BENEFITS AND RISKS OF INCREASED SPATIAL RESOLUTION IN THE MANAGEMENT OF FISHERY METAPOPULATIONS UNDER UNCERTAINTY

Abstract Stock assessments and harvest guidelines are typically based on the concept of a “fish stock,” which may encompass a very large area. The presence of discrete subpopulations within managed fish stocks presents risks and opportunities for fishery management. Failure to manage catch at the same scale as the true population structure can lead to extirpation of discrete subpopulations and to declines in the productivity of the larger metapopulation. However, it may be difficult and costly to assess and manage stocks at a finer spatial scale, and there is likely greater uncertainty about the size of substocks than about the aggregate stock. We use a two‐area simulation model to compare the performance of fishery management at different spatial resolutions when there is uncertainty about growth, the size of the total population, and the relative size of the subpopulations. We show that relative benefits of finer scale management, in terms of profits and risks of depleting subpopulations, depend on a number of biological, technical, and economic factors. In some cases it may be both less risky and more profitable to manage the fishery with a single total allowable catch, even when there are biologically separate fish populations in the two areas.     

IN-SEASON FISHERY MANAGEMENT: A BAYESIAN MODEL

A Bayesian model is presented for optimizing harvest rates on an uncertain resource stock during the course of a fishing season. Pre-season stock status information, in the form of a “prior” probability distribution, is updated using new data obtained through the operation of the fishery, and harvest rates are chosen to achieve a balance between conservation concerns and fishing interests. A series of fishery scenarios are considered, determined by the stock size distribution and the timing distribution; the uncertainty in the fish stock is seen to have a rather complex influence on optimal harvest rates. The model is applied to a specific example, the Skeena River sockeye salmon fishery.     

EFFECT OF FISH MOVEMENT AND FLEET SPATIAL BEHAVIOR ON MANAGEMENT OF FISH SUBSTOCKS

I investigated the questions (i) how much movement of fish between areas within a stock is required before the areas can be managed jointly instead of separately and (ii) how is the trade-off between separate and joint management affected by the spatial behavior of the fishing fleet? I addressed these questions using a simulation model of a fishery on a stock that is divided into two areas (substocks) between which fish can move. Under joint management, fleet spatial behavior is characterized by its “switching level,” or the biomass level in the currently fished area at or below which the fleet will switch to the other area. Catch levels were calculated under both separate and joint management for a range of movement rates and switching levels. I also studied the effect of differences in natural mortality rates between the two areas. When the natural mortality rates were the same for the two areas, (i) separate management resulted in higher catch than joint management, (ii) joint management only approached the catch of separate management when movement rate of fish between the two areas was very high, (iii) the difference between separate and joint management was greatest when (a) the switching level of the joint fleet was low (i.e., inertia was high) and (b) the joint fleet had a preference for one area. When natural mortality rate was different in the two areas, and (i) the joint fleet did not prefer one area, (a) separate management produced higher catches at low fish movement rates while joint management produced higher catches at high movement rates and (b) switching level had no effect on catch, and (ii) when the fleet had a preference for the area with the higher natural mortality rate, separate management resulted in higher catches than joint management, and the difference increased with increasing fish movement rate. These simulations suggest that the relative merits of separate and joint management of two areas depends on the assumptions one makes about the spatial behavior of the fishing fleet. This behavior is as important as movement of fish between the areas, which is normally assumed to be the overriding determinant of the relative merits of separate and joint management.     

A STOCHASTIC FEEDBACK MODEL FOR OPTIMAL MANAGEMENT OF RENEWABLE RESOURCES

Analytical expressions for optimal harvest of a renewable resource stock which is subject to a stochastic process are found. These expressions give the optimal harvest as an explicit feedback control law. All relations in the model, including the stochastic process, may be arbitrary functions of the state variable (stock). The objective function, however, is at most a quadratic function in the control variable (yield). A quadratic objective function includes the cases of downward sloping demand and increasing marginal costs which are the most common sources for nonlinearities in the economic part of the model. When it is assumed that there is a moratorium on harvest for stock sizes below a certain level (biological barrier), it is shown that the barrier requirements influence the optimal harvest paths throughout.     

