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MARV 15 Mathematical methods for forest planning

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we can predict how trees grow. we can do treatments whose effects can be predicted ... silviculture: getting costs. we can compare costs and benefits ... – PowerPoint PPT presentation

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Title: MARV 15 Mathematical methods for forest planning


1
MARV 15Mathematical methods for forest planning
  • Juha Lappi

2
Forest planning at stand and forest level
  • starting point of planning
  • we can predict how trees grow
  • we can do treatments whose effects can be
    predicted
  • harvests getting timber
  • silviculture getting costs
  • we can compare costs and benefits
  • uncertainty expected value/variance

3
Economic planning
  • measure costs and benefits in euros
  • predict price development
  • price of money interest
  • saving interest/interest for loans
  • in forestry long time horizon how to compare
    euros in different time points

4
stand/forest
  • planning can be made at stand level, if it holds
    for income and costs
  • euro_t(stand1stand2) euro_t(stand1)euroja_t(sta
    nd2)
  • holds if labor and machines have unlimited
    availability at fixed price and price of timber
    does not depend on the amount
  • utility(euro_t1 euro_t2) utility(euro_t1)hyöty
    (euro_t2)

5
Present value
  • How to compare money flows from present to
    infinity?
  • Perfect capital market
  • unlimited loans
  • unlimited savings
  • saving interest loan interest
  • gtfor all time preferences one can maximize net
    present value

6
  • present value
  • i interest
  • r 1i
  • Rt net income at year t

7
Rotation
  • Repeat the same cycle, starting from bare land
    with value L

8
Rotation/value growth
  • Fix regeneration and thinnings presnet value P
  • Value of final cutting V(t), G(t)V(t1)-V(t)

9
Stand level optimization
  • decision variables species, regeneration method,
    fertilization, timing, intensity and methods of
    thinning
  • optimization methods
  • direct search
  • random search
  • dynamic programming
  • nonlinear programming

10
decision tree
P periods each has t nt alternatives Nn1
.np timing of treatments beginning, middle or
end of period
11
Decision tree/J
  • can be used for
  • stand level optimization
  • to generate schedules for forest level analyses
  • generate a tree
  • node z at period t
  • function next() daughter node
  • function branch() sister node

12
Planning at forest level
  • needed, when
  • limited availability of labor or machines
  • Non perfect capital market
  • amount of timber has influence on price
  • can be used to analyze the space of alternative
    cutting profiles
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