Problem Chosen
E
2022
MCM/ICM
Summary Sheet
Team Control Number
2218144
Chasing Better Forest Management Strategies
Summary
“Gabon is one of the world’s leading producers of wood. It enforces selective logging:
not more than one tree every hectare.” This occurs in Yann Arthus-Bertrand’s 2009 film Home.
In reality, indiscriminate logging can increase soil erosion, reduce biodiversity, etc. But cutting
down trees and making them into woody forest products can be economically beneficial and can
absorb carbon dioxide. Therefore, it is necessary to make a reasonable forest management plan
to plan the number of trees to be cut and planted to achieve a stable and balanced forest.
First, we propose a Forest-Harvested Wood Products (HWP) Carbon Sequestration
(FHWP) model and measure the amount of carbon sequestered by forests and HWP. First, the
forest is divided into trees, understory plants, and woodlands, and their carbon conversion co-
efficients are calculated, and the forest carbon stock is solved by combining the forest area and
carbon density. Second, the carbon sequestration of HWP was divided into two parts, including
the carbon stock contained in wood and the amount of carbon entering the HWP pool in year
i. The HWP is divided into four types, such as round wood, charcoal, and wood panel, and the
carbon conversion factors of the four products are considered to predict the stock entering the
HWP in year i. Then, we add up the carbon sequestration of both to construct the FHWP model.
Finally, the model is applied to Russia and solved using an improved bat algorithm to derive the
carbon sequestration in Russian forests, e.g., 1.39 × 10
13
t of carbon sequestration in Russian
forests in 2020.
Second, we construct Carbon Sequestration-Economic Value-Ecological Protection (CEE)
model to make forest management optimal in three dimensions: carbon sequestration (CS), eco-
nomic value (EV), and environmental protection (EP). First, 12 indicators in the three dimensions
of CS, EV, and EP are selected, and the indicators are calculated using the current market price
and forest land revenue, and the data are normalized. Secondly, the entropy weight method is
applied to calculate the weight of each indicator. |C| indicates the overall level achieved by this
forest management plan under the three dimensions, and then CEE model is constructed. Finally,
the model is applied to China considering the 5-year transition period of the plan. Under the con-
dition of no deforestation, the transformation at 0.162% planting rate can reach the overall level
of 2020 in 2025, corresponding to a carbon sequestration of 3.0411 × 10
11
t.
Third, the model was applied to Sudanese forests to derive the best forest management plan
after 10 years of transition. First, Sudan’s forests from 2011-2020 was evaluated using CEE
model. Second, based on FHWP model, the current amount of carbon sequestered by forests and
their derivatives is calculated, and the amount of carbon sequestered after 100 years is predicted,
starting from 2020. Next, we optimized the management plan based on the best management
guideline-making the amount of carbon sequestered in 2030 as large as possible and scoring
the forest state higher. The optimized production ratio for Sudan was estimated with reference
to the production ratio of high level woody products in Australia. Finally, FHWP model is used
to find the maximum carbon sequestration in 2030 and its corresponding optimal forest manage-
ment plan, and conclusions are drawn. The amount of carbon sequestered by the existing forest
management plan after 100 years is: 4.1384 × 10
13
t The optimized best management plan has a
deforestation rate of 0.21% and a planting rate of 2.33%, which expands the carbon seques-
tration in 100 years by 42.09 times compared to the pre-optimized forest management plan.
Keywords: Forest Management; FHWP Model; CEE Model; Bat Algorithm
剩余24页未读，继续阅读
资源评论
