Impacts of Forest Management Practices on Carbon Sequestration and Greenhouse Gas Exchange

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Meteorology and Climate Change".

Deadline for manuscript submissions: closed (25 January 2024) | Viewed by 9036

Special Issue Editors


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Guest Editor
College of Environment and Resource Sciences, Zhejiang A&F University, Hangzhou 311300, China
Interests: soil respiration; carbon sequestration; forestry informatization; greenhouse gas exchange

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Guest Editor
School of Mathematical Sciences, Nanjing Normal University, Nanjing 210046, China
Interests: data assimilation; mathematical modeling; numerical computation; remote sensing; machine learning
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Guest Editor
Institute of Forestry and Conservation, University of Toronto, 33 Willcocks St., Toronto, ON M5S 3B3, Canada
Interests: biochar; forestry ecology; methane; carbon; physiological ecology; global change; silviculture
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Forest vegetation and soil are significant carbon sinks at the global scale, and they play important roles in sequestering greenhouse gases (GHGs) and regulating climate. The structure and function of forest ecosystems are strongly impacted by forest management practices, but they have historically been designed to maximize the yield of timber products. Forest management can potentially increase the carbon storage and GHG uptake of forest ecosystems, but such efforts must be based on a fundamental scientific understanding of the processes and wholistic assessments of GHG sources and sinks. To what extent can forest management practices enhance sinks for CO2 and other GHGs? Which practices are best suited for specific forests to maximize carbon sink capacity? These questions remain unresolved, and further research is required to develop forest management practices for benefiting climate change mitigation. Forest management practices addressed in this Special Issue include but are not limited to the designation of reserve areas to enhance carbon sequestration, close-to-nature forest management, skid trail and harvest planning, increased rotation lengths, forest stand conversion, and multi-objective optimization that includes climate mitigation.

This issue welcomes empirical studies and reviews of regional forest management practices in, but not limited to, the following fields:

  • Carbon sequestration and climate change adaptation;
  • Carbon cycling;
  • Soil greenhouse gas flux;
  • Soil organic matter dynamics;
  • Life-cycle analyses of net carbon dynamics.

Prof. Dr. Yixiang Wang
Prof. Dr. Zhibin Sun
Prof. Dr. Sean Thomas
Guest Editors

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Keywords

  • carbon stock and sequestration
  • climate change
  • forest management
  • carbon cycling
  • forest soil

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Published Papers (5 papers)

