harvest and escapement goals for nearly 80 stocks of salmon simultaneously. Results suggest that finding a cost-effective solution requires that all aspects of the salmon life-cycle must be analyzed simultaneously. Policy implications and difficulties in using this modeling approach to inform regional decision-making also are discussed.

Keywords: cost-effectiveness, biological modeling, systems analysis, Columbia River Basin, salmon.

1. Introduction Scientists estimate that in the last 100 years, the annual production of adult salmonids in the Columbia River Basin in the north-western United States has declined by 75 to 85%, from 12 to 16 million to 2 to 3 million (Northwest Power Planning Council, 1987). Some salmon stocks--salmon populations which spawn in a particular subsystem of the river at a particular season and generally do interbreed with other populations from other subsystems or of different breeding seasons--already are extinct, while others have dangerously low populations. In the last 3 years alone, under the guidelines of the 1973 U.S. Endangered Species Act (ESA), the U.S. National Marine Fisheries Service (NMFS) has declared one wild stock of sockeye salmon endangered and two wild stocks of chinook salmon threatened. N M F S also has pronounced one wild stock o f lower-river coho salmon petitioned for listing to be already extinct as a wild species. The American Fisheries Society has identified more than 70 additional stocks in the quarter-million square-mile U.S. portion o f the Columbia Basin as being in some danger of extinction or warranting special concern (Nehlsen et al., 1991). A number of forces have contributed to the decline of the salmon runs throughout the Columbia Basin. Economic activities such as logging, mining, grazing, farming and 313 0301-4797/95/040313+ 19 $08.00/0

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fishing have degraded salmon habitat and water quality, appropriated water critical for salmon survival, introduced barriers to upstream and downstream salmon migrations, and harvested increasingly scarce adult populations. The construction of dams for hydropower, irrigation and flood control have completely blocked off spawning and rearing habitat above Chief Joseph Dam on the Columbia River and Hells Canyon Dam on the Snake River (see Figure 1). The dams also have made upstream and downstream migrations more difficult on the run-of-river dams on the lower-Snake and mid- and lower-Columbia. The reservoirs behind the dams have greatly slowed the downstream migration of juvenile salmon (smolts), thereby increasing their mortality from predator fish and making their physiological transition from freshwater to saltwater more difficult. Hydrosystem operators have altered the natural runoff in the river system by storing water during peak runoffs and releasing it to generate electricity when energy demand warrants it. Thus, the natural seasonal variation in river flow--peak runoff in the late-spring freshet and lower runoff during the fall and winter months--have given way to more modulated flows to meet energy demand, with multiple peak flows (winter and spring months), and the lowest flows in late summer. Efforts to rebuild salmon stocks have been underway for more than 50 years. The Bonneville Power Administration (BPA), the federal authority established in the 1930s to market power produced by the federal hydroelectric dams in the region, has funded many of the actions designed to rebuild salmon populations. For the last several years analysts from several organizations have been working with BPA to develop a capability to model the life cycle of salmon populations and to conduct a system-wide costeffectiveness analysis of actions proposed to assist the rebuilding. The goal of the costeffectiveness analysis is to help regional policy makers systematically and comprehensively to evaluate the costs and biological effects of alternative rebuilding actions for stocks located throughout the Columbia Basin. In the remainder of this paper we discuss the formulation and results of the costeffectiveness analysis. Our analysis focuses on system-wide planning for nearly 80 stocks in the Basin, including both stocks listed for protection under the ESA and stocks that are not currently listed. Section 2 provides background to the work. Section 3 presents an overview of the models used in the analysis, while Section 4 discusses the actions evaluated in the analysis and the fish production objectives that the actions are attempting to meet. Section 5 furnishes results. Sections 6 discusses policy implications for the Pacific Northwest. We conclude in Section 7 with comments on characteristics of the approach that may suggest broader lessons for those interested or engaged in systematic methods for evaluating trade-offs between costs and environmental quality at the regional level.

2. Background Since passage of the Pacific Northwest Electric Power Planning and Conservation Act of 1980 (Northwest Power Act), efforts to rebuild salmon stocks in the Columbia Basin have intensified. The Northwest Power Planning Council (Council), which was created by the Northwest Power Act, developed and has amended several times the Columbia Basin Fish and Wildlife Program. The program provides the framework for investments in activities designed to protect, mitigate and enhance fish and wildlife affected by hydropower development. These activities include changes in the amount and timing of river flows; construction and operation of bypass facilities at run-of-river dams (dams with little or no reservoir storage capacity) to route downstream migrating smolts

