1 Dynamic Economical Optimization of Sustainable Forest Harvesting in Russia with Consideration of Energy, other Forest Products and Recreation Peter Lohmander.

Slides:



Advertisements
Similar presentations
Boyce/DiPrima 9th ed, Ch 2.4: Differences Between Linear and Nonlinear Equations Elementary Differential Equations and Boundary Value Problems, 9th edition,
Advertisements

United Nations Statistics Division/DESA
Moving Up : Microscopes to Mirrors (Microeconomics to Macroeconomics) Microeconomics deals with individuals decisions made at a specific point in time.
METHODOLOGICAL BASES OF NATURE PROTECTION GEOINFORMATION SYSTEM CREATION Kyiv Mohyla Academy National Agricultural University V. Lavryk V. Bogolyubov
Boyce/DiPrima 9th ed, Ch 2.8: The Existence and Uniqueness Theorem Elementary Differential Equations and Boundary Value Problems, 9th edition, by William.
Brief introduction on Logistic Regression
1 Optimal CCS, Carbon Capture and Storage, Under Risk International Seminars in Life Sciences Universidad Politécnica de Valencia Thursday Updated.
Optimization Models Module 9. MODEL OUTPUT EXTERNAL INPUTS DECISION INPUTS Optimization models answer the question, “What decision values give the best.
1 Chapter 12 Forest Economics --Forests cover about 30% of the land surface of the earth; 8,000 years ago, this percentage was about 50 --More than 60%
LECTURE XIII FORESTRY ECONOMICS AND MANAGEMENT. Introduction  If forestry is to contribute its full share to a more abundant life for the world’s increasing.
Economic efficiency criteria n Static efficiency – Maximize net benefits of one optimal rotation n Dynamic efficiency – Maximize net benefits from continuous.
Global Thinking Measurement and Development Marina P. Bonser, PhD.
Decision Making: An Introduction 1. 2 Decision Making Decision Making is a process of choosing among two or more alternative courses of action for the.
Strategic options for the forest sector in Canada with focus on economic optimization, energy and sustainability - Motives for integration in a global.
Examining Clumpiness in FPS David K. Walters Roseburg Forest Products.
Tools for optimal coordination of CCS, power industry capacity expansion and bio energy raw material production and harvesting Peter Lohmander Prof. Dr.
OPTIMAL PRESENT RESOURCE EXTRACTION UNDER THE INFLUENCE OF FUTURE RISK Professor Dr Peter Lohmander SLU, Sweden,
A second order ordinary differential equation has the general form
Jeopardy comments/answers April Existence Uniqueness Each kind of differential equation we studied had a corresponding existence and uniqueness.
1 Methodology for optimization of continuous cover forestry with consideration of recreation and the forest and energy industries Методология оптимизации.
Definition and Properties of the Cost Function
ECON 6012 Cost Benefit Analysis Memorial University of Newfoundland
ECNE610 Managerial Economics APRIL Dr. Mazharul Islam Chapter-6.
Cost Behavior Analysis
1 A Stochastic Differential (Difference) Game Model With an LP Subroutine for Mixed and Pure Strategy Optimization INFORMS International Meeting 2007,
Optimal continuous cover forest management: - Economic and environmental effects and legal considerations Professor Dr Peter Lohmander
1 PhD Defence SLU, Dept. of Forest Economics Umea, Sweden, Author: Licentiate Scott Glen Cole, SLU Thesis: Environmental Compensation is not for.
1 Rational and sustainable international policy for the forest sector with consideration of energy, global warming, risk, and regional development An International.
CHAPTER 14 MULTIPLE REGRESSION
Chapter 6 The Theory and Estimation of Production
Linear Programming An Example. Problem The dairy "Fior di Latte" produces two types of cheese: cheese A and B. The dairy company must decide how many.
1 CM Optimal Resource Control Model & General continuous time optimal control model of a forest resource, comparative dynamics and CO2 storage consideration.