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Research

17 pages, 1106 KiB  
Article
Economic Profitability of Carbon Sequestration of Fine-Aroma Cacao Agroforestry Systems in Amazonas, Peru
by Malluri Goñas, Nilton B. Rojas-Briceño, Darwin Gómez Fernández, Daniel Iliquín Trigoso, Nilton Atalaya Marin, Verónica Cajas Bravo, Jorge R. Díaz-Valderrama, Jorge L. Maicelo-Quintana and Manuel Oliva-Cruz
Forests 2024, 15(3), 500; https://doi.org/10.3390/f15030500 - 8 Mar 2024
Viewed by 2246
Abstract
Currently, the economic profitability of cocoa is being affected by the increasing incidence of pests, low selling prices, high production costs, and the presence of cadmium in cocoa farms, posing a potential risk of crop abandonment. Therefore, the objective of the present research [...] Read more.
Currently, the economic profitability of cocoa is being affected by the increasing incidence of pests, low selling prices, high production costs, and the presence of cadmium in cocoa farms, posing a potential risk of crop abandonment. Therefore, the objective of the present research was to evaluate the economic profitability of carbon sequestration of fine-aroma cacao agroforestry systems in Amazonas, Peru, using the economic indicators of NPV, EIRR, and the benefit–cost ratio. For this purpose, 53 small cocoa producers of the APROCAM cooperative were involved, from which data were obtained on the general characteristics of the production system, production and maintenance costs, indirect costs, and administrative costs; in addition, the costs of implementation and maintenance of an environmental services project were calculated to finally make a cash flow projected over 5 years. As part of the results, the economic analysis was carried out on 104.25 hectares of cocoa belonging to the total number of farmers evaluated, who reported an average yield of 957.32 kg of dry cocoa per he. In addition, it was found that the production cost is PEN 3.91/kg of dry cocoa, and the average selling price is PEN 7.38/kg of dry cocoa. After the economic analysis, it was found that the implementation of an environmental services project is profitable (NPV = PEN 1,454,547.8; EIRR = 44% and B/C = 1.86). These results open up an opportunity for cocoa farmers to diversify and increase their income by contributing to climate change mitigation. Full article
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17 pages, 6677 KiB  
Article
Effects of Different Management Measures on Carbon Stocks and Soil Carbon Stocks in Moso Bamboo Forests: Meta-Analysis and Control Experiment
by Ziliang Zhao, Chunling Tao, Xu Liu, Xuekun Cheng, Chi Zhou, Siyao Huang, Menghan Shou, Qihan Zhang, Banghui Huang, Chong Li, Guoqing Tu and Yufeng Zhou
Forests 2024, 15(3), 496; https://doi.org/10.3390/f15030496 - 7 Mar 2024
Viewed by 1443
Abstract
As a crucial forest resource in southern China and a significant economic forest species for forestry production, moso bamboo has a notable influence on carbon stocks across the entire bamboo forest ecosystem. Studying the impact of different management measures on carbon stocks in [...] Read more.
As a crucial forest resource in southern China and a significant economic forest species for forestry production, moso bamboo has a notable influence on carbon stocks across the entire bamboo forest ecosystem. Studying the impact of different management measures on carbon stocks in moso bamboo forests and soil carbon stocks can assist bamboo forest operators in incorporating the carbon sequestration capacity of bamboo into forest production and management decisions, which can contribute to achieving carbon sequestration, emission reduction, and sustainable development in the decision-making processes of forest production and management. In this study, we utilized a randomized block design to investigate the changes in moso bamboo forests’ carbon stocks and soil carbon stocks under different management measures across three intensities: high-intensity intensive management (HT), moderate-intensity intensive management (MT), and regular management (CK). Additionally, we employed meta-analysis methods to enhance the accuracy of our conclusions. The experimental results showed that MT increased the carbon storage in moso bamboo forests by 19.86%, which was significantly different from CK (p < 0.05), while there was no significant difference between the HT group and the MT and CK groups. For soil carbon stocks, in the 10–30 m and 0–50 m soil layers, HT decreased soil carbon storage by 29.89% and 22.38%, while MT increased soil carbon storage by 64.15% and 31.02%, respectively. Both HT and MT were significantly different from CK (p < 0.05). However, for the soil layers of 0–10 m and 30–50 m, there was no significant difference between the treatments within the experimental group. The results of the meta-analysis indicate that, compared to traditional regular management, intensive management, especially high-intensity intensive management, can significantly increase the carbon storage in bamboo forests (p < 0.05). However, it will significantly reduce soil carbon storage (p < 0.05). Moreover, a significant difference in soil carbon storage is observed only within the 0–20 cm soil layer group. Therefore, from the perspective of the long-term ecological benefits of bamboo forest management, the selection of management measures should prioritize reasonable and moderate-intensity intensive management. Additionally, adopting appropriate and moderate-intensity fertilization, ploughing, and other management methods is recommended to enhance the productivity of moso bamboo forests while concurrently protecting the natural environment and improving the carbon sequestration capacity of moso bamboo forests. Full article
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23 pages, 20392 KiB  
Article
Combining Multisource Data and Machine Learning Approaches for Multiscale Estimation of Forest Biomass
by Yifeng Hong, Jiaming Xu, Chunyan Wu, Yong Pang, Shougong Zhang, Dongsheng Chen and Bo Yang
Forests 2023, 14(11), 2248; https://doi.org/10.3390/f14112248 - 15 Nov 2023
Cited by 3 | Viewed by 1737
Abstract
Forest biomass is an important indicator of forest ecosystem productivity, and it plays vital roles in the global carbon cycling, global climate change mitigating, and ecosystem researches. Multiscale, rapid, and accurate extraction of forest biomass information is always a research topic. In this [...] Read more.
