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    ADAPTIVE MANAGEMENT AND THE REGULATION OF 
            WATERFOWL                HARVESTS*
            
            Byron K. Williams, U.S. Geological Survey, Division of 
                               Biological Resources, 12201 Sunrise Valley Drive, 
              Reston, VA 20192
            Fred A. Johnson, Office of Migratory Bird Management, 
              U.S. Fish                  and Wildlife Service, 11500 American 
              Holly Drive, Laurel, MD 20708-4016
            (* originally published in 1995 in The Wildlife 
              Society                  Bulletin, Vol. 23(3):430-436)
            
            Migratory bird hunting is an important form of outdoor recreation 
            in the                  United States. Each year, approximately 3 
            million people engage in 22                  million days of 
            migratory bird hunting, with an expenditure of $700                  
            million (U.S. Deps. Inter. and Commer. 1993). Although the number of 
                             waterfowl hunters has declined somewhat in recent 
            years (Trost et al.                  1987), duck and goose hunting 
            still constitutes about one-third of all                  migratory 
            bird hunting activity (Martin, E. M. and P. J. Padding, 1994,        
                      Preliminary estimates of waterfowl harvest and hunter 
            activity in the                  United States during the 1993 
            hunting season, U.S. Fish and Wildl. Serv.,                  Off. 
            Migratory Bird Manage. Adm. Rep., Laurel, MD, 1994).
            In response to demands for increased hunting opportunities, 
            waterfowl                  harvest regulations have grown to include 
            features such as special seasons                  on more abundant 
            species, geographic zoning, and species-specific bag                 
             limits (U.S. Dep. Inter. 1988). These regulations, along with basic 
            season                  lengths and bag limits, constitute a 
            sometimes bewildering network of                  regulatory 
            options. The impacts of these regulations on harvest and             
                 population status is highly uncertain, even though North 
            American                  waterfowl are among the world's most 
            thoroughly investigated biota                  (Nichols and Johnson 
            1989).
            Several factors have contributed to uncertainty about the effects 
            of                  waterfowl harvest regulations. One factor is the 
            sheer number and                  complexity of regulatory options 
            offered in recent years. The introduction                  of so 
            many options has complicated the regulations process greatly and has 
                             made it effectively impossible to assess either 
            their marginal or                  cumulative effects. A second 
            factor is the large-scale confounding of                  harvest 
            and environmental effects that occurs when regulations "chase"       
                       population and habitat conditions (i.e., liberal 
            regulations are set                  whenever populations appear to 
            be abundant, and restrictive regulations                  are used 
            whenever populations are low). Such a strategy may be appropriate    
                          under conditions in which population dynamics and the 
            effects of hunting                  are well understood. However, in 
            this case the knowledge required is                  unavailable to 
            waterfowl managers, and "chasing" populations                  makes 
            acquiring the information needed to reduce key uncertainties         
                     virtually impossible. A third factor concerns limitations 
            of "reductionist                  science" in which the behavior of 
            a managed system is understood by                  dividing it into 
            subsystems more amenable to investigation (e.g., studying            
                  the effect of harvest on annual survival rate). A reductionist 
            approach is                  likely to be most useful if one is 
            dealing with processes that are                  additive in their 
            effects on population dynamics (i.e., survival,                  
            recruitment, immigration, emigration), a situation seldom 
            encountered in                  ecological systems.
            These and other factors have resulted in an inability to 
            recognize                  effects of regulations on waterfowl 
            population dynamics. Because this                  uncertainty 
            limits our ability to make regulatory decisions consistent           
                   with long-term harvest and conservation goals, there are 
            material benefits                  in its reduction. We advocate an 
            approach known as "adaptive resource                  management" 
            (Holling 1978, Walters 1986) that explicitly recognizes              
                uncertainty about management impacts and seeks to provide useful 
                             information about system dynamics. Incorporation of 
            uncertainty in the                  formulation of management 
            strategies sets adaptive resource management                  apart 
            from other, more traditional applications of strategic decision      
                        making.
            We describe an adaptive approach to regulating waterfowl 
            harvests. Our                  objectives are to: (1) propose 
            adaptive harvest management as an extension                  of the 
            current regulatory process, focusing on active pursuit of knowledge  
                            for informed decision-making; and (2) discuss key 
            issues and challenges                  associated with adaptive 
            harvest management.
            