Various topics Petter Mostad Overview Epidemiology Study types / data types Econometrics Time series data More about sampling –Estimation.
5.3 Geometric Introduction to the Simplex Method The geometric method of the previous section is limited in that it is only useful for problems involving.
1 Optimal Forest Management Under Risk International Seminars in Life Sciences Universidad Politécnica de Valencia Thursday Peter Lohmander.
1 Some new equations presented at NCSU Peter Lohmander.
Thinning as a tool of close to nature forestry Igor Štefančík Forest Research Institute, Zvolen Slovakia.
RobOff methods and outputs 1.Uncertainty (info-gap) 2.Conservation value 3.Output space 4.Flow of aggregation and time discounting 5.Simple and score features.
1 Optimal dynamic control of the forest resource with changing energy demand functions and valuation of CO2 storage Presentation at the Conference: The.
Natural Resource Economics Academic year: Prof. Luca Salvatici Lesson 8: Forestry.
1 Optimal activities over time in a typical forest industry company in the presence of stochastic markets - A flexible approach and possible extensions!
Optimal continuous natural resource extraction with increasing risk in prices and stock dynamics Professor Dr Peter Lohmander
Discrete, Amorphous Physical Models Erik Rauch Digital Perspectives on Physics Workshop.
WOOD 492 MODELLING FOR DECISION SUPPORT Lecture 14 Sensitivity Analysis.
Data Analytics & Advisory Services Ann C. Dzuranin, PhD Associate Professor, Accountancy Northern Illinois University 2016 Deloitte Foundation/FSA Faculty.
COMPLIMENTARY TEACHING MATERIALS Farm Business Management: The Fundamentals of Good Practice Peter L. Nuthall.
Optimization of adaptive control functions in multidimensional forest management via stochastic simulation and grid search Version Peter Lohmander.
The Optimal Timing of Transition to New Environmental Technology in Economic Growth 2009 International Energy Workshop June, 2009 Fondazione Giorgio.
OPTIMAL STOCHASTIC DYNAMIC CONTROL OF SPATIALLY DISTRIBUTED INTERDEPENDENT PRODUCTION UNITS Version Peter Lohmander Professor Dr., Optimal Solutions.
Fundamental Principles of Optimal Continuous Cover Forestry Linnaeus University Research Seminar (RESEM) Tuesday , , Lecture Hall:
Production and Cost in the Firm
Stochastic dynamic programming with Markov chains
A general dynamic function for the basal area of individual trees derived from a production theoretically motivated autonomous differential equation Version.
Bio-economy opens opportunities for the growth of boreal forest sector
Thermal demand and related CO₂ emissions of buildings under climate change conditions in arid climates: A simulation study in Antofagasta, Chile M. Palme,
Environmental and Natural Resource Economics 3rd ed. Jonathan M
An International Project of the Future
Ch 11.1: The Occurrence of Two-Point Boundary Value Problems
Technical Change, Competition and Vertical Integration
Partners: AFOCEL/FCBA, Skogforsk, Forest Research, STFI-Packforsk, FVA
Forest management optimization - considering biodiversity, global warming and economics goals Workshop at: Gorgan University of Agricultural Sciences.
Forest management optimization - considering biodiversity, global warming and economics goals Workshop at: Gorgan University of Agricultural Sciences.
Continuous improvement is the process by which organizations frequently review their procedures, aiming to correct errors or problems. The most effective.
Forest management optimization - considering biodiversity, global warming and economics goals Workshop at: Gorgan University of Agricultural Sciences.
Adapted by Meryl Probst
Lohmander, P., Adaptive Optimization of Forest
Optimal stochastic control in continuous time with Wiener processes: - General results and applications to optimal wildlife management KEYNOTE Version.
Optimization Models Module 9.
BEC 30325: MANAGERIAL ECONOMICS
Presentation transcript:

