Sustainable Use and Conservation of Marine Living Resources

Transcription

1 Sustainable Use and Conservation of Marine Living Resources by Jürgen E. Blank Abstract Fisheries management models including fishing firms and regulators behaviour, multi-species fisheries, and even uncertainty are analytically intractable. In the case of fishery, management simulation models are more appropriate. Complex simulation models can evaluate different kinds of regulation measures and their impacts on the dynamics of the population of different species. The recommendation for any regulation authority is not an optimal solution, but may be yield in some rule-of-thumb recommendations. Especially individual transferable quotas cannot solve all the problems in fisheries management, but in connection with a variety of some further measures they may ensure a sustainable use and the conservation of some living marine resources. But other aspects than only the biomass aspect of the seas should be taken into account too, like ecological services, biodiversity and recreation possibilities. In case of transboundary fish stocks or for fisheries in the open seas, a scheme of transnational jurisdiction has to be implemented. Aquaculture, although supplying the market with this particular specie, it is not an instrument to secure the sustainability of the marine system. Correspondence address: Jürgen E. Blank Westfälische Wilhelms-Universität Münster Lehrstuhl für Volkswirtschaftstheorie Universitätsstr D Münster Phone: +49 (0)251 / jubl@wiwi.uni-muenster.de

2 Introduction In the traditional economic theory market entry is in generally as the key assumption, which leads to an efficient and optimal resource allocation. In contradiction to the standard theory open access in natural renewable resource markets leads to inefficiencies. This becomes particularly clear by the example of the fishery industry. Open access gives rise to a lot of economic and ecological problems: Inefficient use of factor inputs, overfishing, and even the extinction of fish species. The economic analysis of these problems can be originated to the seminal work of H. Scott Gordon (1954) and Anthony D. Scott (1957). Whereas Gordon s paper offering a simple model describing the rent dissipation process under an open access regime, Scott s paper was more normative, and addresses the question, how the fishery industry should be managed to achieve an optimal outcome. Most of the economic literature on renewable resource management deals with the question Scott raised by using sophisticated dynamic optimal control models. In these models a social planner tries to maximise the present value of rents. These kinds of models are applied to one-species and to multi-species systems. The latter are often compare the Nash non-cooperative solution to the joint management equilibrium solution. But, besides of the enormous intellectual effort done to reach at least some basic necessary conditions for an optimal steady-state resource use, these models are only of little practical meaning for fisheries management. Real world fisheries doesn t occur under pure open access nor under a rent maximising regime. The latter requires the allocation of exclusive property rights for the marine resource. Even since most of the world s fisheries comes under some kind of national or international jurisdiction, there is no exclusive property rights nor pure open access found in the fisheries. Since some kind of regulation rules the coastal and the high seas fisheries, it should be questioned, how fishing firms react to regulations. Even the motivation and the behaviour of the regulator should be mentioned. Why and what kind of instruments are applied to regulate the fisheries? This paper addresses the question what should be considered in modelling the economics of fisheries to get a sustainable use of marine living resources. A special focus lies on the individual transferable quotas (ITQ), whether they are particularly well suited for a sustainable use in fisheries management or not. This paper begins with a short overview of the basic economic models used in the renewable resource theory, which most readers will be familiar. A short description of real life fishing management models is given in section 2. In section 3 the concept of individual transferable quotas are discussed. Section 4 mentioned the question whether aquaculture may be an alternative or not. Section 5 concludes this paper. 2

3 1 Economic modelling of marine living resources 1.1 The Schaefer-Gordon Model Schaefer (1954) assumed that the population dynamics of a single-species fish stock is a function of its size and weight. The biomass will grow towards some maximum weight, the carrying capacity, where it will remain. The growth function F X b g is often represented as a logistic function as illustrated in figure 1.1 and can be represented mathematically by: b g c b g h b g b g b g F b gi HG KJ X t = F X t, t = ax t 2 X t bx t = rx t 1 (1.1) K In equation (1.1), r represents the intrinsic growth rate and K they carrying capacity.. X MSY F(X) 0 X MSY K X Figure 1.1:Sustainable yield and biomass in the Schaefer model The Schaefer growth curve represents an idealized simplification of a regeneration function. The Schaefer model is deterministic, it assumes complete information about the relevant biological data. It regards a homogeneous resources stock under constant environmental condition for spatially evenly distributed species. If the stock is used for example by fishery activities, then the equation for the stock dynamics (equation (1.1)) changes too: b g b g (1.2) b g describes the catch quantity, which is harvested in time t. If the catch is Ẋ = F X Y t The variable Y t covered away by the increase in biomass exceeding the natural mortality, the yield can be sustained, hence: Fb Xg = Y (1.3) 3