            MANAGING ADAPTIVELY
            Managing adaptively requires feedback between management and 
            assessment,                  when each activity influences the 
            other. Thus, managers must assess a                  managed system 
            periodically and somehow adapt decisions to the system               
               state while accounting for uncertainty about the effects of those 
                             decisions. Adaptive management is sometimes 
            described as "embracing"                  uncertainty (Walters 
            1986), in that it recognizes uncertainty as an                  
            attribute of management, and uses management itself as a tool to     
                         accelerate the reduction in uncertainty. A definition 
            we find useful is:
            
            "Adaptive harvest management describes the ability to 
              make                  a sequence of decisions, in the face of 
              uncertainty, that is optimal with                  respect to a 
              stated objective, recognizing some constraints"
            
            (D. R. Anderson, Natl. Biol. Serv., Ft. Collins, Colo., pers. 
            commun.                  1995). Less formally, adaptive harvest 
            management might be described as                  managing in the 
            face of uncertainty, with a focus on its reduction. An               
               adaptive approach emphasizes uncertainty about regulatory effects 
            and                  incorporates uncertainty as a factor guiding 
            management actions (Johnson                  et al. 1993). It also 
            implies that the performance of management can be                  
            improved if uncertainties are reduced.
            
            Operational Components
            For management to account for resource status as well as 
            uncertainty                  about harvest effects, 3 critical 
            components linking management,                  assessment, and 
            population dynamics are required: (1) a process of                  
            decision making with clear, focused management objectives; (2) a     
                         monitoring program that periodically determines the 
            status of the                  resource; (3) a process by which the 
            effects of management decisions on                  the resource can 
            be assessed.
            Decision making process.--The process of regulating 
            waterfowl                  harvests is well known, and involves a 
            rather lengthy sequence of public                  announcements, 
            deliberations, and decision making (Blohm 1989).                  
            Participation by the U.S. Fish and Wildlife Service (USFWS), state   
                           wildlife agencies, the Canadian and Mexican 
            governments, and the public                  occurs at numerous 
            times during the regulatory cycle. The process involves              
                assessment of waterfowl populations, publication of 
            Federal Register notices, and numerous meetings by the 
            Waterfowl Flyway Councils and USFWS                  Regulations 
            Committee. It culminates in selection of regulations at the          
                    flyway level (season lengths, daily bag limits, and outside 
            dates for the                  earliest opening and latest closing 
            dates for a hunting season) and                  special regulations 
            at the state level (e.g., split seasons, harvest                  
            zones, special seasons, area closures). A major challenge for 
            waterfowl                  biologists is to identify the effects of 
            such a profusion of harvest                  regulations.
            A critical component of this process should be the unambiguous    
                          specification of objectives for harvest management. 
            Sound harvest                  management requires clear objectives, 
            if only to measure how well the                  decision-making 
            process has worked over time. This apparently simple                 
             requirement has been difficult to fulfill. Indeed, many of the 
            conflicts                  arising in waterfowl harvest regulation 
            can be traced back to disagreement                  about goals and 
            objectives for harvest management. At various times the              
                Flyway Councils and the USFWS Regulations Committee have 
            promulgated                  regulations to maximize average 
            harvest, minimize harvest variability,                  stabilize 
            population size, and other variations. A predictable consequence     
                         of this conflicting process is that regulations have 
            failed to meet any of                  the proposed objectives and 
            thus have been unsatisfactory to many                  participants 
            and stakeholders. A rational regulatory process that                 
             encourages regulations pursuant to recognized, agreed upon goals 
            and                  objectives is not possible in the face of such 
            confusion and controversy.                  Clarification of goals 
            and objectives is an ongoing need, and must be seen                  
            as a key responsibility of management.
            Monitoring programs.--Informed decision making consists of 
                             large-scale monitoring programs that deliver 
            information about population                  status and trends, 
            harvest levels, and other important biological                  
            attributes. This information is crucial to ascertain the impacts of  
                            harvest regulation, and thereby to establish a 
            coherent framework for                  setting harvest regulations.
            Key sources of information in the regulatory process are the 
            long-term                  cooperative monitoring programs of the 
            USFWS, state wildlife agencies, and                  federal and 
            provincial governments in Canada. These programs yield               
               information about breeding-population status, harvest levels, 
            production,                  migration, and other population 
            characteristics of value in regulating                  harvests. 
            Data collected each year and added to long-term databases            
                  represent a foundation for harvest management of waterfowl. 
            They are the                  baseline on which much waterfowl 
            research is conducted and are necessary                  for 
            modeling waterfowl populations.
            Analysis and assessment.--Many organizations have played 
            key                  roles in adding to knowledge about waterfowl, 
            including the Flyway Council                  Technical Committees, 
            the USFWS Office Migratory Bird Management, and                  
            wildlife research programs at Patuxent Environmental Science Center, 
                             Northern Prairie Science Center, the Cooperative 
            Fish and Wildlife                  Research Units, and other 
            research institutions. These groups have made                  
            important advances toward a sound understanding of waterfowl 
            populations                  and the impacts of harvest, including 
            investigating patterns in monitoring                  data, 
            estimating key population parameters such as survivorship and        
                      reproduction, and predicting harvest impacts on population 
            dynamics.                  Information accumulated through 
            monitoring and assessment is folded into                  models of 
            population size and distribution as influenced by harvest            
                  regulations. The goal of these efforts is to model the 
            responses of a                  population to harvest regulation, 
            based on long-term monitoring and                  research 
            programs. By building on the databases they are designed to          
                    represent, these models provide valuable information to 
            management, and                  thus represent a crucial link in 
            the regulations process.
            