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around turbines; removal of smolts from the river and transportation of them in barges to a release point below Bonneville Dam (see Figure 1); reduction of predator populations in the reservoirs; introduction of hatchery programs; and numerous habitat improvement, barrier removal and irrigation diversion screening actions in the individual subbasins of the Columbia Basin. In the 1980s, BPA invested about $1 billion to rebuild Columbia River salmon runs and wildlife populations. Current costs of BPA efforts to preserve fish runs are $350 million annually (BPA, 1991, 1993, 1995). Under the terms of the Northwest Power Act, the fish and wildlife program must include measures which are supported by the best scientific evidence available and which "utilize, where equally effective alternative means of achieving the same sound biological objective exist, the alternative with the minimum economic cost". The Northwest Power Act also directs that the protection, mitigation and enhancement efforts of the fish and wildlife program be designed, to the greatest possible extent, to deal with the Columbia River and its tributaries as a system, while assuring an adequate, efficient, economical and reliable supply of power to the Pacific Northwest (16 U.S.C. ~839b). The analysis presented here relies on a modeling framework to assess the biological effects and financial costs of fish and wildlife program measures aimed at enhancing salmon populations. It adopts a system-wide approach, by addressing those measures which promote salmon production in individual sub-basins (sub-basin propagation), the harvest of returning adults in the sub-basins (terminal harvest) and downstream passage actions on the mainstem Columbia and Snake Rivers, for nearly 80 wild and hatchery stocks of chinook salmon and steelhead. Our goal is to contribute useful information to decision makers who are interested in system-wide least-cost planning for mitigation or in exploring trade-offs among passage and propagation costs, fish production measures and maintenance of the genetic integrity of wild stocks. 3. Methods

The system-wide analysis is designed to find the cost-effectiveness frontier, the locus of

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the least-cost combinations of sub-basin propagation, passage and terminal harvest actions which meet varying stock-specific objectives. The derivation of the frontier rests on the application of a suite of computer models, with outputs from one model serving as inputs to another. This section briefly describes each model's general logic and role in the cost-effectiveness analysis [see Paulsen et al. (1993a) and Paulsen and Wernstedt (in press) for more detailed presentations of the models]. Figure 2 depicts the relationships among the models and the flow of inputs to and outputs from each. 3.1. SYSTEM ANALYSIS MODEL

Regional power planners in the Pacific Northwest developed the system analysis model (SAM) to simulate the operation of the region's hydroelectric and thermal power system to meet demand for capacity and energy within the region (PNUCC, 1983). SAM addresses concerns with the variability inherent in power planning, with the natural water conditions in the region and energy demand being the major variable elements. Generally, each run of the simulation model covers a 20-year planning horizon and 50 historical water years. SAM can model different levels and timing of turbine and spillway flows for fish (the survival of smolts over spillways is higher than that through turbines, so flows routed through a spillway can enhance smolt survival). The result of incorporating the fish flow requirements, energy demand, natural runoff and other constraints yields a set of regulated flows at each hydroelectric project. The SAM output from each modeled flow and spill scenario consists of the regulated flows at each mainstem hydroelectric project for each water year modeled, and the average costs of running the power system to meet demand. We express the costs of each scenario relative to a base-case cost (pre-ESA power operations), so the costs represent the marginal cost of operating the power system under different flow and spill scenarios.

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COLUMBIA RIVER SALMON PASSAGE MODEL

The Center for Quantitative Science at the University of Washington developed the Columbia River Salmon Passage Model (CRISP) to simulate the downstream migration of salmon and steelhead smolts from their initial entry into the mainstem Columbia and Snake Rivers to a point below the most downstream dam on the Columbia River. In the version of the model that we used, CRISP accounts for smolt mortality due to passage through turbines, bypass facilities, spillways and sluiceways at all of the 13 mainstem dams, and mortality associated with passage through the reservoirs [see Hinrichsen et al. (1991) for documentation of the CRISP model]. The regulated flows from SAM drive the hydrologic component of the CRISP model. CRISP allows the choice of several functional forms for expressing the relationship between flows and fish survival, different levels of effectiveness of predator control programs, alternate timing of entry to the mainstem by each stock's smolts, and various survival parameter values for different dam passage routes and barge transportation of smolts [over 17 million smolts were transported by barge in 1992 (U.S. Army Corps of Engineers, 1992)]. For each combination of passage actions modeled in CRISP, the calculated mean passage survival for each stock is used as input in the life-cycle model.

3.3.

DETERMINISTIC LIFE-CYCLE MODEL

The deterministic life-cycle model (DLCM) simulates the entire life-cycle of anadromous salmon and steelhead. We designed the DLCM to mimic the basic factors regulating populations of Pacific salmonids and to be relatively simple and computationally fast. The models needs to run fast because it has to generate information on the biological effectiveness of nearly 100 000 alternative management strategies. The number of such strategies is so large because we are combining passage actions, sub-basin propagation actions and variable sub-basin harvest rates, and because we are analyzing multiple stocks simultaneously. The simulation model divides the salmonid life-cycle into several stages, with each stage linked to the preceding one by the proportion surviving from one stage to the next. Inputs to the model include parameters describing the number of eggs per female each year, the proportion of fish surviving from one stage to the next (downstream passage survivals from CRISP, for example), and harvest and hatchery broodstock requirements. Model outputs of interest for each stock include the number of fish caught in the sub-basins and the number of adult fish that escape to the sub-basin to spawn, at equilibrium (generally at 40 to 50 years). After calibrating the DLCM, one can model the effects of management actions at the downstream passage, terminal harvest and propagation (spawning and rearing) stages by changing the survival proportions. This results in different equilibrium population sizes for each propagation strategy/terminal harvest rate/passage strategy alternative. The model is essentially a deterministic variant of the stochastic life-cycle model developed by Lee and Hyman (1992) and used by the Bonneville Power Administration in its analyses of endangered chinook salmon stocks. Unlike the stochastic model, the DLCM models long-term average population levels. In the abstract, this is undesirable since it fails to capture the year-to-year variability that all stocks experience (even stable ones with relatively constant long-term average populations). However, because the spawning escapement and terminal harvest goals that we took from planning

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documents in the region are formulated as long-term averages, with no explicit goals for reducing variability, the deterministic model suffices in this context. The deterministic model would not be suitable for analyzing low-abundance fish stocks, however, because random events could force a stock to extinction, even if the population were stable or even increasing [see Paulsen et al. (1993b), Montgomery and Brown (1992), and Dennis et al. (1991) for examples of stochastic models used in the analysis of endangered species]. 3.4.