4 Each point on the logistic growth curve in figure 1.1 represents thus the sustainable yield of fish with respect to the stock. With exception of the maximum sustainable yield (MSY) each catch quantity is attainable with two stock levels. In order to use the resources stock, factors of production must be used as combination of work and capital. This input is described as effort E. For simplification effort is described as the number of the catch hours or days per season. Thus yield is a function effort and of the stock itself: b g (1.4) Y = G E, X = E X With given stock the yield increases as effort rises. With given effort the yield increases as the stock increases and vice versa. Formally this corresponds to a production function, which the stock and the catch expenditure enter as input factors, obtaining the catch quantity as output. Just, the Schaefer curve can easily be transformed to an effort-yield curve, i.e. yield is a function of effort. Assuming that a unit of landed fish can be sold on the market at a constant price p, the effort-yield curve can be illustrated as the fishing industries total revenue curve TR. Assuming further a constant cost c per unit of effort, total costs TC are just a linear function of effort. Both are shown in figure 1.2. TC, TR Rente TC=cE MC, AR, MR 0 TR=pY(E) E AR MR Rente AC=MC=c 0 E MEY E OA E Figure 1.2: Bioeconomic and efficient equilibrium 4

5 The difference between total sustained revenue TR and total cost TC is the so called sustainable economic rent. The maximum economic rent is reached at the level of effort of E MEY, where the difference between TR and TC is at its maximum and marginal revenue equals marginal cost. In open access fisheries, the rent will be dissipated over time. The fishery will reach a bioeconomic equilibrium at the level E OA, at which total revenue equals total cost. In the long rum effort cannot exceed E OA, because costs would exceed revenue and at least some fishing firm would leave the fishing industry taking up alternative activities. A level below E OA would induce fishing firms to enter the fishery attracted to revenue greater than they can achieve elsewhere. Note that neither the open access yield nor the maximum sustainable yield (MSY) is economic efficient. In the very simple model of the Gordon-Schaefer approach market price for a unit of landed fish is given and fix. If price is variable, one can derive the so called backward bending supply curve of the open access fishery. In figure 1.3 the backward bending supply curve is shown. The curves labelled D in (b) represents different demand curves. It can be easily seen, that the amount of catch at the level Y 1 is a bioeconomic equilibrium corresponding to the demand curve D 1 as well as to the demand curve D 3. But at different costs of fishing. Since each point on the backward-bending supply curve is a bioeconomic inefficient equilibrium, the welfare lost well grow further more if price will rise along the backward-bending slope of the curve. Any market price for a unit of landed fish exceeding 2c K P results in biological overfishing. p S S p 3 2c K c K Y MSY Y 1 Y 2 a) langfristige a) Angebotskurve b) p 2 p 1 D 1 D 2 D3 Y Figure 1.3: Backward-bending supply curve 5