            Regulating Waterfowl Harvests
            The current regulatory process links decision making, modeling 
            and                  assessment, and population monitoring in an 
            iterative cycle. Regulations                  in 1 year influence 
            harvest, which in turn influences population status in               
               the next year. Effects of harvest regulations on a waterfowl 
            population                  are reflected in monitoring data, which 
            add to the cumulative body of                  information that is 
            used to update population models. These models in turn               
               guide the regulatory process in the next cycle. Model updating 
            occurs each                  year with new monitoring data, so that 
            both the models and the information                  base they 
            represent constantly evolve.
            In this scenario regulations have both direct as well as indirect 
                             effects, and both are key to effective regulation 
            of waterfowl harvests.                  First, regulations directly 
            affect a population by influencing the amount                  of 
            harvest, and through harvest, the subsequent population size. 
            Second,                  regulations have indirect effects by 
            influencing the information available                  for the 
            subsequent regulatory cycle. For example, following on a period in   
                           which regulations have been relatively constant for a 
            number of years, new                  insights often can be gained 
            by deliberating changing regulations and                  observing 
            the response in harvest and population size. It seems intuitive      
                        that "informative" regulations are in some sense better 
            than                  regulations that are not informative.
            The current regulatory scenario is itself adaptive, in that it 
            describes                  a procedure whereby regulations are 
            adapted to the available monitoring                  data. For the 
            management of waterfowl harvests, this means periodic                
              updating of databases, incorporating these data into improved 
            population                  models, and using this information for 
            setting annual harvest regulations.                  A typical 
            application would involve using population models to explore the     
                         impacts of a number of different regulations to 
            identify regulations that                  maximize harvest (or 
            harvest opportunity) and limit the negative effects                  
            on populations. Regulations thus identified should guide the         
                     decision-making process.
            