BASIN-WIDE SCREENING MODEL

The system-wide screening model that we developed processes cost data for passage and sub-basin propagation actions and outputs from the deterministic life-cycle model, in order to select the system-wide strategy which meets terminal harvest and spawning objectives for each stock at lowest cost. The model uses linear programming techniques to find the least-cost solution from a large number of possible management strategies. Multiple runs of the model with varying objectives (see Section 4.2) yield different leastcost management strategies, and allow policy makers to explore the biological and financial trade-offs among different objectives. Because only passage and propagation strategies have financial costs, the cost minimization objective can be represented simply as: Minimize Z(PASSm x CPASSm) + E Z(PROPi., x CPROP;.,), where PASSm=passage strategy m; PROPi,~=propagation strategy n in sub-basin i; CPASSm = cost of passage strategy m; CPROPi,~ = cost of propagation strategy n in subbasin i. Other than the constraints on fish production to ensure that the passage, propagation and terminal harvest activities meet the spawning and harvest objectives, all other equations in the model will be mass balance constraints. With the exception of the passage and propagation cost coefficients, all coefficients in the linear programming formulation are set at - 1, 0 or 1, so all model activities (passage strategies, propagation strategies or terminal harvest actions) will take on the value of zero or one. One either implements a passage, propagation or terminal harvest alternative in full or not at all. The model can be viewed as a transshipment problem [see Gass (1985) for an explanation of why all decision variables will take on only integer values]. This is important because it allows an integer solution to be found without resorting to impractical (for a problem of this size) pure or mixed-integer programming.

4. Mitigation actions and regional objectives The mitigation actions modeled in the cost-effectiveness analysis, as well as the objectives that the mitigation actions are designed to meet, come from planning documents developed in the Pacific Northwest over the last several years. This section briefly discusses the costs and biological effects of the .mitigation actions and the regional objectives set by planners in the region. 4.1.

COSTS AND BIOLOGICAL EFFECTS OF MITIGATION ACTIONS

The cost-effectiveness analysis of prospective management actions assesses the financial

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costs and biological effects of sub-basin propagation and downstream passage actions, and the biological effects of terminal harvest restrictions (terminal harvest alternatives are assumed to have no financial costs). The sub-basin propagation actions come largely from the sub-basin planning documents developed under the auspices of the Columbia Basin Fish and Wildlife Authority (CBFWA, 1990) and the Northwest Power Planning Council. These plans provide quantitative estimates of the costs and anticipated biological effects of proposed sub-basin actions. The proposed actions can be categorized roughly into four types: (1) initiation or expansion of hatchery programs; (2) improvement of habitat; (3) screening of irrigation diversions; and (4) removal of barriers to adult spawners. The passage strategies analyzed consist of combinations of flow alternatives, smolt transportation, and predator control. The two flow scenarios considered are: (1) 1990-1991 operating conditions; and (2) flows called for in the Council's Phase II amendments to the downstream passage portion of the Fish and Wildlife Program (Northwest Power Planning Council, 1991). Transportation actions include: (1) full barge transportation of all smolts at the four current transportation projects (Lower Granite, Little Goose, Lower Monumental and McNary in Figure 1); (2) barge transportation of only summer and fall chinook smolts at the current transportation projects; and (3) no barge transportation of smolts. Predator control actions are: (1) reduction in predator populations to allow a 50°/'odecrease in predation mortality; and (2) no predator control. Other system characteristics such as the efficiency of fish bypass systems, the survival of smolts in transportation, and turbine and spillway mortality do not vary among the passage strategies. The various flow, transportation and predator control actions are combined in different ways to yield nine passage strategies. The analysis also evaluates different assumptions about the efficacy of some of the passage actions, to investigate the sensitivity of the cost-effectiveness results to these assumptions. Specifically, we decreased the assumed smolt transportation survival for each stock by 50%, lowered the estimate of the reduction in predator mortality due to predator control from 50 to 25%, and reduced the fish guidance efficiencies of the bypass systems at each project by 25%. 4.2. OBJECTIVES The system-wide cost-effectiveness analysis identifies the set of passage, propagation and terminal harvest alternatives which meet a set of stock-specific numerical objectives at lowest cost. We investigated two sets of objectives: the terminal harvest and spawning escapement objectives specified in each Columbia Basin Fish and Wildlife Authority (1990) sub-basin plan; and the objective of doubling the runsize of the stocks, as called for by the Council's fish and wildlife program (Northwest Power Planning Council, 1987). In this analysis, we attempted to meet a doubling of the runsize of each stock in the sub-basin, which is a more strenuous objective than the doubling of the aggregate (across all stocks) runsize specified in the Council's document. For some stocks, the terminal harvest, spawning escapement and/or runsize objectives could not be achieved with any strategy, in which case we reduced the stated objectives until at least one strategy could meet them. In addition to trade-offs between costs and different levels of fish abundance, other less-specific goals and constraints of the fish and wildlife program exist. For example, program managers may be reluctant to rely on hatchery production to augment a weak stock, because of the potential genetic risk associated with introducing hatchery fish

