The Economics of Ecosystem Based Management: The Fishery Case

Transcription

1 The Economics of Ecosystem Based Management: The Fishery Case Fisheries impact on marine ecosystem and policy implications Peder Andersen Co-authors: Lars Ravensbeck Hans S. Frost Department of Food and Resource Economics Faculty of SCIENCE University of Copenhagen 2013 Dias 1

2 Fisheries impact on marine ecosystem and policy implications Motivations: a) Increasing focus on Ecosystem Based Management of Fisheries /Marine Resources a) EU fishery policy 2013 proposal b) The application of economic theory to Ecosystem Based Management a) Enrich biological ecosystem analyses a) Empirical evidence a) Problem: Lack of data b) Policy implications c) The need for a research agenda with focus on the economics of the marine ecosystems Dias 2

3 Marine Ecosystem Services Ecosystem services are the contribution of ecosystems to the production of goods and services that generate human welfare or well-being. It is necessary with a clear distinction between ecosystem processes and functions, the latter often named intermediate ecosystem services, on one side and on the other, ecosystem services that contribute to the production of goods (services) that generates human wellbeing. Figure on next slide. With respect to fisheries: Ecosystems services described in the physical terms: Natural net growth of fish stocks The value of ecosystems services are net benefits, in some simple cases resource rent Dias 3

4 Marine Ecosystem Services Ecosystems are considered as capital assets which together with stocks of water, air and minerals form the portfolio of natural capital. The ecosystems provide a return or a stream of services for the benefit of humans. Ecosystems, ecosystems services and their value Ecosystems with structures, properties and processes Ecosystem functions Ecosystem services Other input Goods/ (services) Humans Benefits/ Values Dias 4

5 The importance of economics A. Ecosystem Based Management of the marine resources and areas has become a key guiding principle B. Economic incentives and policies are highly important to the successful implementation of Ecosystem Based Management C. Challenging combinations of the following well-known concepts: Externalities, Public goods, Open access resources, Joint and non-joint production. Dias 5

6 The importance of economics In a wider perspective we have multi-functionality of many environmental assets, as we obtain bundles of goods and services To what extent do we have joint production or when do we have to make trade-offs? How does the presence of externalities and public goods interact with multi-functionality? Will empirical evidence that includes several and possibly conflicting ecosystem services point to (very) different policy recommendations for fisheries management? Dias 6

7 Basic challenges The starting point for an assessment of ecosystem services is an identification and quantification of these services in the physical sense and of the changes to be valued However, valuation of ecosystem services are still to a large extent impeded by limited scientific knowledge about the processes and functions of the ecosystems One of the main reasons why ecosystem services are difficult to assess is the complex relations within the ecosystem Also, problems arise from the fact that ecosystems are nonlinear complex systems with strong interconnections among elements Such characteristics lead to the existence of path dependency that can lead to different states and to regime shifts, as well as thresholds that if exceeded can lead to major and irreversible ecological damages Dias 7

8 Challenges In ecosystem based management we aim at estimating the marginal costs and benefits for optimal management Hence, we must aggregate several values related to marketable and non-marketable goods - private as well as public/common goods A generalised simple model assuming joint production Dias 8

9 Optimal production of ecosystem services An example of private good and public good ecosystem services and joint production Dias 9

10 Challenges Trade-offs and synergies Pure win-win situations are rarely available, usually trade-offs have to be carried out. Although there may be reductions in some services an increase in the number of ecosystem services will in most cases provide an increase in the total value of these services and thereby also a positive contribution to increased human welfare or well-being. Dias 10

11 Commercial fishing and other interests Monotonic concave trade-off Dias 11

12 The fisheries model A model for optimal management of a multiple species and multiple fleet fishery, which captures three main elements; fishing profit, non-fishing values and externalities with respect to fishing. The goal of the fishery management is to maximize the net present social value, S, of a multi-species fishery by choosing effort in each period. Objective function: subject to: dx i /dt = g i (x) - h ij (e ij, x i ) Dias 12

13 where: The fisheries model π ij (e ij (t ), x i (t)) = [p i -c ij ] h ij (e ij, x i ) = profit (or resource rent) from fishing species i for fleet j in period t. v i (x i (t)) = non-fishing value of species i in period t, e.g. recreation, non-use (existence) value. v i (x i (t)) 0. d ij (e ij (t)) = externality of fishing activities related to species i and fleet j in period t, e.g. damage on seafloor, discards, impact on fishing communities. In most cases d ij (e ij (t)) is negative in effort, but it can be positive (e.g. impact on fishing communities). e ij (t) = effort for species i and fleet j in period t. e ij (t) 0. x i (t) = stock of species i in period t. x i (t) > 0. x = (x 1, x 2,, x i ). g i (x) = r i x i [1- x i / K i ] + α i x i x = growth of species i. g i 0. The simple logistic growth function has been used here as the basis. h ij (e ij, x i ) = q ij e ij x i = g i ( in equilibrium). Harvest of species i for fleet j. h ij (e ij, x i ) 0. Dias 13