            The Pursuit of Information With Regulations
            Although the regulatory procedure described above is in some 
            sense                  adaptive, the strategy is far from optimal 
            for attaining management                  objectives. Its key 
            limitations are a failure to account for uncertainty                 
             about population responses to regulations, and a failure to 
            recognize                  value in attaining useful information to 
            reduce that uncertainty. Thus,                  information is 
            simply an unplanned by-product of harvest regulations, and           
                   the process is an example of passive adaptive management 
            (Walters and                  Holling 1990). Although a passive 
            adaptive approach can lead to improved                  management 
            over time, improvements typically accrue very gradually. With        
                      the single exception of the period from 1980-84 when 
            waterfowl harvest                  regulations were stabilized 
            (Patterson and Sparrowe 1987), waterfowl                  harvest 
            management has been (and continues to be) passively adaptive.
            The use of regulations to actively pursue understanding of 
            regulatory                  effects is an example of active adaptive 
            management (Walters and Holling                  1990). In this case 
            the accretion of information and reduction of                  
            uncertainty about population responses are incorporated explicitly 
            as an                  objective in the decision-making process. 
            Some regulatory strategies are                  likely to be more 
            informative than others, because they lead to more                  
            informative databases and improved models for describing the 
            consequences                  of regulations. Active adaptive 
            management entails the use of such                  strategies while 
            pursuing more traditional harvest management objectives.
            Hereafter, we use the phase adaptive harvest management to mean 
            the                  active pursuit of information through 
            regulations. To avoid any confusion                  about the role 
            of information in adaptive harvest management, it is useful          
                    to identify its role explicitly. An adaptive approach 
            emphasizes resource                  management per se, with value 
            ascribed to information and understanding                  only to 
            the extent that they contribute to the objectives of resource        
                      management. Thus, adaptive management does not recognize 
            intrinsic value                  in biological monitoring, research, 
            or scientific assessment. From a                  management 
            viewpoint these activities, and the knowledge they produce, are      
                        justified only to the extent that they serve management 
            purposes. It may                  be reassuring that adaptive 
            management, by recognizing the importance of                  
            reliable information on which to base management decisions, 
            reinforces                  strong cooperation between researchers 
            and managers.
            
            Adaptive Harvest Management
            Adaptive harvest management can be described in terms of 4 
            components:                  (1) an array of potential hunting 
            regulations that are available to                  decision makers 
            for the control of waterfowl harvests; (2) a set of models           
                   representing meaningful hypotheses about population dynamics 
            and the                  effects of harvest; (3) a measure of 
            "uncertainty" for each                  model, expressing the 
            relative likelihood that it appropriately describes                  
            population responses to regulations; and (4) an objective function 
            (i.e.,                  a mathematical expression of harvest 
            management objectives) by which to                  evaluate and 
            compare regulatory options. These components are used to             
                 identify the actively adaptive harvest strategy that is optimal 
            with                  respect to management objectives.
            The actual mechanics of determining optimal regulatory strategies 
            is                  quite complicated and beyond the scope here (see 
            Williams 1988, 1989;                  Lubow 1993, 1995). In essence, 
            the problem is cast in the framework of                  constrained 
            optimization of stochastic dynamic systems, with an objective        
                      function based on expected long-term harvests weighted by 
            the model                  likelihoods. The system in this case 
            consists of the set of population                  models, each 
            describing population dynamics in terms of population size,          
                    environmental conditions, and regulations. The models 
            represent different                  hypotheses about the impacts of 
            regulations, and the likelihood weights                  represent 
            uncertainty as to which hypothesis is most appropriate.
            The optimization procedure accounts for both the current 
            population                  status and the degree of uncertainty 
            about system dynamics in assessing                  the influence of 
            regulatory decisions on future population status                  
            (Williams 1996a,b). It chooses regulations at each point in time 
            based on                  the expected sum of present and future 
            harvests, recognizing that future                  yields are 
            influenced by regulatory decisions in the present. The goal, of      
                        course, is to choose regulations at each point in time 
            that are optimal,                  in that they produce a maximum 
            expected value of present and future                  harvests. The 
            process recognizes that optimal management can be realized           
                   only by eventually identifying the most appropriate model of 
            population                  dynamics.
            The key to an actively adaptive regulations process involves the 
            active                  pursuit of information. Regulations 
            influence the removal of individuals                  from the 
            population through harvest and hence affect the size of the          
                    population the next year. Monitoring programs record data on 
            harvest and                  population status from year to year, 
            which then are used to improve the                  models under 
            consideration and update the likelihoods associated with each        
                      model. This information is incorporated in an objective 
            function                  consisting of predicted long term harvests 
            for each model, with                  model-specific harvests 
            weighted by the updated likelihoods. The                  
            optimization procedure identifies harvest strategies that maximize 
            the                  weighted average of harvests, and these 
            strategies subsequently are used                  to set 
            regulations. This sequence is repeated each year in an ongoing       
                       cycle of monitoring, model updating, analysis and 
            optimization, and                  regulations setting. Information 
            that discriminates among models accrues                  with each 
            cycle so that the most appropriate model for describing              
                population dynamics is identified over time.
            