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into a wild population (Northwest Power Planning Council, 1993). The analysis incorporates this "genetic integrity" goal with a scenario that omits those propagation strategies that have a high risk of compromising the genetic integrity of wild stocks. It also investigates the cost and biological implications of adopting increased river flow as a goal--increased flow itself as an objective, rather than just a possible strategy for meeting a numerical abundance objective--by including a scenario that omits those strategies that have low flows. Both the genetic integrity scenario and the increased flow scenario may generate least-cost alternatives that differ from those generated under the more general case of no genetic or flow restrictions, at one or more levels of fish abundance. The least-cost, constrained alternatives need not differ from the least-cost, unconstrained alternatives, however. For example, in the case of the genetic constraint, if at a particular level of fish abundance the cost-effective alternative identified in the unconstrained, more general case contains only those propagation strategies with low genetic risk, then the alternative identified in the constrained case will contain exactly the same strategies. At the extreme, if the cost-effective alternative for each level of fish abundance contains only low-risk strategies, the cost-effectiveness frontiers for the constrained and unconstrained cases will be identical.

5. Results

Tables 1 through 3 and Figures 3 through 5 depict some of the major results of the cost-effectiveness analysis. This section first discusses how the passage and propagation costs of the recovery alternatives change with the addition of constraints, and then shows how the composition of the prop~igation alternatives differs among sub-basins. It concludes by examining the cost-effectiveness frontiers generated by varying the harvest and spawning escapement objectives.

5.1. TOTAL COSTS

Table 1 summarizes the results for seven scenarios or combinations of biological objectives, passage sensitivity and genetic risk. Total annualized costs for the seven scenarios range from $12.7 million to $89 million per year, with these total costs disaggregated into passage and propagation expenditures as shown. Several features of the results deserve mention. First, the screening model almost always selects 1990-1991 (no additional) flows. (Although not shown directly in Table 1, the model always selects predator control and full transportation.) Only in scenario 2, which forced the model to select the Council's phase II flows in order to assess the implications of requiring increased flows, do 1990-1991 flows not appear. In comparing scenarios 2 and 3, which are identical in their passage sensitivities, numerical objectives, level of acceptable genetic risk and preferred propagation strategy (not shown directly in the table), we can see that the requirement for phase II flows appears to yield a system-wide strategy to meet the planners' objectives that costs $70 million more annually than the systemwide strategy identified by the screening model. This result rests on the assumptions regarding the relationship between reservoir flows and smolt survival in CRISP.0. Given the tension among the popularity of increased flows, the apparent large cost and limited effectiveness of these flows, and the biological importance of enhancing survival for

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many stocks above Bonneville Dam, the results indicates to us that the region needs to continue and extend its investigation of downstream survival. Second, if we ignore sub-basin escapement and focus only on the terminal harvest objectives, not surprisingly costs decrease significantly. Table 1 suggests that attaining only the terminal harvest objectives for each stock (scenario 1) will cost roughly twothirds as much as attaining both the terminal harvest and natural spawning escapement objectives for each stock (scenario 3). This result prevails because scenario 1 allows high terminal harvest rates, which are financially costless, and mitigates these with extensive hatchery production. In reality, of course, this may be only a short-term solution for maintaining high harvest levels. Third, the addition of a constraint on acceptable genetic risk in Table 1 appears to make a cost difference for only a small number of stocks in the system-wide costeffective strategy. After initially imposing the genetic constraint to simulate scenario 4, we saw that no analyzable propagation alternatives (with costs and biological effects) with acceptable genetic risks existed for spring chinook in several sub-basins (Hood River sub-basin, Bear Valley in the Salmon River sub-basin and the Lemhi River subbasin), and that passage strategies alone could not meet the objectives for these stocks. After relaxing the genetic risk constraint for these stocks, however, the screening model selected the same passage and propagation strategies for scenarios 3 and 4, which are identical except for the genetic constraint. In other words, except for the stocks with no low-risk propagation alternatives, the constraint on genetic risk did not affect the composition or cost of the least-cost, system-wide strategy. (The Bear Valley and Lemhi River spring chinook stocks are on the federal threatened species list, however, so they are important exceptions.) Fourth, in contrast to the minor effects of the genetic risk constraint, alteration of assumptions regarding the efficacy of passage actions substantially affected the costs and choice of preferred propagation strategies. In Table 1, scenario 5 differs from scenario 3 only in the more pessimistic passage assumptions concerning fish guidance efficiencies (FGE), predator control effectiveness and transportation survival included in scenario 5. However, the different assumptions result in considerably higher costs for propagation strategies ($13.9 million per year versus $10.0 million). In addition, although not shown in Table 1, we were forced to reduce the objectives for Tucannon steelhead, Bear Valley spring chinook, and Pahsimeroi summer chinook by I0 to 50% to model scenario 5, since under the low FGE of scenario 5, no combinations of propagation and passage could meet their spawning and harvest objectives. Fifth, the analysis of the preferred propagation strategies identified in the sub-basin plans indicated that the planners' strategies cost considerably more and sometimes do not yield harvest and spawning escapement levels that meet the objectives. Scenario 7 displays the results of modeling the preferred propagation strategies, which are identified in the Columbia Basin Fish and Wildlife Authority (1990) sub-basin plans, in combination with each of the nine passage strategies and allowing the terminal harvest rates to vary in the same fashion as in the other model runs (0 to 80% in 20% increments). From Table 1, one can see that the cost of the planners' preferred propagation strategies ($18.0 million annually) greatly exceeds the cost of the propagation strategies identified by the screening model ($10"0 million annually in the comparable case, scenario 3). Additionally, the planners' preferred strategies did not meet the terminal harvest and spawning escapement objectives met in the other scenarios (i.e. scenarios 2, 3, 4 and 5) for several stocks. (In some sub-basins, we could not