OPTIMAL HARVESTING OF FISH POPULATIONS WITH NON-STATIONARY STOCK-RECRUITMENT RELATIONSHIPS

Optimal harvesting policies are commonly derived by assuming a time-invariant relationship between some productivity measure and the resource variable under control. Yet, long-term trends in the environment appear to induce persistent changes in spawning success in several fish stocks. I show that when predictable trends in environmental effects are incorporated into stock-recruitment models, optimal policies respond to changing environmental conditions in a way that depends very much on the management objective. When the goal is to maximize expected discounted yield, resulting risk-neutral policies computed for a model of a cyclic iteroparous population respond by continuously adjusting optimal spawning targets in phase with the environmental cycle: escapements are raised when favorable conditions are anticipated and they are lowered when poor environments are expected. These feedback responses reinforce recruitment fluctuations and lead to a sequence of boom and bust periods in the fishery. Policies shift diametrically when a risk-averse objective is pursued such as maximization of the expected sum of discounted logarithms of catches. Optimal escapements closely parallel fluctuations in population abundance, with harvest rates and catches much less variable than in the risk-neutral policy. Harvest rates respond in a compensatory way to changes in population abundance, anticipated environmental conditions, and expected strength of incoming year-classes. Depending on the specific model used, a constant harvest rate strategy may perform nearly as well as the optimal. Analytical results are provided that characterize risk-neutral optimal policies for stochastic delay-difference population models. Results show that knowledge of current environmental conditions can be used to construct harvest policies which are nearly as good as those “optimal” ones based on long-term environmental forecasts.     

Optimal provisioning strategies for slow moving spare parts with small lead times

When an expensive piece of equipment is bought, spare parts can often be bought at a reduced price. A decision must be made about the initial provisioning of spare parts. Furthermore, if at a certain time the stock drops to zero, because a number of failures have occurred, a decision must be made about the number of parts to be ordered. We focus on one specific expensive slow-moving part that is essential for the functioning of the equipment. The lead time of that part is small compared to its lifetime. We seek an ordering strategy for this part that covers the entire lifetime. Such a strategy should also be applicable to cases where there is uncertainty about the lifetime of the machine, the reliability of the components and the cost of failure. The main result is the development of a simple strategy that performs well in almost all cases. Furthermore, this strategy can easily deal with uncertainty and changes in the parameters.     

INFERRING A BIOPOLITICAL CONSENSUS VIEW OF STOCHASTIC DYNAMICS FOR MANAGEMENT OF A TRANSBOUNDARY FISHERY

ABSTRACT. Management of trans‐boundary fisheries is a complicated problem with biological, legal, economic and political implications. We propose a simple stochastic differential‐equation model to describe a biopolitical consensus view of fish stock dynamics. Estimates of the drift and diffusion terms of three stochastic differential equations are obtained using data from the southern bluefin tuna (SBT) fishery with a method based on the Kolmogorov‐Smirnov statistic. We refer to these estimated equations as alternative biopolitical consensus views of SBT stock dynamics. Each of these is used to generate a time series of optimal harvest that achieves the objective of maximizing the present value of expected fishery returns. These time series of optimal harvests are then compared to actual harvests for the period 1981 1997.     

MODELING DYNAMICS OF FISHERY HARVEST REALLOCATIONS: AN ANALYSIS OF THE NORTH CAROLINA RED DRUM FISHERY

The interactive dynamics of red drum stock growth and two-sector harvest are modeled as a system of differential equations. The dynamic effects of commercial harvest restrictions on stock growth and recreational catch and effort are simulated. The simulation shows that a reallocation of the North Carolina red drum stock from the commercial sector to the recreational sector will not only increase benefits to the recreational sector, but will also be stock enhancing. Stock growth in the years immediately following the reallocation is quite rapid, with complete transition to the final steady-state taking between 23 and 46 years. Parameters important to the behavior of the system are identified through sensitivity analysis, and are used to establish critical areas for further research.     

WHY INCREASED UNCERTAINTY MAY LEAD TO MORE RISKY BEHAVIOR

The purpose of this article is to investigate circumstances under which it may be optimal to deliberately harvest a fish stock to extinction applying a stochastic surplus growth model. It is known from the literature that deliberate extinction may result when there is critical depensation or when the discount rate is high compared to the intrinsic growth rate. Here it is shown that deliberate extinction may also be optimal when the degree of stochasticitry is high even with zero discounting. A high degree of stochasticity may have the same effect as critical depensation even though it is not present in the biological model. In other words, high uncertainty, instead of leading to more conservative harvesting as is usually expected, in this model result in more aggressive harvesting and more risky behavior. The main message is therefore always to try to keep the stock well above any critical limit.     

DO ACCURATE STOCK ESTIMATES INCREASE HARVEST AND REDUCE VARIABILITY IN FISHERIES YIELDS?