6 1.2 The dynamic extension of the Gordon-Schaefer model The static Gordon-Schaefer model can easily be extended to a dynamic approach. The dynamic version of the Gordon-Schaefer model is like the intention of Scott more normative, asking: how should marine living resources be managed for the societies benefit? Target is the maximization of the present value of the resources use by a resource manager, who has to consider the regeneration function of the resources as a binding restriction. s.t. δt max Π X, E = p c X Q e dt Q ( ) ( ( )) 0 Ẋ = F( X ) Q and 0 Q Q Q Q (1.5) min MSY max (1.6) Setting up the Hamiltonian and applying the maximum principle leads to the steady-state solution: c ( ) ( ) X * F X * F ( X *) = δ (1.7) p c( X *) Equation (1.7) is an implicit equation for the resources stock X and has the unique determined solution X = X *. The equation is central for the optimal management of a fish stock. The steady-state catch must be controlled in such a way that the "marginal productivity of the fish stock " equals the discount rate. 1.3 The Beverton-Holt Model The biological framework of the logistic growth function in the Gordon-Schaefer model is very simple. All biological informations represented by the parameters intrinsic growth rate and the carrying capacity. Furthermore, one of the fundamental problems of this type of model exists in the assumption of the homogeneity of the resources stock. Since fishing gear have a varying selectivity pattern for different size of fish and most stocks consist however of individuals of different age and weight, the assumption of a homogenous fish stock is far away from realism. The commercial value and the reproduction potential of resources depend generally on the age or weight of the individual fish. Gear selectivity means that all fish smaller than a certain size will escape, but all fish equal or bigger than that mesh size are caught. In case that mesh size is close to the catch size of fish that are old enough to spawn, depletion cannot occur. A model using year-class features was developed for practical purposes in the North Sea fishery by the British biologists R. J. Beverton and S. J. Holt. For certain questions it is meaningful to use models in which the fish stock distinguish to such individual criteria. However the model implementation turns out to be very difficult due to insufficient data gathering possibilities. The model finds nevertheless application in the fishery, for example on the North Sea plaice, the 6

7 Atlantic haddock and the Peruvian anchovies. Non suitably is this approach for species, which spawn only towards the end of their life, like salmon. For an optimal catch policy the determination of the age of the fish, when catched and landed, and the amount of effort for a given fishing season is of importance. Depending upon mesh size one receives different yield curves. The larger the meshes, the more largely the maximum yield becomes, but it corresponds to a higher fishing mortality rate. The envelope to all the individual yield curves is called the eumetric yield curve. Since the fishing mortality is stock-independent and regarding the assumption of sustainable yield in proportion to effort, only points on the eumetric yield curve can be efficient. All realizable catches below the eumetric yield curve are inefficient. To each mesh size there exists an associated level of effort, which realized an efficient, but not necessarily optimal catch. The optimal catch policy is determined by two factors. The first factor is the determination of the fishing rate Y, which is in proportion to effort (Y = E). If effort increases, the fish stock will decrease and the average weight of the fish stock decreases too. The second factor is the determination of the size of the fish. The more largely the mesh size, the more largely the landed fish will be. An increase in the mesh size will at first reduce the yield but finally increase the biomass. The optimal policy have to determine the optimal mesh size and the fishing rate / effort simultaneously. Y Y eum Y µ3 Y µ2 Y µ1 y=e Figure 1.4: The eumetric yield curve With open access to a common pool resource two effects have to be considered. On the one hand the effort is expanded in such a way that the economic rent will be dissipated. This effect leads to the bioeconomic equilibrium, like in the Gordon-Schaefer model. On the other hand it has to be expected that fishing firms will use sufficiently small mesh sizes, in order to catch any available fish of commercial value. Thus the case of open acces without any regulation implies a so-called growth overfishing. The effort can achieve an equilibrium, in which the economic rent 7

8 dissipates. In this situation overfishing results from to much effort and non-eumetric mesh sizes. A regulator, who wish to achiev an optimal allocation of the resources, has to control both the effort E and the mesh size µ. With open access the fishing industry stops in a bioeconomic equilibrium, described by C in figure 1.4. In C the total cost equals total revenue of the fishing industry, determining the corresponding mesh size µ 3. This bioeconomic equilibrium is not stable. As long as fishing firms are able to choose their mesh size, they will have an incentive to reduce the size to raise their catch. A reduction of the mesh sizes leads to raise in economic rents represented by the difference between the TC line and the TR curve, like the distance AB with less effort E 1 but smaller mesh size µ 2. A reduction in mesh sizes leads to higher catches and a reduction in effort. With the mesh size µ 1 a bioeconomic equilibrium is achieved in point B. However this is not efficient, since it is not on the eumetric yield curve. With effort E 1 the corresponding mesh size should be would be µ 2. The optimal allocation is given by point D with optimal effort E 0 and mesh size µ 1. Therefore a regulator who wish to achieve an optimal outcome has to determine both: effort and mesh size. TR TC TC Y m2 A C TR=pY eum D Y m1 B py m1 py m2 py m3 E E 0 E 1 E 2 Figure 1.5: Equilibria in the Beverton-Holt model Even the static Beverton-Holt model is related to the static Gordon-Schaefer model, dynamic optimization in the Beverton-Holt model becomes very complex and only simple versions are tractable, for extensions numerical methods are commonly used, especially in fishery management models. 8