1 Dynamic Economical Optimization of Sustainable Forest Harvesting in Russia with Consideration of Energy, other Forest Products and Recreation Peter Lohmander Professor Dr., SUAS, Umea, SE-90183, Sweden Zazykina Liubov PhD Student, Moscow State Forest 14 th SSAFR Systems Analysis in Forestry, Reñaca, Chile, March 8-11, 2011

2

3 Growth Compare: Verhulst, Pierre-François (1838). "Notice sur la loi que la population poursuit dans son accroissement"."Notice sur la loi que la population poursuit dans son accroissement" Correspondance mathématique et physique 10: pp. 113–121.

4

5

6 A separable differential equation

7

8

9

10

11

12

13

14

15

16

17 Stock (m3/ha) Time (Years)

18

19 The Present Value Function Profit from the first harvest Present value of an infinite series of profits from the later harvest

20 Initial stock level Rate of interest Harvest interval

21 * * *

22 y=250 y=200 y=150 Present Value Harvest Interval (Years) y = First Harvest Volume (m3/ha) (SEK/ha)

23 First Harvest Volume (m3/ha) Harvest Interval (Years) C = 500 Vertical Scale = Present Value (SEK/ha)

24 First Harvest Volume (m3/ha) Harvest Interval (Years) C = 500 Vertical Scale = Present Value (SEK/ha)

25 Harvest Interval (Years) First Harvest Volume (m3/ha) C = 500 Vertical Scale = Present Value (SEK/ha)

26 First Harvest Volume (m3/ha) Harvest Interval (Years) C = 500 Vertical Scale = Present Value (SEK/ha)

27 First Harvest Volume (m3/ha) Stock Level Directly After Harvest (m3/ha) C = 100

28 Stock Level Directly After Harvest (m3/ha) Harvest Interval (Years) C = 100 Vertical Scale = Present Value (SEK/ha)

29 C = 100 C = 500

30 Stock Level Directly After Harvest (m3/ha) Harvest Interval (Years) C = 100 C = 500 Vertical Scale = Present Value (SEK/ha)

31 C = 2000

32 Stock Level Directly After Harvest (m3/ha) Harvest Interval (Years) C = 2000 Vertical Scale = Present Value (SEK/ha)

33 Stock Level Directly After Harvest (m3/ha) Harvest Interval (Years) C = 100 C = 2000 Vertical Scale = Present Value (SEK/ha)

34 Stock Level Directly After Harvest (m3/ha) Harvest Interval (Years) C = 100 C = 500 Vertical Scale = Present Value (SEK/ha)

35 REM REM CCF0403 REM Peter Lohmander REM OPEN "outCCF.dat" FOR OUTPUT AS #1 PRINT #1, " x1 t h1 PV" FOR x1 = 10 TO 150 STEP 20 FOR t = 1 TO 31 STEP 5 c = 500 p = 200 r =.03 s =.05 x0 = 300 h0 = x0 - x1 x2 = 1 / (1 / (1 / x1 - 1 / 400) * EXP(-.05 * t)) h1 = x2 - x1 multip = 1 / (EXP(r * t) - 1) pv0 = -c + p * h0 pv1 = -c + p * h1 PV = pv0 + pv1 * multip PRINT #1, USING "####"; x1; PRINT #1, USING "####"; t; PRINT #1, USING "####"; h1; PRINT #1, USING "#######"; PV NEXT t NEXT x1 CLOSE #1 END

36 x1 t h1 PV

37 REM REM OCC0403 REM Peter Lohmander REM OPEN "outOCC.dat" FOR OUTPUT AS #1 PRINT #1, " C X1opt topt PVopt h1opt x2opt" FOR c = 0 TO 3000 STEP 100 FOPT = x1opt = 0 topt = 0 pvopt = 0 h1opt = 0 x2opt = 0

38 FOR x1 = 10 TO 150 STEP 5 FOR t = 1 TO 61 STEP 1 p = 200 r =.03 s =.05 x0 = 300 h0 = x0 - x1 x2 = 1 / (1 / (1 / x1 - 1 / 400) * EXP(-.05 * t)) h1 = x2 - x1 multip = 1 / (EXP(r * t) - 1) pv0 = -c + p * h0 pv1 = -c + p * h1 PV = pv0 + pv1 * multip IF PV > pvopt THEN x1opt = x1 IF PV > pvopt THEN topt = t IF PV > pvopt THEN h1opt = h1 IF PV > pvopt THEN x2opt = x2 IF PV > pvopt THEN pvopt = PV NEXT t NEXT x1 PRINT #1, USING "######"; c; x1opt; topt; pvopt; h1opt; x2opt NEXT c CLOSE #1 END

39 Optimal Stock Level Directly After Harvest (m3/ha) Set up Cost (SEK/ha)

40 Optimal Stock Level Directly Before Thinning Harvest (m3/ha) Set up Cost (SEK/ha)

41 Optimal Thinning Harvest Volumes per occation (m3/ha) Set up Cost (SEK/ha)

42 Optimal Harvest Interval (Years) Set up Cost (SEK/ha)

43 Optimal Present Value (SEK/ha) Set up Cost (SEK/ha)

44 What happens to the optimal forest management schedule if we also consider the value of recreation?

45 Source: Zazykina, L., Lohmander, P., The utility of recreation as a function, of site characteristics: Methodological suggestions and a preliminary analysis, Proceedings of the II international workshop on Ecological tourism, rends and perspectives on development in the global world, Saint Petersburg Forest Technical Academy, April 15-16, 2010, Alekseevskiy forest