Abstract Fisheries managers normally make decisions based on stock abundance estimates subject to process, observation, and model uncertainties. Considerable effort is invested in gathering information about stock size to decrease these uncertainties. However, few studies have evaluated benefits from collecting such information in terms of yield and stability of annual harvest. Here, we develop a strategic age‐structured population model for a long‐lived fish with stochastic recruitment, resembling the Norwegian spring‐spawning herring (NSSH, Clupea harengus L.). We evaluate how uncertainties in population estimates influence annual yield, spawning stock biomass (SSB), and variation in annual harvest, using both the proportional threshold harvesting (PTH) and the current harvest control rule for NSSH as harvest strategies. Results show that the consequences of a biased estimate are sensitive to the harvest strategy employed. If the harvest strategy is suitably chosen, the benefits of accurate information are low, and less information about the stock is necessary to maintain high average yield. Reduced harvest intensity effectively removes the need for accurate stock estimates. PTH (a variant of the constant escapement strategy) with low harvest ratio and the current NSSH harvest control rule both provide remarkable stability in yield and SSB. However, decreased uncertainty will often decrease year‐to‐year variation in harvest and the frequency of fishing moratoria.     

THE EFFECTS OF ITQ IMPLEMENTATION: A DYNAMIC APPROACH

ABSTRACT. This paper investigates the intertemporal effects of introducing Individual Transferable Quota, ITQ, fishery management programs on stock size, fleet size and composition, and returns to quota holders and to vessel operators. Theoretical analysis is conducted using a specific version of a general dynamic model of a regulated fishery. It is demonstrated that the effects will differ depending upon the prevailing regulation program, current stock size, and existing fleet size, composition and mobility and upon how the stock and fleet change over time after the switch to ITQs. The paper expands upon previous works by modeling the dynamics of change in fleet and stock size and by allowing for changes in the TAC as stock size changes, by comparing ITQs to different regulations, and by allowing the status quo before ITQ implementation to be something other than a bioeconomic equilibrium. Specific cases are analyzed using a simulation model. The analysis shows that the annual return per unit harvest to quota owners can increase or decrease over the transition period due to counteracting effects of changes in stock and fleet size. With ITQs denominated as a percentage of the TAC, the current annual value of a quota share depends upon the annual return per unit of harvest and the annual amount of harvest rights. Because the per unit value can increase or decrease over time, it is also possible that the total value can do the same. Distribution effects are also studied and it is shown that while the gains from quota share received are the present value of a potentially infinite stream of returns, potential losses are the present value of a finite stream, the length of which depends upon the remaining life of the vessel and the expected time it will continue to operate.     

MULTISPECIES MODELING FOR ADAPTIVE MANAGEMENT OF HORSESHOE CRABS AND RED KNOTS IN THE DELAWARE BAY

Abstract Adaptive management requires that predictive models be explicit and transparent to improve decisions by comparing management actions, directing further research and monitoring, and facilitating learning. The rufa subspecies of red knots (Calidris canutus rufa), which has recently exhibited steep population declines, relies on horseshoe crab (Limulus polyphemus) eggs as their primary food source during stopover in Delaware Bay during spring migration. We present a model with two different parameterizations for use in the adaptive management of horseshoe crab harvests in the Delaware Bay that links red knot mass gain, annual survival, and fecundity to horseshoe crab dynamics. The models reflect prevailing hypotheses regarding ecological links between these two species. When reported crab harvest from 1998 to 2008 was applied, projections corresponded to the observed red knot population abundances depending on strengths of the demographic relationship between these species. We compared different simulated horseshoe crab harvest strategies to evaluate whether, given this model, horseshoe crab harvest management can affect red knot conservation and found that restricting harvest can benefit red knot populations. Our model is the first to explicitly and quantitatively link these two species and will be used within an adaptive management framework to manage the Delaware Bay system and learn more about the specific nature of the linkage between the two species.     

GROWTH AND MEASUREMENT UNCERTAINTY IN AN UNREGULATED FISHERY

Abstract Complete information is usually assumed in harvesting models of marine and terrestrial resources. In reality, however, complete information never exists. Fish and wildlife populations often fluctuate unpredictably in numbers, and measurement problems are frequent. In this paper, we analyze a time‐discrete fishery model that distinguishes between uncertain natural growth and measurement error and in which exploitation takes place in an unregulated manner. Depending on the parameterization of the model and at which point of time uncertainty is resolved, it is shown that expected harvest under ecological uncertainty may be below or above that of the benchmark model with no uncertainty. On the other hand, when stock measurement is uncertain, expected harvest never exceeds the benchmark level. We also demonstrate that the harvesting profit, or rent, under uncertainty may be above that of the benchmark situation of complete information. In other words, less information may be beneficial for the fishermen.     