Forest biomass is an important indicator of forest ecosystem productivity, and it plays vital roles in the global carbon cycling, global climate change mitigating, and ecosystem researches. Multiscale, rapid, and accurate extraction of forest biomass information is always a research topic. In this study, comprehensive investigation of a larch (Larix olgensis) plantation was performed using remote sensing and field-based monitoring methods, in combination with LiDAR-based multisource data and machine learning methods. On this basis, a universal, multiscale (single tree, stand, management unit, and region), and unit-high-precision continuous monitoring method was proposed for forest biomass components. The results revealed the following. (1) Airborne LiDAR point cloud variables exhibited significant correlation with the aboveground components (except leaves) and the whole-plant biomass (Radj2 > 0.91), suitable for extraction or estimation of forest parameters such as biomass and stock volume. (2) In terms of biomass monitoring at forest stand and management unit scale, a random forest model performed well in fitting accuracy and generalization ability, whereas a multiple linear regression model produced clearer explanation regarding the biomass of each forest component. (3) Using seasonal phenological characteristics in the study area, larch distribution information was extracted effectively. The overall accuracy reached 90.0%, and the kappa coefficient reached 0.88. (4) A regional-scale forest biomass component estimation model was constructed using a long short-term memory model, which effectively reduced the probability of biomass underestimation while ensuring good estimation accuracy, with R2 exceeding 0.6 for the biomass of the aboveground and whole-plant components. This research provides theoretical support for rapid and accurate acquisition of large-scale forest biomass information. Full article
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22 pages, 28529 KiB  
Article
Optimizing Carbon Sequestration in Forest Management Plans Using Advanced Algorithms: A Case Study of Greater Khingan Mountains
by Weitian Zhang, Hanqin Shao, Haitao Sun, Wei Zhang and Qinglun Yan
Forests 2023, 14(9), 1785; https://doi.org/10.3390/f14091785 - 1 Sep 2023
Cited by 3 | Viewed by 1673
Abstract
The Paris Agreement aims to combat climate change by reducing greenhouse gas emissions, with bioenergy identified as a potential solution. However, concerns remain about its impact on carbon stocks and the optimal timing for implementation. To address these challenges, we propose a comprehensive [...] Read more.
The Paris Agreement aims to combat climate change by reducing greenhouse gas emissions, with bioenergy identified as a potential solution. However, concerns remain about its impact on carbon stocks and the optimal timing for implementation. To address these challenges, we propose a comprehensive multi-objective optimization model for forest management that maximizes carbon sequestration and economic benefits. Our model integrates three key components: (1) a sophisticated carbon-sequestration model encompassing living plants, wood forest products, and soil and microbial carbon uptake, (2) dynamic factors such as forest fires and extreme weather events, and (3) an economic benefits model focused on wood-processing products. We optimized the forest-management strategy over ten years by leveraging the simulated annealing and Karush–Kuhn–Tucker (KKT) algorithms. Through simulations using data from China’s Greater Khingan Mountains region, we explored the optimal logging plans for maximizing carbon sequestration without external factors. Our results revealed that the optimized logging plans significantly enhance carbon sequestration compared to proportionally averaged logging plans. Next, we investigated the impact of external factors on forest management, specifically wildfires and extreme weather events. Our findings demonstrate that wildfires have a more-substantial detrimental effect on the absolute value of carbon sequestration and the extent of improvement achieved through model optimization. At the same time, extreme cold primarily affects the growth rate of carbon sequestration. We employed a linear-weighting approach and the Analytic Hierarchy Process (AHP) to address the trade-offs between carbon sequestration and economic benefits to transform the multi-objective optimization function into a single objective. The results showed that the optimized harvesting schedule can lead to improved economic benefits compared to uniformly harvesting trees. Moreover, the joint optimization approach enabled us to identify optimal solutions that balance carbon sequestration and economic benefits, offering sustainable forest management strategies. Our study provides valuable quantitative insights into forest management strategies that balance carbon sequestration and economic benefits, making it highly relevant for real-world applications. Full article
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18 pages, 2754 KiB  
Article
CH4 and N2O Emissions of Undrained and Drained Nutrient-Rich Organic Forest Soil
by Aldis Butlers, Andis Lazdiņš, Santa Kalēja, Dana Purviņa, Gints Spalva, Guntis Saule and Arta Bārdule
Forests 2023, 14(7), 1390; https://doi.org/10.3390/f14071390 - 7 Jul 2023
Cited by 8 | Viewed by 1372
Abstract
The ability to accurately assess the impact of organic soil drainage on greenhouse gas emissions (GHG) is still limited. Methane (CH4) emissions are characterized by significant variations, and GHG emissions from nutrient-rich organic soil in the region have not been extensively [...] Read more.
The ability to accurately assess the impact of organic soil drainage on greenhouse gas emissions (GHG) is still limited. Methane (CH4) emissions are characterized by significant variations, and GHG emissions from nutrient-rich organic soil in the region have not been extensively studied. The aim of this study was to assess CH4 and nitrous oxide (N2O) emissions from nutrient-rich organic soil in hemiboreal forests to provide insights into their role in regional GHG balance. Over the course of one year, CH4 and N2O emissions, as well as their affecting factors, were monitored in 31 forest compartments in Latvia in both drained and undrained nutrient-rich organic soils. The sites were selected to include forests of different ages, dominated by silver birch (Betula pendula Roth), Norway spruce (Picea abies (L.) Karsten), and black alder (Alnus glutinosai (L.) Gärtner), as well as clearcuts. Soil GHG emissions were estimated by collecting gas samples using the closed manual chamber method and analyzing these samples with a gas chromatograph. In addition, soil temperature and groundwater level (GW) measurements were conducted during gas sample collection. The mean annual CH4 emissions from drained and undrained soil were −4.6 ± 1.3 and 134.1 ± 134.7 kg CH4 ha−1 year−1, respectively. N2O emissions from undrained soil (4.1 ± 1.4 kg N2O ha−1 year−1) were significantly higher compared to those from drained soil (1.7 ± 0.6 kg N2O ha−1 year−1). In most of the study sites, undrained soil acted as a CH4 sink, with the soil estimated as a mean source of CH4, which was determined by one site where an emission hotspot was evident. The undrained soil acted as a CH4 sink due to the characteristics of GW level fluctuations, during which the vegetation season GW level was below 20 cm. Full article
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