Multi-objective optimization of forest ecosystem services under uncertainty

Nabhani, Abbas; Mardaneh, Elham; Sjølie, Hanne K.

doi:10.1016/j.ecolmodel.2024.110777

Ecological Modelling

2024

DOI: 10.1016/j.ecolmodel.2024.110777

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Multi-objective optimization of forest ecosystem services under uncertainty

Abbas Nabhani,

Elham Mardaneh,

Hanne K. Sjølie

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2024

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Cited by 2 publications

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Optimizing Forest Management: Balancing Environmental and Economic Goals Using Game Theory and Multi-Objective Approaches

Amiri,

Mohammadi Limaei

2024

Forests

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Forests are complex ecosystems that require integrated management to balance economic, social, and environmental dimensions. Conflicting objectives among stakeholders make optimal decision-making particularly challenging. This study seeks to balance the economic gains of forest harvesting with the goals of environmental conservation, with a focus on the Shafarood forest in Northern Iran. We applied multi-objective optimization and game theory to maximize the net present value (NPV) of forest harvesting while enhancing carbon sequestration. The research utilized data on stumpage prices, harvesting costs, tree density, volume per ha, growth rates, interest rates, carbon sequestration, and labour costs. Applying the epsilon-constraint method, we derived Pareto optimal solutions for a bi-objective model, and game theory was applied to negotiate between economic and environmental stakeholders. In the fifth round of bargaining, a Nash equilibrium was achieved between the two players. At this equilibrium point, the economic player achieved NPV from forest harvesting of 9001.884 (IRR 10,000/ha) and amount of carbon sequestration of 159.9383 tons/ha. Meanwhile, the environmental player achieved NPV from forest harvesting of 7861.248 (IRR 10,000/ha), along with a carbon sequestration of 159.9731 tons/ha. Results indicate significant trade-offs but reveal potential gains for both economic and environmental goals. These findings provide a robust framework for sustainable forest management and offer practical tools to support informed decision-making for diverse stakeholders.

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Optimizing Forest Management: Balancing Environmental and Economic Goals Using Game Theory and Multi-Objective Approaches

Amiri,

Mohammadi Limaei

2024

Forests

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Value Assessment and Prediction of Regulating Ecosystem Services in Hainan Tropical Rainforest National Park, China

Du,

Liu,

Liu

et al. 2024

Sustainability

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Ecosystem services serve as a bridge between the ecological environment and human society. The quantitative analysis and forecasting of ecosystem services can provide references for regional eco-environmental assessments and land-use planning for the future. In this study, taking Hainan Tropical Rainforest National Park (HTRNP) as an example, the value of regulating ecosystem services (RESs) in 2020 was assessed via ArcGIS 10.1 and the InVEST 3.5 model, and the per-unit value of RESs was calculated for different LULC types. In addition, in accordance with the Overall Planning for HTRNP and the objective of optimizing RESs, the value of RESs in short-term (to 2030) and long-term (to 2050) scenarios was forecast via a linear programming model. The results are as follows: (1) The RES value of HTRNP in 2020 was CNY 2090.67 × 108, with climate regulation accounting for the largest proportion; the spatial distribution of RESs in the eastern and central areas was higher than that in the western area, but different indicators of RESs differed in their spatial patterns in varied geographic units. (2) The natural forest ecosystem in HTRNP accounts for 76.94% of the total area but 84.82% of the total value of RESs. The per-unit value is ranked from highest to lowest as follows: montane rainforests > wetlands > lowland rainforests > lowland secondary rainforests > tropical coniferous forests > deciduous monsoon rainforests > tropical cloud forests > shrub forests > timber forests > economic forests > rubber forests > grasslands > farmlands > settlements. (3) In the short-term scenario, the value of RESs is CNY 2216.64 × 108, an increase of CNY 118.97 × 108 compared to 2020, with an increase rate of 5.67%. In the long-term scenario, the value of RESs is CNY 2472.48 × 108, an increase of CNY 374.81 × 108 compared to 2020, with an increase rate of 17.87%. The results reveal the significance of ecosystem services in the national park and can inform more targeted and scientifically sound decision-making in the future.

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Multi-objective optimization of forest ecosystem services under uncertainty

Cited by 2 publications

References 99 publications

Optimizing Forest Management: Balancing Environmental and Economic Goals Using Game Theory and Multi-Objective Approaches

Optimizing Forest Management: Balancing Environmental and Economic Goals Using Game Theory and Multi-Objective Approaches

Value Assessment and Prediction of Regulating Ecosystem Services in Hainan Tropical Rainforest National Park, China

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