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include some of the planners' preferred actions in our model, because we had no biological or cost data on the actions.) Finally, doubling the runsize of each stock may entail higher costs than meeting the terminal harvest and spawning escapement goals specified in the sub-basin plans. Scenario 6 in Table 1 summarizes the results of modeling the runsize doubling goal. The model selects a substantially higher-cost group of propagation strategies in comparison to the terminal harvest/spawning escapement goals in scenario 3 ($14.9 million versus $10-0 million per year), and again selects 1990-1991 flows. The runsize doubling goal entails substantially lower terminal harvest rates for most stocks, since reducing harvest rates increases total runsize at no financial cost. 5.2.

COMPOSITION OF PROPAGATION ALTERNATIVES

The total cost of propagation strategies can vary widely among the different scenarios, from $3-7 million annually to $18-0 million annually (Table 1). The variation becomes more pronounced when one looks at the disaggregated propagation strategies for individual sub-basins. Table 2 shows that the cost of the preferred propagation strategy for any given sub-basin can vary greatly among scenarios, and that the cost of the propagation strategies among different sub-basins can vary greatly within any given scenario. As an example of the former variation, Table 2 shows that the Klickitat subbasin has a propagation cost of zero for two scenarios, and a maximum propagation cost of $1-254 million for the planners' preferred strategy. As an example of the betweensub-basin cost variation, note the wide variation in propagation costs in the average passage assumption, model-selected propagation action scenario for the harvest and escapement objective (column 2 in Table 2). Five sub-basins have a propagation cost of zero (and therefore evidently require no propagation actions to achieve their terminal harvest and escapement objectives), 15 additional sub-basins need propagation strategies that cost less than $500000, five sub-basins require propagation strategies that cost between $500 000 and $1 000 000 annually, and one sub-basin has a cost that exceeds $2"7 million annually. With more pessimistic assumptions regarding the efficacy of passage actions (the rightmost column of Table 2), four sub-basins still require no propagation actions, eight require expenditures between $500 000 and $1 000000 annually, and two sub-basins have costs that exceed $2.7 million annually. (In one case, we end up with higher costs under the higher FGE assumption than with the lower FGE assumption because, as mentioned earlier, we arbitrarily reduced some of our original objectives if no strategy could meet the objectives under the low FGE assumption.) Table 3 shows the preferred propagation actions for five sub-basins with significant propagation expenditures. An " x " in the entry for each action and scenario indicates that the model solution for the scenario includes the action identified in the row, while a blank indicates its exclusion. The table highlights several points. First, recall from earlier discussion that the scenarios with terminal harvest/spawning escapement objectives and average passage assumptions and the scenario with planners' preferred propagation actions and average passage assumptions have the same set of terminal harvest and spawning escapement objectives. However, the planners' strategies did not meet the numerical objectives for several stocks, and the planners' recommended propagation actions cost more in total than those suggested by the screening model. For example, as Table 3 shows, the planners suggested six actions in the Klickitat subbasin, while the screening model identified the need for no propagation actions. Similarly,

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TABLE 2. Propagation costs for 100% solutionst Sub-basin

Clearwater Deschutes Entiat Grande Ronde Hood River Imnaha John Day Klickitat Little White Methow Okanogan Bear (Salmon) Lemhi (Salmon) Lower Salmon Mid-Salmon Panther (Salmon) Pahsimeroi (Salmon) S. Fork Salmon Little Salmon Upper Salmon Tucannon Umatilla Wind River Wenatchee White Salmon Walla Walla Total prop. cost

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0.205 0"279 0 2.709 0"313 0.330 0.739 0 0"006 0 0-005 0" 188 0"867 0.188 0.867 0.469 0 0"380 0.189 0.716 0.0166 0-419 0.495 0 0.017 0.633 10"031

0.370 0.474 0-081 1.578 0"238 0.234 0.799 0-039 0-006 0-052 0.000 0"000 0"679 0.882 0.679 0-036 0-664 0.380 0-807 2-225 0-022 3-169 0-556 0-000 0-035 0.856 14-862

0.845 0.661 0"027 2.030 0"245 0.563 0-825 1.254 0"346 0-708 0-334 na 0"867 na na 0.699 0.664 0.229 0.807 0-724 0"069 3" 169 0"709 0" 185 0.469 1.60 18.032