            IMPLEMENTATION ISSUES
            
            Management Objectives
            International treaties relating to the conservation of migratory 
            birds                  clearly mandate that the opportunity to 
            harvest waterfowl is of lesser                  importance than the 
            protection and maintenance of populations. Although                  
            these priorities are useful to managers, the potentially competing   
                           objectives (i.e., size of the harvest vs. size of the 
            population) leave                  room for debate about appropriate 
            harvest strategies. Even if all                  management 
            strategies under consideration provide sustainable harvests,         
                     average population size still can vary under the 
            alternative strategies.
            Waterfowl population goals have been identified in the North 
            American                  Waterfowl Management Plan (U.S. Dep. 
            Inter. and Environ. Can. 1986). These                  goals were 
            established to ensure satisfactory levels of hunting                 
             opportunity, but also for ecological and aesthetic purposes. Though 
            the                  Plan has a strong focus on waterfowl habitats, 
            its population goals have                  been formally endorsed by 
            the federal governments of Canada, Mexico, and                  the 
            U.S. Therefore, waterfowl managers are obligated to consider these   
                           goals in the development of harvest strategies. 
            However, we believe that                  the Plan goals are 
            insufficient by themselves to identify unambiguous                  
            harvest objectives and optimal harvest strategies, particularly 
            under                  conditions in which habitat cannot adequately 
            support such population                  levels.
            We suggest an objective that attributes relatively high value to 
            hunting                  opportunity when Plan goals are met, and 
            lower value to hunting                  opportunity as populations 
            fall short of Plan goals. Decline in the value                  of 
            hunting opportunity may be linear or non-linear, with the rate of    
                          decline dependent on the relative importance of 
            providing hunting                  opportunity and achieving the 
            Plan’s goals. In developing such an                  objective, 
            managers must specify the minimum population level at which          
                    hunting opportunity can be allowed.
            Managers also may wish minimize the temporal variability in 
            hunting                  regulations for sociological and 
            administrative reasons (U.S. Dep. Inter.                  1988). 
            This can be accomplished most easily by either: (1) altering the     
                         frequency of regulatory decisions from 1 to multiple 
            years; or (2)                  constructing a set of regulatory 
            options with large differences in                  predicted harvest 
            rates. It is likely that either of these options would               
               lead to smaller amounts of hunting opportunity over the long-term 
            and more                  variability in population size than if a 
            temporal constraint on                  regulations were not imposed 
            (Hilborn and Walters 1992).
            