9 1.4 Multi-Species Approaches In the single-species models intra and interspecific relations are considered only in form of summarized constant parameters. For economic analyses it is also of importance, in which way fish stocks are merged into a more complex ecological system. Therefore it is necessary to consider the interaction among different species in the economic management explicitly. For simplification and for didactical reasons multi-species models are limited to interactions between two species, which are basically reducible to three types: Predator-prey relations with (mostly) mutual de- or increase or oscillations of the stocks; Symbiosis relations, which is in favour of both species; Competition relations, in which due to inter-species competition both species are influenced negatively. Ecological interactions, which can be described by predator-prey relations, are preferred in the economic modelling of optimal resource use. These approaches are either normative asking: whether an optimal solution exists and whether it is stable. Game theoretic approaches comparing the efficient outcome and the Nash-solution are modelled too. These models are very stylized. Multi-species models together with multicohort age-structured biomodels are used in numeric fisheries management models. Even a game theoretic framework is incorporated, like in the Barents Sea fishery model by Sumaila (1997). 2 Fisheries Management models Actual management models as used in the fishery partly consider a whole range of biological data, like age and size structure, sex differentiation, spatial as well as multi-species relationship, gear selectivity, etc. Figure 2.1 shows a simple model for the Islandic cod. Minke Fin Humpback Cod Ricker or Beverton-Holt -function, cannibalism, weight, food Capelin stock cycles (stochastic), food Shrimps production -function, food Figure 2.1: A simple model for the Islandic cod (Stefansson, 1998) 9

10 To enlarge this biological models incorporating fishing fleets, areas, fishing seasons and other components of interest is a due to the huge amount of data needed, is nearly impossible. A lot of components are needed, like a model for revenues and costs for different fishing policy alternatives. Fisheries management within the biological tradition seeks to affect the structure of fish population by controlling the relative size of different species and year-classes through regulation measures like territorial and seasonal restrictions, gear and appliance restrictions, mesh size, size regulation for landed fish, fleet restriction, etc Before the concept of individual transferable quotas is to be examined in more detail, we will have a look at the regulator s behaviour. 3 Regulator s behaviour In modelling the optimal use of living marine resources, no or little attention has been paid to what regulators do in practice. Institutional economics may give some hints how regulators may behave. Even the objective function regulaters are using in fisheries management is not quite clear, whether thy maximizing the present value of profits or maximizing the present utility of consumption. Wilen and Homans (1998), showed that regulators are balancing stock safety goals against the short-term costs that attaining these goals may place on the industry. Therefore, regulators try to smooth the effect of instruments on the industry. However, economists are in favour of the optimization problem imposed by Scott, rather of management questions like how the fishing industry will be affected by any regulation measurement. Economists so far have just argued that non-market instruments will shift the total cost curve in such a way, that any economic rent will be dissipated again, with less effort and a larger fish stock. Market instruments like a tax on effort or on landed fish or ITQs would guarantee an efficient outcome and a sustainable use of marine living resources. Nevertheless, non-market instruments are very common in fisheries management. see the EU Common Fisheries Policy (CFP), seems far away from success. Fish stocks are still overfished, economic rent still dissipates. These instruments are neither economic efficient nor ensure conservation. Like the economic models the fisheries management models neglect both the motivation and behaviour of the regulator and the fishing firm reaction to the regulation measures. Economists are in favour of economic efficient instruments like taxes or transferable quotas. The letter is already implemented as individual transferable quotas (ITQ) in many countries including Australia, Canada, Iceland, New Zealand, Norway, the USA, and the Faroe Isles. ITQs are seen as an instrument to overcome the problem of the tragedy of the commons, by instituting property rights to the fishing stocks. The aim of the ITQ is to reduce overfishing, downsize the overcapitalized fishing industry and to avoid detailed regulation. The following section shows, that ITQs cannot overcome this problems. 10