0.205 0"301 0 2.709 0"313 0.563 0.739 0 0-006 0-173 0.299 0" 189 0-867 0.189 0.867 0.469 0 0.569 0.189 0-716 0 2-842 0-495 0.582 0"017 0"633 13.932

t Costs in millions of dollars, annualized at a 3% real discount rate. Passage strategies for all cases are current conditions (1990-1991 flows with planned improvements to bypass and transport facilities) and predator control, with an annual cost of 9-0 million dollars. :~Objectives are harvest and spawning escapement (harvest/spawn) and runsize doubling (run doubling). The propagation actions are identified by the model (model prop.) or specified by the sub-basin planners (planner prop.). Sensitivity runs for passage are "average" assumptions on the etiicacy of fish guidance efficiencies (FGE), transportation survival and predator control (avg. passage), or "low" assumptions, with fish guidance efficieneies reduced by 25%, transport survival by 50%, and predator control efficacy by 50% (low passage).

the planners r e c o m m e n d e d three actions in the U p p e r S a l m o n sub-basin, while the preferred p r o p a g a t i o n strategy identified by the screening model included only one. This pattern does n o t hold universally, however. The screening m o d e l identified a strategy with m o r e p r o p a g a t i o n actions in the G r a n d R o n d e sub-basin t h a n did the planners, because the model required an additional action in the G r a n d R o n d e subbasin to meet the planners' stated numerical objectives. A second interesting feature displayed in Table 3 is that six o f the 29 actions s h o w n in the table are included in all four scenarios. T h e six include one action to improve hatchery effectiveness a n d two habitat e n h a n c e m e n t actions in the G r a n d R o n d e subbasin, one supplementation action and one habitat e n h a n c e m e n t action in the Walla

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Walla sub-basin, and a habitat enhancement action in the Umatilla sub-basin. The robustness of these actions over the four scenarios argues that the region should seriously consider these actions, since both the planners and the screening model selected the actions, despite disparate objectives and assumptions among the four scenarios. A final point raised by Table 3 is that the results never indicate a preference for three of the options (Walla Walla headwater storage, Umatilla headwater storage and Umatilla passage improvements). These actions are expensive and seemingly can boast only limited biological effectiveness. While this does not mean that the region should abort all consideration of these projects, their apparent limited efficacy and high costs suggests that these actions require more extensive study or justification along different lines than effectiveness and cost. 5.3.

COST-EFFECTIVENESS FRONTIERS

Figure 3 and Figure 4 display the cost-effectiveness frontiers composed of the leastcost strategies for varying percentages of the terminal harvest/spawning escapement numerical objectives (scenario 3) and the runsize doubling goals (scenario 6), respectively. Because of the way we defined the objectives, the percentage figures have different meanings for terminal harvest/spawning escapement and runsize doubling. For example, the 50% level for terminal harvest/spawning escapement indicates a reduction in the numerical objectives for each stock of 50%. For the runsize doubling goal, however, the 50% level indicates a numerical objective that equals the base-case runsize for each stock. Similarly, a 75% level for the runsize doubling goal indicates an objective that represents a 50% increase in runsize from the base-case [(0-75-0.50)/0.50], and the 100% level an objective that represents a 100% increase [i.e. doubling] in runsize from the base-case [(1-00-0-50)/0.50]. In Figure 3, the costs of attaining the terminal harvest/spawning escapement objectives rise sharply at two points. The sharpest increase--S8 million per year---occurs when the number of fish for terminal harvest and spawning escapement for each stock increases from 60% to 65% of the number originally specified in the sub-basin plans. This increase results from the introduction of an expensive predator control action. The other sharp increase--S3 million per year---occurs when the number of fish for terminal harvest and spawning escapement for each stock increases from 85% to 90% of the number originally specified. This increase results from a large increment in propagation costs.

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Figure 4 shows that the costs of attaining runsize increases above the base-case also rise most sharply at two points. Again, the sharpest increase--S5 million per year--occurs with the introduction of predator control, although this takes place when the number of fish increases from the 70% level to the 75% level. As indicated above, because of the way we defined the objectives this represents a change from a 40% increase from the base-case runsize to a 50% increase from the base-case runsize. The next sharpest increase--S3 million per year---occurs from the 95% level to the 100% level. This represents a change from a 90% increase from the base-case runsize to a 100% increase (doubling) from the base-case runsize. Figure 5 provides an overlay of the cost-effectiveness frontiers for terminal harvest/ spawning escapement and runsize increases. Note that the frontiers cross each other three times---once between 55% and 60%, immediately again between 60% and 65%, and finally between 70% and 75%. Furthermore, the frontier depicting runsize increases above base-case runsizes consistently lies above the harvest/escapement frontier from the 75% level to the 100% level. Taken together, this suggests that while increasing the size of the runs likely will cost more than increasing terminal harvest and spawning escapement as one approaches likely ranges for the two kinds of goals, the attainment of the proportional runsize increases sometimes may cost less than attainment of the stock-specific numerical objectives for terminal harvest and spawning escapement. An approach for setting objectives that is based on equal proportional increases above one reference case (i.e. historical run sizes) thus may not be entirely consistent with an approach that is based on equal proportional increases above another reference case (i.e. terminal harvest and spawning escapement objectives set by sub-basin planners). In other words, not only can the composition and cost of least-cost recovery alternatives depend very much on what reference case is chosen for setting objectives, but objectives defined on an apparently less-ambitious reference case may not always yield a recovery alternative that entails fewer recovery actions and lower costs. As a final point, the shape of the cost-effectiveness frontiers differs somewhat from expectations, in that the marginal cost of each 5% increase in the number of fish does not always increase as the number of fish increases. (Each of the three figures that depict cost-effectiveness frontiers display this dearly.) This results from the discrete nature of the actions; that is, one can either implement an action in whole or 'not at all. Given that our objective is to minimize total costs at different levels of terminal

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harvest, spawning escapement and runsize, the intuitive approach of choosing the actions based on lowest marginal cost generally will not yield a least-cost frontier unless the rankings of the actions based on marginal costs and on total costs are identical.