            The Array of Regulatory Options
            A array of regulatory options representing, for example, 
            restrictive,                  moderate, and liberal seasons, must be 
            developed and agreed upon. The                  number of options 
            must be limited to facilitate their assessment. In                  
            addition, regulatory options should: (1) elicit different harvest 
            and                  population responses; (2) produce predictable 
            harvest rates; (3) be                  consistent with hunter 
            preferences to the extent possible; and (4)                  
            facilitate law enforcement.
            The development of limited regulatory options provides an 
            opportunity to                  address the problems associated with 
            the current regulatory complexity,                  which is 
            criticized by managers and hunters alike (Babcock and Sparrowe       
                       1989). The complexity of migratory bird hunting 
            regulations, particularly                  those designed to 
            increase hunting opportunities for lightly-harvested                 
             species, was probably an inevitable by-product of the increasing    
                          information available about waterfowl populations and 
            demands for higher                  levels of consumptive use. Goals 
            to simplify regulations and to increase                  harvest 
            opportunities on lightly-harvested species conflict. Another         
                     consideration is whether species-specific regulations have 
            distributed                  harvest pressure in the desired manner. 
            Recent analyses (e.g., Rexstad et                  al. 1991) suggest 
            that the capability to shift harvest pressure among                  
            various stocks of migratory birds may be limited. Finally, the 
            ability to                  provide expanded harvest opportunity for 
            any species is dependent on the                  quality of resource 
            monitoring programs and on the ability to target the                 
             species of interest with management actions. Thus, it is 
            unrealistic to                  expect to maximize harvest 
            opportunities for every species.
            
            Alternative Models of Population Dynamics
            Many waterfowl models have been developed for purposes other than 
                             harvest management (Williams and Nichols 1990), but 
            there is a dearth of                  models that describe mortality 
            and reproductive processes over the annual                  cycle. 
            In adaptive harvest management, models must not only describe the    
                          effect of hunting (e.g., additive vs. compensatory 
            hunting mortality), but                  also the effect of the 
            environment (which may include population                  
            abundance) on changes in population size. In addition, candidate 
            models                  should meet 3 other criteria: (1) models 
            must describe different harvest                  strategies (or 
            there is no value in learning which model is best); (2)              
                models must describe different responses to harvest that are 
            detectable by                  the monitoring program (or the 
            process will fail to identify the most                  appropriate 
            model); and (3) models should be consistent with historical          
                    experience (i.e., empirical).
            
            Other Considerations
            It is important to recognize uncertainties, other than those 
            associated                  with biological mechanisms, that further 
            complicate the regulation of                  harvest. A lack of 
            knowledge about underlying biological mechanisms (often              
                called structural uncertainty) is exacerbated by our inability 
            to                  precisely observe population status and trends, 
            and our inability to                  completely control harvest 
            with regulations. A limited ability to                  recognize 
            status and trends is described generically by the term partial       
                       observability, to emphasize the fact that (1) 
            observability of a                  population is tied to monitoring 
            precision and (2) population status can                  be measured 
            only within the limits of that precision. Limitations in the         
                     control of harvest are described by the term partial 
            controllability,                  which expresses the fact that 
            regulations can be used to target actual                  harvest 
            rates (and harvest impacts) only as precisely as control limits      
                        allow.
            Partial observability, partial controllability, and a lack of 
            knowledge                  about biological mechanisms all 
            contribute to the uncertainties waterfowl                  managers 
            face in their attempts to regulate harvests. When simultaneously     
                         operative, their joint effects may well be greater than 
            the sum of their                  individual effects. For example, 
            monitoring imprecision diminishes one's                  ability to 
            "see" the system, and thus impedes the rate of                  
            learning about underlying biological structures. Similarly, an 
            inability                  to recognize and control harvest rates in 
            the presence of structural                  uncertainty slows 
            learning rates, essentially because population dynamics              
                can be attributable to: (1) an assumed rate of harvest; (2) an 
            assumed                  relationship between harvest and biological 
            processes; or (3) both                  factors. Finally, monitoring 
            imprecision in the presence of partial                  
            controllability can effectively mask the effect of partial control 
            and                  further confound the recognition of biological 
            structure.
            