11 4 Individual Transferable Quotas (ITQ) ITQs are usually a fraction of the total allowable catch (TAC) set by the regulation authority for a particular species. Assumed, the TAC corresponds to the optimal steady-state fishing stock or corresponds to the optimal path reaching the steady state stock, then ITQs will lead to an optimal resource allocation. The economic rent then will be maximized, because the individual fishing firm will include all user costs into their objective function. But it is necessary that the fishery is perfectly monitored and enforced. Since the extension of the Exclusive Economic Zone (EEZ) to 200 nautical miles, nearly 90% to 95% of worldwide catch is under some kind of national jurisdiction, the implementation of ITQ should be affordable. Besides its theoretical advantage there are arise quite a lot impediments in the real life. A number of problems are already discussed by Copes (1986). Some of the problems are presented and suggestions how to overcome the impediments are discussed in the following section. Quota busting Quota busting or smuggling arises when more fish are caught and landed than the individual quota allows. The extent of compliance is at a large amount due to monitoring and enforcement efforts. In coastal fisheries, in which vessels return to their home port and land their catch there, quota busting is a problem which can be neglected as long as there is only a small number of marketing channels. Traditionally landed catch is marketed by local co-operatives besides local direct marketing on a low level. If there is a lot of marketing channels the problem of quota busting will become much more severe, especially if there are a lot of different landing places. In case the catch is landed outside the area controlled by the national or regional regulator, quota busting will be much easier. To avoid quota busting the marketing channels have to be regulated too. High-Grading and Multi-Species fisheries A fishing firm, confronted by an individual quota will wish to obtain the maximum amount of net value from that quota. Since the ITQ does in general not regulate the amount of fish that is harvested, but rather the amount that is landed and brought to market. Fishing firms may want to fill the quota with the best quality of fish. Fish of less quality results in a lower market price than fish of high quality, therefore the fishing firm has an incentive to High grade the catch by discarding fish of lower quality. Since discarded fish have a very high mortality rate, and since they are not reported, the regulator gets wrong information on the fishing mortality leading to an overexploitation of the resource. This problem arises in multi-species fisheries, too. Typically a TAC is set for each specie in a multi-species fisheries. But it is not sure, that catching the fish can 11

12 be done separated. Therefore, not only the target specie would be caught but also other species as by-catch. By-catch will often be discarded, even if quotas are transferable. By-catch species might be of less value, the hold should not be wasted for fish of lower value than the targeted species. An instrument to avoid high-grading is to emit value-based ITQs, which gives the allowance to land a certain value of each particular type of fish. Setting the Value-TAC the regulator is confronted with two unknowns: The market price and the amount of caught and landed fish. There is some evidence that the quota-induced discarding problem might be reduced (Turner 1995). To avoid discarding in multi-species fisheries, a value based ITQ, might be more appropriate. Efficient allocation is not guaranteed From a theoretical viewpoint the TAC would be optimal allocated by ITQ among the fishing firms. In practise, ITQ may not be utilized due to some problems with the fishing gear and no transfer to other fishing firms is possible due to time restrictions. Therefore the TAC will not come into full effect. One might argue that this effect will oppose quota busting, but it is not guaranteed, that one effect makes up for the other. The amount of the shortfall in total catch cannot be determined in advance. In case of straddling or highly migratory fish stocks the problem of underutilization of the TACs is much more serious because fish stocks may leave the quota area earlier than expected, i.e. the season would be much shorter than anticipated. Volatile stocks For many species a TAC cannot not determined at the beginning of the fishing season, because the are short living and the stock can be characterized by instability in biomass. Many pelagic species like herring fall into this category. Therefore only tentative TACs can be announced in advanced, encouraging fishing firms to race for the fish. Spatial distribution of effort Fish species are not distributed equally within the fishing area but have different stock densities on various grounds. Fishing firms will go to the profitable grounds first, to achieve this, they will invest in fishing gear. Profit per unit of effort will decline, the rent will be dissipated. As long as the individual quota is not filled, this behaviour results in an open access fisheries like outcome, with a lower loss of rent, but still with a loss. 12