6. Policy implications for the Pacific Northwest The system-wide cost-effectiveness analysis does not definitively answer the question of what enhancement actions to implement in the Pacific Northwest, nor was it designed to. Rather, as stated earlier, we undertook the analysis in order to contribute useful information to decision makers who are interested in least-cost system-wide planning for mitigation or in exploring trade-offs among passage and propagation costs, fish production measures and attributes of fish stocks, including genetic risk. Beyond this immediate usefulness, the application and results of the system-wide analysis suggest several other policy implications for Northwest policy makers. First, the downstream passage component of the cost-effectiveness analysis clearly points out the pressing need for more information. The modeling exercise highlights the obvious problem of a lack of data to support proposals directed at improving downstream survivals. Given the high costs and apparently limited effectiveness of the flow levels advocated in the Council's flow amendment, it seems imperative that the region continue to push forward with empirical research on downstream passage. More generally, the results suggest that cost-effectiveness modeling can be a useful tool for prioritizing information needs. Management strategies that consistently appear on the cost-effectiveness frontier seem particularly ripe for further investigation, as do strategies currently in place or under serious consideration that consistently appear far off the frontier. Second, the analysis highlights the need for a system-wide focus. A significant amount of effort to date in the Pacific Northwest has concentrated on sub-basins within the Columbia Basin, yet the aggregation of cost-effective results from sub-basin analyses does not necessarily lead to system-wide least-cost planning. Furthermore, a focus on sub-basin actions in isolation from passage actions is unlikely to produce a systemwide, least-cost set of management actions. Obviously, all problems of environmental management do not require a systems approach. However, the analysis does suggest that such an approach may be useful to minimize costs when a large inter-connected set of subsystems is present.

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Finally, the modeling work suggests that the region should articulate a wider range of possible objectives related to fish populations, because the desirability of passage and sub-basin strategies can change as objectives change. The objectives modeled in the analysis represent our perception of the objectives and constraints of the region's fish and wildlife program, as expressed by the sub-basin planners. Clearly, a number of other objectives or constraints exist (e.g. increasing passage survival through natural means such as flows, spreading the costs of mitigation around the region, keeping commercial harvest stocks viable, etc.). These other objectives and contraints are important considerations that we hope to capture in future work.

7. Broader implications of analysis Although the cost-effectiveness analysis described in this paper was designed to provide information to decision makers interested in evaluating actions to rebuild the Columbia Basin salmon populations, it has been our experience that the approach's practical contribution to decision making has been limited. We conclude with several observations on some of the limitations of the approach and some of the characteristics of the decision making environment that have limited the use of the analysis. We believe that these observations may have broader relevance for other regional-scale problems of environmental management. First, the deterministic framework of the analysis clearly constrains the relevance of the approach. Processes and the behavior of individuals in the biological world are highly uncertain and variable, yet the cost-effectiveness analysis generally relies on point estimates of biological parameters and the effectiveness of each action. This limits the utility of the assessments, particularly for low-abundance stocks. By ignoring uncertainty, the essentially deterministic analysis may promote inferior recovery or mitigation alternatives and be of limited help in designing necessary monitoring programs. Most other environmental management problems would likewise benefit from approaches which address stochasticity more fully and directly. We have used a stochastic life-cycle model for other analyses of Columbia Basin salmon stocks, but as stated earlier the basin-wide scope of this analysis prevented its use here. Second, the accuracy, completeness and timeliness of the data necessary for the analysis pose problems. For example, the region suffers from incomplete information on the relationships between mainstem flow and smolt survival, the importance of water temperature, carrying capacity of sub-basins, ocean survival and the effectiveness of recovery or mitigation actions. Any environmental management problem which adopts a systems framework is likely to share this problem of data availability and accuracy, since the all-inclusive framework generally requires extensive data and, at the same time, somewhat coarse resolution in order to maintain tractability. Third, the cost-effectiveness analysis did not stress dynamic elements of the fish populations. The assessment generally ignored the sequence and timing of actions required to arrive at a targeted population size, which assumes away real-world problems of budget and personnel constraints, design and construction lead times, possibilities for adaptive management and trends in the effectiveness of actions over time. Again, given data constraints and the necessarily coarse resolution of many studies, the importance of dynamic elements in shaping environmental management efforts may be under-appreciated in a large number of regional-scale studies. Fourth, and with respect to the decision making environment, many policy makers