46 Source: Zazykina, L., Lohmander, P., The utility of recreation as a function, of site characteristics: Methodological suggestions and a preliminary analysis, Proceedings of the II international workshop on Ecological tourism, rends and perspectives on development in the global world, Saint Petersburg Forest Technical Academy, April 15-16, 2010,

47

48

49 Interpretations and observations: #1: Several alternative interpretations are possible! #2: Furthermore, the results are most likely sensitive to local conditions, weather conditions etc..

50 Assumptions: The ideal average forest density, from a recreational point of view, is 0.5. Directly before thinning, the density is 0.8. As a result of a thinning, the density in a stand is reduced in proportion to the harvest volume. The density of a stand is a linear function of time between thinnings. The value of recreation is a quadratic function of average stand density in the forest area. The recreation value is zero if the density is 0 or 1. Under optimal density conditions, the value of recreation, per individual, hectare and year, is 30 EURO. (The value 30 has no empirical background.)

51 Approximation in the software: D =.8 * ((x1 + x2) / (2 * x2)) IF D < 0 THEN D = 0 IF D > 1 THEN D = 1 U = 120 * D * D * D PVtotU = n / r * U

52 N(Y) = Number of persons per 100 m2 a function of Y = Basal Area (m2/ha), Moscow DURING THE VERY HOT SUMMER OF 2010 Forest visitors seem to prefer forests with rather high basal area levels during hot periods.

53

54

55

56 What was the most popular basal area during the hot summer of 2010 from a recreational point of view?

57 Scenic Beauty, SB, as a function of basal area, BA. The graph has been constructed using equation SB = – BA/t ln (BA), which is found in Hull & Buhyoff (1986).

58 Optimization of present value of roundwood production and recreation

59 REM OP REM Peter and Luba REM OPEN "outOP.txt" FOR OUTPUT AS #1 PRINT #1, " n x1opt topt h1opt x2opt pvopt optPV opttotU" FOR n = 0 TO 550 STEP 55 pvopt = optpv = x1opt = 0 topt = 0 h1opt = 0 x2opt = 0 c = 50 p = 40 r =.03

60 FOR x1 = 10 TO 150 STEP 5 FOR t = 1 TO 100 STEP 1 x0 = 158 h0 = x0 - x1 x2 = 1 / (1 / (1 / x1 - 1 / 316) * EXP( * t)) h1 = x2 - x1 multip = 1 / (EXP(r * t) - 1) pv0 = -c + p * h0 pv1 = -c + p * h1 PV = pv0 + pv1 * multip

61 D =.8 * ((x1 + x2) / (2 * x2)) IF D < 0 THEN D = 0 IF D > 1 THEN D = 1 U = 120 * D * D * D PVtotU = n / r * U TPV = PV + PVtotU IF TPV > pvopt THEN x1opt = x1 IF TPV > pvopt THEN topt = t IF TPV > pvopt THEN h1opt = h1 IF TPV > pvopt THEN x2opt = x2 IF TPV > pvopt THEN optpv = PV IF TPV > pvopt THEN opttotU = PVtotU IF TPV > pvopt THEN pvopt = TPV NEXT t NEXT x1

62 Approximation in the software: D =.8 * ((x1 + x2) / (2 * x2)) IF D < 0 THEN D = 0 IF D > 1 THEN D = 1 U = 120 * D * D * D PVtotU = n / r * U

63 PRINT #1, USING "######"; n; x1opt; topt; PRINT #1, USING "######"; h1opt; x2opt; PRINT #1, USING "########.##"; pvopt; optpv; opttotU NEXT n CLOSE #1 END

64 Optimal results: ( outOP.txt)

65 Optimal stock level directly after harvest

66 Optimal stock level directly before harvest

67 Optimal thinning volume per occation

68 Optimal time interval between thinnings

69 In forest areas with many visitors, close to large cities, the present value of recreation may be much higher than the present value of timber production.

70

71 The case with no visitors

72 The case with many visitors that prefer low density forests

73 Conclusions: A new methodological approach to optimization of sustainable continuous cover forest management with consideration of recreation and the forest and energy industries has been developed. It maximizes the total present value of continuous cover forest management and takes all relevant costs and revenues into account, including set up costs. Optimal solutions to some investigated cases have been analysed and reported.

