How Strategic Forest Harvesting Boosts Carbon Capture: Insights from the 2022 MCM Award Paper

Interpretation of the 2022 MCM E‑Problem O‑Award Paper

Problem

Background

Climate change threatens life, and reducing atmospheric greenhouse gases requires both emission cuts and increased carbon sequestration. Forests store carbon in living trees, wood products, soil, and water, making them essential for mitigation. Proper forest management, including selective harvesting, can enhance carbon storage while providing economic and social benefits.

Requirements

Build a carbon‑sequestration model to determine how much CO₂ forests and their products can store over time and identify the most effective management plan for carbon capture.

Develop a decision model that balances carbon sequestration with other forest values (biodiversity, recreation, cultural factors) and answer questions such as the range of possible plans, conditions where no harvesting occurs, transition points between plans, and how site characteristics affect these transitions.

Apply the model to specific forests, determine which forests should include harvesting, estimate CO₂ absorption over 100 years, and recommend the best management plan with justification.

Discuss a strategy to shift from current harvesting intervals to a longer interval that adds ten years, considering stakeholder needs.

Write a non‑technical newspaper article persuading the local community that selective harvesting is the optimal choice.

2202171

Paper framework

Carbon neutrality is achieved by reducing emissions and increasing carbon storage. This study builds a forest‑system carbon‑storage prediction model and a forest‑value balance decision model, showing that moderate harvesting can improve overall carbon sequestration.

Task 1 finds that forest carbon storage follows a logistic growth pattern, allowing calculation of the optimal harvesting intensity and age for maximum carbon capture.

2202666

Paper framework

The paper develops two models: a forest carbon‑storage model and a forest‑value evaluation model. The carbon model calculates total sequestration from live trees and wood products using area, species‑specific sequestration rates, and harvest rates. The value model creates a three‑dimensional ESE evaluation system, applies AHP and K‑means clustering, and uses a GE matrix to rank management plans.

Case studies on Beijing forests show an optimal harvest rate of 0.06 % with a 30‑year rotation, achieving substantial carbon storage while meeting social demands.

2202838

Paper framework

The study builds a carbon‑sequestration model for forests and wood products, combines it with a dynamic goal‑programming management model, and integrates a three‑level social‑value assessment using entropy weighting and the GE matrix. Application to the Daxing’anling region yields a 100‑year total sequestration of 42.64 billion tons, with optimal harvesting intervals extended by ten years.

2203489

Paper framework

Active forest and wood products are modeled separately. A logistic biomass growth model provides the time function for live forest carbon, while linear programming estimates carbon storage of forest products. Decision variables include ecological and economic benefits, solved via hierarchical analysis and a Gini‑based optimization index.

2209336

The paper introduces an Efficiency‑Estimation‑Evaluation‑Management (EEEM) model comprising three sub‑models to assess carbon storage and overall forest value. Using AHP, EWM, and a BP neural network, the model predicts long‑term scores and suggests optimal management plans, illustrated with the Bahema National Park case.

2216618

A comprehensive index (CIF) combining carbon storage (CSI), economic value (EI), and biodiversity impact (BDI) is created. Multi‑objective planning and a floating‑man model are employed to determine optimal harvest timing across forests in developed and developing countries, highlighting differing priorities.

2218144

A Forest‑Harvested Wood Product (FHWP) carbon‑sequestration model and a Carbon‑Economic‑Ecological (CEE) model are built. Applied to Russia, China, and Sudan, the models show that selective harvesting combined with re‑planting can dramatically increase 100‑year carbon storage while maintaining economic and ecological benefits.

2223269

Using multi‑objective programming, the study balances carbon sequestration, water‑soil conservation, and harvest economics. A case study of Jin‑dong forest in China predicts a 100‑year carbon stock of several teragrams and proposes a five‑stage management plan that includes sustainable harvesting.

2223495

Differential equations, multi‑objective planning, evolutionary game theory, and simulation are employed to find optimal forest management strategies under various climate scenarios. Results confirm that moderate harvesting improves overall system carbon storage and economic value, while extended rotation periods aid forest recovery.

Overall, the research demonstrates that well‑designed, moderate forest harvesting can enhance carbon sequestration, support economic use of forest products, and satisfy ecological and social objectives.