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Forests
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Biomass Estimation and Carbon Stocks in Forest Ecosystems—Volume II
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Biomass Estimation and Carbon Stocks in Forest Ecosystems—Volume II

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

Deadline for manuscript submissions: 30 June 2024 | Viewed by 7904

Special Issue Editors

Dr. Andrzej Węgiel

E-Mail Website
Guest Editor
Department of Forest Management, Faculty of Forestry and Wood Technology, University of Life Sciences, Wojska Polskiego 28, 60-637 Poznań, Poland
Interests: forest management; biomass estimation; forest inventory; remote sensing; forest ecology
Special Issues, Collections and Topics in MDPI journals
Dr. Adrian Łukowski

E-Mail Website
Guest Editor
Faculty of Forestry and Wood Technology, University of Life Sciences, PL60-637 Poznań, Poland
Interests: plant–insect interactions; shrub species; silviculture; ecophysiology; forests and insects ecology; climate change and forestry; particulate matter pollution; game management; social dimensions of forest; invasive species and biological control
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Forest biomass and carbon are key elements in the development of climate change mitigation strategies. Due to the growing demand for renewable energy, there is also a growing interest in the wider use of forest biomass for energy as a possible substitute for fossil fuels. The use of woody biomass as an energy source can make a significant contribution to mitigating climate change. Forest biomass estimation is also important in the evaluation of carbon sequestration and the carbon balance capacity of forest ecosystems. Forests, being the most important carbon sink, are a good tool to reduce the carbon content of the atmosphere. Estimating the amount of carbon stored by forests is essential to support climate change mitigation and promote the transition to a low-carbon-emission economy.

This Special Issue aims to present updated knowledge relating to biomass estimation and carbon storage in forest ecosystems. The topics will include:

  • Advanced methods for forest biomass modelling, mapping, and estimation;
  • Linking field and remote sensing measurements;
  • Biomass components of forest ecosystems: tree compartments, vegetation, fungi, bacteria, soil fauna, etc.;
  • Modelling growth and biomass production;
  • Effects of forest management practices on biomass allocation;
  • Forest biomass utilization;
  • Factors influencing carbon and nutrient storage.

Dr. Andrzej Węgiel
Dr. Adrian Łukowski
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • biomass allocation
  • allometric equations
  • growth models
  • biomass expansion factors
  • remote sensing
  • bioenergy
  • carbon and nutrient storage
  • ecosystem biodiversity
  • soil productivity
  • forest management

Published Papers (7 papers)