            CONCLUSIONS
            
            Implementation of an actively adaptive harvest strategy for 
            waterfowl                  faces formidable obstacles. In addition 
            to the technical difficulties                  discussed above, 
            there are a number of potential institutional                  
            impediments. Adaptive harvest management requires an explicit 
            admission of                  ignorance or disagreement (i.e., 
            uncertainty about biological mechanisms)                  and 
            involves the use of mathematical methods (i.e., stochastic           
                   optimization) not easily explained (Walters 1986). Competing 
            interests                  will make it extremely difficult to reach 
            agreement on explicit objectives                  and constraints. 
            Administrators and politicians often have difficulty                 
             focusing on long-term objectives, and even short-term sacrifices of 
            lost                  hunting opportunity or impacted resources may 
            be unacceptable. Ultimately,                  success in adaptive 
            harvest management will require, more than anything                  
            else, an institutional framework that embraces patience, 
            persistence, and                  commitment.
            Despite potential pitfalls, we believe adaptive harvest 
            management                  offers considerable benefits from both 
            technical and administrative                  perspectives. Some of 
            these advantages are: (1) the opportunity to resolve                 
             long-standing controversies about the effects of hunting 
            regulations,                  while pursuing more traditional 
            management goals; (2) increased                  objectivity and 
            integrity in the decision-making process; (3) a clearer              
                focus on long-term management (i.e., sustainability); (4) a 
            better                  understanding of harvest management 
            objectives through identification of                  difficult 
            trade- offs; (5) a clearly-defined role of data-gathering            
                  programs in the regulations process; (6) a stronger link 
            between migratory                  bird management and research; (7) 
            explicit accounting for all sources of                  uncertainty 
            (environmental, structural, partial management control,              
                partial system observability); and (8) treatment of management 
            as an                  adaptive process, which is more appropriate 
            for dynamic systems than a                  static strategy (i.e., 
            managers make adjustments to hunting regulations                  
            based on changing resource status and their understanding of 
            population                  dynamics).
            
            LITERATURE CITED
            
            BABCOCK, K. M., AND R. D. SPARROWE. 1989. Balancing expectations 
            with                  reality in duck harvest management. Trans. 
            North Am. Wildl. and Nat.                  Resour. Conf. 
            54:594-599.
            BLOHM, R. J. 1989. Introduction to harvest - Understanding 
            surveys and                  season setting. Proc. Inter. Waterfowl 
            Symp. 6:118-133.
            HILBORN, R., AND C. J. WALTERS. 1992. Quantitative fisheries 
            stock                  assessment: choice, dynamics & 
            uncertainty. Routledge, Chapman &                  Hall, Inc., 
            New York, NY. 570pp.
            HOLLING, C.S., EDITOR. 1978. Adaptive Environmental Assessment 
            and                  Management. John Wiley and Sons, London, UK. 
            363pp.
            JOHNSON, F.A., B.K. WILLIAMS, J.D. NICHOLS, J.E. HINES, W.L. 
            KENDALL,                  G.W. SMITH, AND D.F. CAITHAMER. 1993. 
            Developing an adaptive management                  strategy for 
            harvesting waterfowl in North America. Trans. North Am.              
                Wildl. Nat. Resour. Conf. 58:565-583.
            LUBOW, B. 1993. Stochastic Dynamic Programming (SDP): User's 
            Guide.                  Version 1.04. Coop. Fish and Wildl. Research 
            Unit, Colorado State                  University. 119 pp.
            LUBOW, B. 1995. SDP: Generalized software for solving stochastic 
            dynamic                  optimization problems. Wildl. Soc. Bull. 
            23:738-742.
            NICHOLS, J. D., AND F. A. JOHNSON. 1989. Evaluation and 
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