ENVIRONMENTAL UNCERTAINTY AND THE TIMING OF ENVIRONMENTAL POLICY

ABSTRACT. This paper shows that the timing of an investment to reduce the emissions of a stock pollutant under environmental uncertainty depends on the specification of uncertainty, on its level, and on the presence of a lower reflecting barrier for the stock pollutant. With quadratic damages, when variability increases with the level of pollution, emissions should be curbed immediately when uncertainty is large enough; when uncertainty is small, however, its impact is ambiguous. A lower reflecting barrier may also significantly influence the investment threshold. These results highlight the importance of better understanding the links between greenhouse gas concentration and weather variability.     

BIOECONOMIC MODEL OF EASTERN BALTIC COD UNDER THE INFLUENCE OF NUTRIENT ENRICHMENT

Abstract The objective of this paper is to study the economic management of Eastern Baltic cod (Gadus morhua) under the influence of nutrient enrichment. Average nitrogen concentration in the spawning areas during the spawning season of cod stock is chosen to be an indicator of nutrient enrichment. The optimal cod stock is defined using a dynamic bioeconomic model for the cod fisheries. The results show that the current stock level is about half of the estimated optimal stock level and that the current total allowable catch (TAC) is about one‐fourth of the optimal equilibrium yield. The results also indicate that the benefit from a reduction in nitrogen very much depends on the harvest policies. If the TAC is set equal to the optimal equilibrium yield, the benefit of a nitrogen reduction from the 2009 level to the optimal nitrogen level would be about 604 million DKK over a 10‐year time horizon, given a discount rate of 4% per year. However, if a recovery management plan is chosen, the benefit would only be about 49 million DKK over a 10‐year time horizon.     

THE EFFECTS OF DIFFERENT STRATEGIC VARIABLES IN NONCOOPERATIVE FISHERIES GAMES

Abstract In this paper, we use stock size, harvest quantity, and fishing effort as strategic variables. We model a two‐agent noncooperative fishery game, where the agents (nations) harvest a common fish stock. The planning horizon is infinite. The model is solved successively using one instrument at a time as the strategic variable in the game. The net present values of fishing and the escapement stock level from the three different models are compared to show how the choice of variables affects the results. The choice of strategic variable is not a trivial one, as the results are shown to be sensitive to the discounting, the stock's rate of growth, and the assumptions about the distribution of the fish in response to harvesting.     

Asset Pricing Using Finite State Markov Chain Stochastic Discount Functions

This article fuses two pieces of theory to make a tractable model for asset pricing. The first is the theory of asset pricing using a stochastic discounting function (SDF). This will be reviewed. The second is to model uncertainty in an economy using a Markov chain. Using the semi-martingale dynamics for the chain these models can be calibrated and asset valuations derived. Interest rate models, stock price models, futures pricing, exchange rates can all be introduced endogenously in this framework.     

Exploring the dynamics of financial markets: from stock prices to strategy returns

Exploring the dynamics of financial time-series is an exciting and interesting challenge because of the many truly complex interactions that underly the price formation process. In this contribution we describe some of the anomalous statistical features of such time-series and review models of the price dynamics both across time and across the universe of stocks. In particular we discuss a non-Gaussian statistical feedback process of stock returns which we have developed over the past years with the particular application of option pricing. We then discuss a cooperative model for the correlations of stock dynamics which has its roots in the field of synergetics, where numerical simulations and comparisons with real data are presented. Finally we present summarized results of an empirical analysis probing the dynamics of actual trading strategy return streams.     

On theoretical pricing of options with fuzzy estimators

In this paper we present an application of a new method of constructing fuzzy estimators for the parameters of a given probability distribution function, using statistical data. This application belongs to the financial field and especially to the section of financial engineering. In financial markets there are great fluctuations, thus the element of vagueness and uncertainty is frequent. This application concerns Theoretical Pricing of Options and in particular the Black and Scholes Options Pricing formula. We make use of fuzzy estimators for the volatility of stock returns and we consider the stock price as a symmetric triangular fuzzy number. Furthermore we apply the Black and Scholes formula by using adaptive fuzzy numbers introduced by Thiagarajah et al. [K. Thiagarajah, S.S. Appadoo, A. Thavaneswaran, Option valuation model with adaptive fuzzy numbers, Computers and Mathematics with Applications 53 (2007) 831–841] for the stock price and the volatility and we replace the fuzzy volatility and the fuzzy stock price by possibilistic mean value. We refer to both cases of call and put option prices according to the Black & Scholes model and also analyze the results to Greek parameters. Finally, a numerical example is presented for both methods and a comparison is realized based on the results.