13 Residual catch management In fisheries where the catch is managed by an escapement target, ITQs are inappropriate. An escapement target means, that not the catch is the target, but the escapement and that the catch will be the residual. The rate of escapement is determined in such a way, that it guarantees the sustainable use of the fish stock. As an example for residual catch management the Northeast Pacific salmon fisheries can be mentioned. 5 Is aquaculture an alternative? Aquaculture is the farming of fish species in an attempt to generate profit and aid in conservation of marine living resources. The fish are raised in large submersible cages in the coastal seas. Therefore, nearly no effort in harvesting the catch is needed, just lift the cage and the fish is already caught. Aquaculture has a long tradition in fresh water fish farming. In the coastal seas fish farming starts with the production of high priced in Southeast Asia in the early 80s. Norway and Scotland started fish farming in the 70s by producing high priced salmon. Aquaculture results in a much more constant and secure supply of this particular species in comparison to the traditional method of fishing. Since aquaculture is very efficient production method. Fish are raised in huge cages, harvesting is easy, just lift the cage, and the fish are caught. The harvest of the open seas fish will be reduced, due to the costs in effort. But this only holds, if farmed fish and the open seas fish are seen as perfect substitutes. This is not always the case, as the demand for salmon demonstrates, total demand for salmon is raising, but the demand for the wild salmon is raising to. But there are quite a lot of negative aspects, which should be mentioned: Escaped fish compete with open seas fish, genetic mutation and weakening the biodiversity of the oceans will occur. External environmental effects occur directly by destroying the mongrove forest in Southeast Asia for the implementation of fish (shrimp) farms. Other negative external effect are the use of pesticide, antibiotics. Uneaten fish food and fish excrements remain in the water, destroying marine life by reducing the oxygen especially on the bottom. The species which are commonly farmed are typically predators, they need other fish as food. The fish food is mainly made by fish meal. As a rule of thumb, for a kilo of salmon a kilo of fish meal have to be produced. Fish meal is produced from small species like the capelin, but these species are typically prey species. If they are caught intensively, food supply for predator species will be reduced. 13

14 6 Conclusion Models including fishing firms and regulators behaviour, multi-species fisheries, and even uncertainty are analytically intractable. In the case of fishery, management simulation models are more appropriate. Complex simulation models can evaluate different kinds of regulation measures and their impacts on the dynamics of the population of different species. The recommendation for any regulation authority is not an optimal solution, but may be yield in some rule-of-thumb recommendations. Especially individual transferable quotas cannot solve all the problems in fisheries management, but in connection with a variety of some further measures they may ensure a sustainable use and the conservation of some living marine resources. But other aspects than only the biomass aspect of the seas should be taken into account too, like ecological services, biodiversity and recreation possibilities. In case of transboundary fish stocks or for fisheries in the open seas, a scheme of transnational jurisdiction has to be implemented. Aquaculture, although supplying the market with this particular specie, it is not an instrument to ensure the sustainability of the marine system. 14

15 References Beverton, R. J. H. and Holt, S. J. (1957): On the Dynamics of Exploited Fish Populations. Ministry of Agriculture, Fisheries and Food, Fisheries Investigation Series 2(19), London Copes, P. (1986): A Critical Review of the Individual Quota as a Device in Fisheries Management. Land Economics, 62 (3), Gordon, H. S. (1953): An Economic Approach to the Optimum Utilization of Fisheries Resources. Journal of the Fisheries Research Board of Canda 10. S Gordon, H. S. (1954): The Economic Theory of a Common Property Resource: The Fishery. In: Journal of Political Economy 62, S Schaefer, M. B. (1954): Some Aspects of the Dynamics of Populations Important to the Management of Commercial Marine Fisheries. Inter-American Tropical Tuna Commission Bulletin 1, S Schaefer, M. B. (1957): Some Considerations of Population Dynamics and Economics in Relation to the Management of Marine Fisheries. Journal of the Fisheries Research Board of Canada 14, S Scott, A. D. (1955): The Fishery: The Objectives of Sole Ownership. Journal of Political Economy 63, S Stefansson, G, (1998): Statistical and other fisheries models. Sumaila, U. R. (1997): Strategic Dynamic Interaction: The Case of Barents Sea Fisheries. Working Paper 1997/1, Chr. Michelsen Institute, Bergen, Norway. Wilen, J. E. and Homans, F. R. (1998): What regulators do? Dynamic bshaviour of resource managers in the North Pacific Halibut Fishery Ecological Economics, 24,