14 The fisheries model In addition we have: r i = intrinsic growth rate of species i. r i = 0. K i = carrying capacity of species i. K i > 0. α i = constant that relates to species interaction. q ij = catchability coefficient for species i and fleet j. p i = price of species i. p i 0. c ij = cost per unit of harvest for species i and fleet j. c ij 0. n = number of species, n N m = number of fleets, m N i = species number, i = 1,, n j = fleet number, j = 1,, m t = time. δ = discount rate. δ 0. Dias 14

15 One scenario North Sea Cod-Herring fishery Case: North Sea Predator (cod) Prey (herring) Age structured model Fixed proportions of the catch: Fleet 1 catches 75 % of the cod and fleet 2 catches the remaining 25 % and all the herring. Examples: 1) One fleet and one species (cod) 2) One fleet and two species and joint production 3) One fleet, two species, joint production and damage 4) Two fleets, two species, joint production for fleet 2 and damage. 5) Maximization of resource rent for example 4. Dias 15

16 Example 4 assumptions (two species two fleets) Using an age structured model includes many parameters for fishing and natural mortality rates on age groups, intrinsic growth etc. The magnitude of these parameter and the species interaction specification play a very significant role for the results not only the level of the yield curves but also the shape of the yield curves The fleets catch simultaneous a sort of game The share of catch of the predator is fixed between the two fleets The proportion of fishing mortality between predator and prey is fixed for fleet 2 Dias 16

17 Model development The model is developed into a net benefit maximization model with less restrictions - Hence it is possible to evaluate the impact of: Relaxing assumptions about fixed allocations between fleets Various damage costs and non-use values The net benefit maximization result (effort allocation etc.) differs from the result in the simulation presented in example 4 Dias 17

18 Data for the North Sea Cod-Herring scenario Department of Food and Resource Economics Species Predator (cod) Prey (herring) Age structured; age Recruitment at age mill fish 3000 mill fish Recruitment at age 2 (where fishing begins) 250 mill fish 2500 mill fish Natural mortality rate own age Natural mortality rate own age Fishing mortality rate age Fishing mortality rate age Von Bertalanffy growth; weight at age kg kg Predator preys on prey age groups 0-5 Predator mortality depends on abundance of prey age groups (starving coefficient) in proportion to base case Model runs over (not in balance at t=0) 20 years 20 years The vector for fishing mortality rates is varied between Fishing the fishing mortality rate and effort linear linear Catches for each age group determined by Baranov equation Baranov equation Dias 18

19 Revenue and costs Department of Food and Resource Economics Single species case one fleet (1) Max resource rent TR Resource rent TC Effort Dias 19

20 Revenue and costs Department of Food and Resource Economics Two species case one fleet and joint production (2) Optimal solutions Total revenue Predator MSY TR-predator Fishing costs Prey MSY TR-prey Opt. solutions: Single Two species Effort Dias 20

21 Revenue and costs Department of Food and Resource Economics Two species case one fleet, fishing damage and joint production Total ecossystem costs Total revenue Green:Optimal solution Predator MSY Fishing cost Prey MSY Place and date Dias 21 Effort Predator Prey Total revenue Total fishing costs Total costs

22 Revenue and costs Department of Food and Resource Economics Two fleets, two species, joint production for fleet Total costs incl. damage Total fishing costs Total revenue Optimal solution Without damage Fishing costs fleet 2 Revenue fleet Revenue fleet 1 Fishing costs fleet Effort for each fleet Dias 22

23 Revenue and costs Department of Food and Resource Economics Two fleets, two species, joint production for fleet 2 and damage costs Total costs incl. damage Total fishing costs Total revenue Optimal solutions Without damage With damage Fishing and damage costs fleet 1 Fishing costs fleet 2 Revenue fleet Fishing costs fleet 1 Revenue fleet 1 0 Effort for each fleet Dias 23

24 Maximization of net benefit policy implication Preliminary result: Solution is improved marginally by a different catch and effort composition between the fleets In the presented one fleet two species example the optimal solution is almost identical to the optimal management of the cod stock Preliminary policy implication: Optimal allocation of TACs between fleets depends on relative prices of prey/predator, fishing costs, and catch per unit effort and damage costs/non-use values In principle: an advanced tax system can give optimality In principle: An advanced AITQ system (Adjusted Individual Transferable Quota) can give optimality An ecosystem based fisheries management system is a challenge from a practical point of view, it is data demanding and complicates international solutions (e.g. EUs relative stability pact) Place and date Dias 24

25 Conclusions/questions for discussion: 1. Perhaps the value of extending analyses from simple bioeconomic models to complex bioeconomic-ecosystem models (in some cases) is minor only solid empirical analyses can show? 2. The scientific value versus management gains by using complex bioeconomic-ecosystem models? 3. And: a) Do we need more theory? b) Do we need a new research agenda for the Economics of Ecosystem Based Fisheries Management? c) What are the main scientific questions? Dias 25

26 Thank you Place and date Dias 26