Suggestions and Comments are welcome April 2010 – DSFM2010, Lisbon, Portugal Suggestions and Comments are welcome

Apresentação em tema: "Suggestions and Comments are welcome April 2010 – DSFM2010, Lisbon, Portugal Suggestions and Comments are welcome"— Transcrição da apresentação:

1 Suggestions and Comments are welcome liliana.ferreira@ipleiria.pt April 2010 – DSFM2010, Lisbon, Portugal Suggestions and Comments are welcome liliana.ferreira@ipleiria.pt April 2010 – DSFM2010, Lisbon, Portugal Optimizing eucalypt stands management scheduling under the risk of fire Ferreira, L. 1, Constantino, M. 2, Borges, J. 3, Garcia-Gonzalo, J. 3 1 Instituto Politécnico de Leiria, Escola Superior de Tecnologia e Gestão, DMAT 2 Universidade de Lisboa, Faculdade de Ciências, DEIO 1 Instituto Politécnico de Leiria, Escola Superior de Tecnologia e Gestão, DMAT 2 Universidade de Lisboa, Faculdade de Ciências, DEIO 3 Universidade Técnica de Lisboa, Instituto Superior de Agronomia, DEF 3 Universidade Técnica de Lisboa, Instituto Superior de Agronomia, DEF Optimizing eucalypt stands management scheduling under the risk of fire Ferreira, L. 1, Constantino, M. 2, Borges, J. 3, Garcia-Gonzalo, J. 3 1 Instituto Politécnico de Leiria, Escola Superior de Tecnologia e Gestão, DMAT 2 Universidade de Lisboa, Faculdade de Ciências, DEIO 1 Instituto Politécnico de Leiria, Escola Superior de Tecnologia e Gestão, DMAT 2 Universidade de Lisboa, Faculdade de Ciências, DEIO 3 Universidade Técnica de Lisboa, Instituto Superior de Agronomia, DEF 3 Universidade Técnica de Lisboa, Instituto Superior de Agronomia, DEF Stochastic dynamic programming approach Figure 2 - DP network design for deterministic eucalypt stand management problem. Nodes above the horizontal axis represent the possible states for each stage; nodes below the horizontal axis correspond to the called "bare land nodes“- nodes associated to clear cuts or destruction fires. Introduction Research aim: Development of an optimization forest management scheduling model: at stand level; with a stochastic element - wildfire risk; for short rotation coppice systems; Eucalyptus globulus Labill stand (even aged stand); maximizes the soil expectation value; finds the optimal harvest age in each cycle; determines the optimal number of coppice cycles within a full rotation. Backward time approach iterative process; starts at the last stage; to start the process - necessary to use an estimate for the "bare land nodes" (rotations’ value to perpetuity). Model Building Fire risk Fire risk was incorporated into the model through wildfire and damage scenarios: J= J¹ ∪ J² J¹ J² scenarios involving wildfires with death of trees that force a clearcut of the stand scenario where a fire does not occur + scenarios involving the occurrence of wildfires without mortality Case Study Results Figure 1 - Characterization of the n th stage Prices: Timber stumpage price: 36€/m³; Salvage price: 27€/m³; Discount rate: 4%. Operational Costs: Table 1 - Source: CAOF's Database of ANEFA OperationFixed cost (€/ha)Variable Cost Shrub removal167 -- Plantation cost7250.14€×number of plants Sprout selection cost---0.15€×number of sprouts Conversion cost1204 0.14€×number of plants DecisionPossible values Harvest age Ψ n = {10, 11, …, 16} Sprouts selected Θ n = {1; 1.5; 2} Shrub cleaning Π n = {1, 2, 3} StageStates 1 T = {0} 2 T = {1, 2,..., 16} 3 T = {11, 12,..., 32} 4 T = {21, 22,..., 48} 5 T = {31, 32,..., 64} Table 2 - Possible values for management decisions Table 3 - Possible states for stochastic model Deterministic case NPL 1 st rotation2 nd rotation3 rd rotation4 th rotation SEV (€/ha) InIn MnMn VnVn InIn MnMn VnVn InIn MnMn VnVn InIn MnMn VnVn 1111151-1612 12 124390.12 1250151-1612 12 124584.98 1667141- 12161214125153.99 NPL = Number of planted trees SEV = Soil expectation value Stochastic case NPL 1 st rotation2 nd rotation3 rd rotation4 th rotation SEV (€/ha) InIn MnMn VnVn InIn MnMn VnVn InIn MnMn VnVn InIn MnMn VnVn 1111161- 12 12 122387.13 1250161- 12 12 122498.68 1667161- 12 12 122813.84 Stochastic case Rate (%) 1 st rotation2 nd rotation3 rd rotation4 th rotation SEV (€/ha) InIn MnMn VnVn InIn MnMn VnVn InIn MnMn VnVn InIn MnMn VnVn 2161- 12 12 127307.97 4161- 12 12 122387.13 6151-1612 12 12793.76 8131-1412 12161273.08 Stochastic case P1 €/m³ P2 €/m³ 1 st rotation2 nd rotation3 rd rotation4 th rotation SEV (€/ha) InIn MnMn VnVn InIn MnMn VnVn InIn MnMn VnVn InIn MnMn VnVn 28.821.6161- 12 12 121345.76 3627161- 12 12 122387.13 43.232.4161- 12 12 123428.49 P1 = timber stumpage price P2 = salvage price Table 4 - Results for deterministic case Table 5 - Results for stochastic dynamic programming model StageStates 1 st rotation10.7 2 nd rotation10.46 3 rd rotation10.86 4 th rotation11.12 Table 6 - Expected rotation length for SDP model, with NPL=1111 Table 7 - Sensitivity analysis for variations in discount rate, with NPL=1111 Table 8 - Sensitivity analysis for variations in prices (changes of 20%), with NPL=1111