74 ABSTRACT Page 1(4) Peter Lohmander and Liubov Zazykina: (Peter Lohmander, Professor, Swed.Univ.Agr.Sci., Sweden and Liubov Zazykina, PhD Student, Moscow State Forest University, Russia) Title: Dynamic economical optimization of sustainable forest harvesting in Russia with consideration of energy, other forest products and recreation. Forests are used for many different purposes. It is important to consider these simultaneously. A new methodological approach to optimization of forest management with consideration of recreation and the forest and energy industries has been developed. It maximizes the total present value of continuous cover forest management and takes all relevant costs and revenues into account, including set up costs. In several regions, in particular close to large cities, such as Paris and Moscow, the economic importance of recreation forestry is very high in relation to the economic results obtained from traditional “production oriented” forest management.

75 ABSTRACT Page 2(4) This does however not automatically imply that production of timber, pulpwood and energy assortments can not be combined with rational recreation forestry. On the contrary: It is sometimes necessary to harvest and to produce some raw materials that can be utilized by the forest products industry and/or the energy industry, in order to avoid that the forest density increases to a level where most kinds of forest recreation becomes impossible, at least for large groups of recreation interested individuals. The optimization model includes one section where the utility of recreation, which may be transformed to the present value of net revenues from recreation, is added to the traditional objective function of the present value of the production of timber, pulpwood and energy assortments.

76 ABSTRACT Page 3(4) In several situations, individuals interested in recreation prefer forests with low density. This means that forest management that is optimal when all objectives are considered, typically is characterized by larger thinning harvests than forest management that only focuses on the production of timber, pulpwood and energy assortments.

77 ABSTRACT Page 4(4) The results also show that large set up costs have the same type of effect on optimal forest management as an increasing importance of typical forms of recreation, close to large cities. Both of these factors imply that the harvest volumes per occation increase and that the time interval between harvests increases. Even rather small set up costs imply that the continuous cover forest management schedule gives a rather large variation in the optimal stock level over time. The general analysis of the optimization problems analysed within this study is based on differential equations describing forest growth, in combination with two dimensional optimization of the decisions “harvest interval” and “stock level directly after harvest”. All of the other variables are explicit functions of these decisions.

78 ABSTRACT Peter Lohmander and Liubov Zazykina: (Peter Lohmander, Professor, Swed.Univ.Agr.Sci., Sweden and Liubov Zazykina, PhD Student, Moscow State Forest University, Russia) Title: Dynamic economical optimization of sustainable forest harvesting in Russia with consideration of energy, other forest products and recreation. Forests are used for many different purposes. It is important to consider these simultaneously. A new methodological approach to optimization of forest management with consideration of recreation and the forest and energy industries has been developed. It maximizes the total present value of continuous cover forest management and takes all relevant costs and revenues into account, including set up costs. In several regions, in particular close to large cities, such as Paris and Moscow, the economic importance of recreation forestry is very high in relation to the economic results obtained from traditional “production oriented” forest management. This does however not automatically imply that production of timber, pulpwood and energy assortments can not be combined with rational recreation forestry. On the contrary: It is sometimes necessary to harvest and to produce some raw materials that can be utilized by the forest products industry and/or the energy industry, in order to avoid that the forest density increases to a level where most kinds of forest recreation becomes impossible, at least for large groups of recreation interested individuals. The optimization model includes one section where the utility of recreation, which may be transformed to the present value of net revenues from recreation, is added to the traditional objective function of the present value of the production of timber, pulpwood and energy assortments. In several situations, individuals interested in recreation prefer forests with low density. This means that forest management that is optimal when all objectives are considered, typically is characterized by larger thinning harvests than forest management that only focuses on the production of timber, pulpwood and energy assortments. The results also show that large set up costs have the same type of effect on optimal forest management as an increasing importance of typical forms of recreation, close to large cities. Both of these factors imply that the harvest volumes per occation increase and that the time interval between harvests increases. Even rather small set up costs imply that the continuous cover forest management schedule gives a rather large variation in the optimal stock level over time. The general analysis of the optimization problems analysed within this study is based on differential equations describing forest growth, in combination with two dimensional optimization of the decisions “harvest interval” and “stock level directly after harvest”. All of the other variables are explicit functions of these decisions.

79 Thank you for listening! Questions?