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have perceptions of the utility of models that differ from those held by modelers. A modeler may subscribe to the belief that at relatively low cost and with no direct danger to fish populations, models can serve well to explore alternative hypotheses about biological processes, how different assumptions about the effectiveness and costs of proposed actions influence the desirability of the actions, and how to achieve different objectives. These explorations often require a range of model frameworks. Decision makers often understandably argue for a single best model to present useful, noncontradictory information, however. This can lead to modeling wars among analysts from different camps, which can obscure the information-providing, debate-generating function of models. Fifth, many environmental management analyses, including this one, are conducted in the shadow of potential litigation. If decision makers look to the long term and believe that a thorough, defensible argument will carry more weight in a litigious setting, they may favor a systematic approach that provides such arguments. On the other hand, if they want to avoid litigation at all costs, they may want to de-emphasize the science in order to maximize consensus and agreement on the best way to proceed. Often, the fear of protracted court battles wins out, which may make approaches such as cost-effectiveness analysis less appealing to the policy-making community. Sixth, the analysis deliberately ignores the fragmentation of responsibility for implementing decisions. Realistically, however, recovery and mitigation planning and implementation require participation by different executive agencies, legislative representatives, private industry, non-profit groups, citizens and multiple political jurisdictions. More generally, systematic assessments often focus on overall system performance, and neglect the real-world constraint of fragmented responsibility for implementation of actions. Additionally, they also often unjustifiably posit the presence of a suitable legal environment or discount the legal obstacles to implementations of actions. Finally, the objectives of policy-makers in the Pacific Northwest are like most realworld objective sets, in that they are multi-dimensional and often ill-defined. Recovery and mitigation planning entail multiple biological and social objectives which often lack clear definition and pose difficult trade-offs. Analysts typically do not fully comprehend the entire range of objectives in regional environmental management, and decision-makers be unwilling or unable to reveal their objectives to the analytical community. Modelers often articulate the objectives based on their notions of rationality, without realizing that their definition of rational objectives may reflect their biases and not a wider cross-section of societal values and goals. As a result, systematic assessments of environmental management thus often provide information relevant only to a small subset of the objectives. Analyses such as the one presented here are perhaps most useful in an atmosphere of exploration, where the public and policy-making community articulate possible objectives, investigate the trade-offs that the analysis uncovers among different objectives, form new objectives based on this information, investigate trade-offs among the new set of objectives, debate new objectives, compromise and so on. This atmosphere requires, of course, that objectives be explicitly stated, rather than just implicitly incorporated (and perhaps hidden) in proposed courses of action. At the risk of stating the obvious, without clear articulation of the range of possible objectives by the public and the policy-making community, analysts are often hard-pressed to provide relevant information.

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References Bonneville Power Administration. (1991). Issue Alert: What is BPA Doing About the Salmon? DOE/BP-1730. Portland, Oregon: Bonneville Power Administration. Bonneville Power Administration. (1993). Journal. DOE/BP-2027. Portland, Oregon: Bonneville Power Administration. Bonneville Power Administration. (1995). State of the Agency. DOE/BP-2529. Portland, Oregon: Bonneville Power Administration. Columbia Basin Fish and Wildlife Authority. (1990). Columbia Basin System Planning Salmon and Steelhead Production Plans. Portland, Oregon: Columbia Basin Fish and Wildlife Authority and Northwest Power Planning Council. Dennis, B., Munholland, P. and Scott, J. (1991). Estimation of growth and extinction parameters for endangered species. Ecological Monographs 61, 115-143. Gass, S. I. (1985). Linear Programming, 5th edn. New York: McGraw Hill. Hinrichsen, R. et al. (1991). Columbia River Salmon Passage (CRISP) Model." Documentation for CRiSP.O. Seattle: Center for Quantitative Science, University of Washington. Lee, D. C. and Hyman, J. B. (1992). The Stochastic Life-Cycle Model (SLCM): Simulating the Population Dynamics of Anadromous Salmonids. Research Paper INT-459. Ogden, Utah: Intermountain Research Station, Forest Service, U.S. Department of Agriculture. Montgomery, C. and Brown, G. M. (1992). Economics of species preservation: The spotted owl case. Contemporary Policy Issues 10(2), 1-12. Nehlsen, W., Williams, J. E. and Lichatowich, J. A. (1991). Pacific salmon at the crossroads. Fisheries 16(2), 4-21. Northwest Power Planning Council. (1987). 1987 Columbia River Basin Fish and Wildlife Program. Portland, Oregon: Northwest Power Planning Council. Northwest Power Planning Council. (1991). Proposed Amendments with Technical Appendices. Document 91-25. Portland, Oregon: Northwest Power Planning Council. Northwest Power Planning Council. (1992). System Planning Model Documentation Update, Version 5.10. Portland, Oregon: Northwest Power Planning Council. Northwest Power Planning Council. (1993). Strategy for Salmon Volume 11. Portland, Oregon: Northwest Power Planning Council. PNUCC. (1983). The System Analysis Model." Methods and Theory Manual. Portland, Oregon: Pacific Northwest Utilities Conference Committee. Paulsen, C. M., Hyman, J. B. and Wernstedt, K. (1993a). Above-Bonneville Passage and Propagation Cost-Effectiveness Analysis. Technical Report DOE/BP-98852-1. Portland, Oregon: Bonneville Power Administration. Paulsen, C. M., Wernstedt, K. and Hyman, J. B. (1993b). Recovery Planning for Endangered Salmon: A Multiple Attribute Analysis. Washington, D.C.: Resources for the Future. Paulsen, C. M. and Wernstedt, K. (In press). Cost-effectiveness analysis for complex managed hydrosystems: An application to the Columbia River basin. Journal of Environmental Economics and Management. U.S. Army Corps of Engineers. (1992). Salmon Passage Notes. Portland, Oregon: North Pacific Division, U.S. Army Corps of Engineers.