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Research

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26 pages, 4823 KiB  
Article
Enhancing Urban Above-Ground Vegetation Carbon Density Mapping: An Integrated Approach Incorporating De-Shadowing, Spectral Unmixing, and Machine Learning
by Guangping Qie, Jianneng Ye, Guangxing Wang and Minzi Wang
Forests 2024, 15(3), 480; https://doi.org/10.3390/f15030480 - 04 Mar 2024
Viewed by 1005
Abstract
Accurately mapping urban above-ground vegetation carbon density presents challenges due to fragmented landscapes, mixed pixels, and shadows induced by buildings and mountains. To address these issues, a novel methodological framework is introduced, utilizing a linear spectral unmixing analysis (LSUA) for shadow removal and [...] Read more.
Accurately mapping urban above-ground vegetation carbon density presents challenges due to fragmented landscapes, mixed pixels, and shadows induced by buildings and mountains. To address these issues, a novel methodological framework is introduced, utilizing a linear spectral unmixing analysis (LSUA) for shadow removal and vegetation information extraction from mixed pixels. Parametric and nonparametric models, incorporating LSUA-derived vegetation fraction, are compared, including linear stepwise regression, logistic model-based stepwise regression, k-Nearest Neighbors, Decision Trees, and Random Forests. Applied in Shenzhen, China, the framework integrates Landsat 8, Pleiades 1A & 1B, DEM, and field measurements. Among the key findings, the shadow removal algorithm is effective in mountainous areas, while LSUA-enhanced models improve urban vegetation carbon density mapping, albeit with marginal gains. Integrating kNN and RF with LSUA reduces errors, and Decision Trees, especially when integrated with LSUA, outperform other models. This study underscores the potential of the proposed framework, particularly the integration of Decision Trees with LSUA, for advancing the accuracy of urban vegetation carbon density mapping. Full article
(This article belongs to the Special Issue Biomass Estimation and Carbon Stocks in Forest Ecosystems—Volume II)
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20 pages, 4338 KiB  
Article
The Role of Wood Density Variation and Biomass Allocation in Accurate Forest Carbon Stock Estimation of European Beech (Fagus sylvatica L.) Mountain Forests
by Stefan Petrea, Gheorghe Raul Radu, Cosmin Ion Braga, Alexandru Bogdan Cucu, Tibor Serban, Alexandru Zaharia, Dan Pepelea, Gruita Ienasoiu and Ion Catalin Petritan
Forests 2024, 15(3), 404; https://doi.org/10.3390/f15030404 - 20 Feb 2024
Cited by 1 | Viewed by 733
Abstract
The European beech (Fagus sylvatica L.) is one of the most common tree species in Romania, with importance both economically and environmentally. Accurate methods of biomass assessment at the tree compartment level (i.e., stump, stem, branches, and leaves) are necessary for carbon [...] Read more.
The European beech (Fagus sylvatica L.) is one of the most common tree species in Romania, with importance both economically and environmentally. Accurate methods of biomass assessment at the tree compartment level (i.e., stump, stem, branches, and leaves) are necessary for carbon stock estimation. Wood density (WD) is an important factor in determining biomass and, ultimately, the tree’s carbon content. The average tree density was found to be 578.6 kg/m3. For this study, WD was evaluated by the weighting method related to tree volume. Also, to investigate a practical approach to determining the weighted wood density (WWDst), models were run using density at the base of the tree (WDBase), density at breast height level using discs (WDDBH), the wood core density (WDic), and the diameter at breast height (DBH) as predictors. The biomass assessment was conducted using different model evaluations for WWDst as well as allometric equations using the destructive method. From the results, it was noted that using the WWDst, the total biomass was underestimated by −0.7% compared to the biomass measured in the field. For allometric equations that included DBH and tree height as independent variables, the explained variability was around 99.3% for total aboveground biomass (AGBtotal), while it was 97.9% for allometric function using just the DBH. Overall, the distribution of biomass across different compartments was as follows: 73.5% in stems, 23.8% in branches, 1.9% in stumps, and 1.3% in leaves. The study findings offer valuable insights into WD, biomass distribution among different components, and biomass allometric quantification in natural beech forest environments in mountainous areas. Full article
(This article belongs to the Special Issue Biomass Estimation and Carbon Stocks in Forest Ecosystems—Volume II)
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18 pages, 3072 KiB  
Article
Pedodiversity and Organic Matter Dynamics in the North Apennines (Italy): Relationships among Soil Types, Biodiversity, and Ecological Functionality
by Livia Vittori Antisari, Mauro De Feudis, William Trenti, Gloria Falsone, Federico Puliga, Alessandra Zambonelli, Giulia Tabanelli and Fausto Gardini
Forests 2024, 15(2), 353; https://doi.org/10.3390/f15020353 - 11 Feb 2024
Viewed by 725
Abstract
Pedodiversity is generally neglected in studies concerning soil organic carbon (SOC). Therefore, this investigation aimed to explore the effect of soil types on the following: (1) soil processes related to organic matter (OM) dynamics along the profile; and (2) the microbial community and [...] Read more.
Pedodiversity is generally neglected in studies concerning soil organic carbon (SOC). Therefore, this investigation aimed to explore the effect of soil types on the following: (1) soil processes related to organic matter (OM) dynamics along the profile; and (2) the microbial community and functionality within the uppermost horizon. Humic Dystrudepts (HD), Typic Dystrudepts (TD), and Humic Lithic Dystrudepts (HLD) were selected in beech forests of the Apennine ridge in the Emilia-Romagna Region (Italy). Soils were sampled by horizons until parent material, and physico-chemical and functional analyses were performed. The results showed that both HD and HLD soils had a higher SOC accumulation than TD, particularly within the deeper horizons. Such accumulation might be due to the lower turnover rate of soil OM forms, namely fulvic acid-like substances, humic acid-like substances, and non-extractable OM. Noteworthy, the A horizons showed slight differences in SOC among the soil types, suggesting similar SOC decomposition processes. This fact was confirmed by the lack of differences in microbial DNA-based diversity and functionality. This study highlighted the importance of combining pedodiversity and microbial diversity for a wider perspective on SOC dynamics. Full article
(This article belongs to the Special Issue Biomass Estimation and Carbon Stocks in Forest Ecosystems—Volume II)
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19 pages, 4368 KiB  
Article
Influence of Irrigation on Biomass Partitioning in Above- and Belowground Organs of Trees Planted in Desert Sites of Mongolia
by Ser-Oddamba Byambadorj, Byung Bae Park, Sarangua Lkhagvasuren, Enkhchimeg Tsedensodnom, Otgonsaikhan Byambasuren, Altankhundaga Khajid, Donato Chiatante and Batkhuu Nyam-Osor
Forests 2024, 15(1), 46; https://doi.org/10.3390/f15010046 - 25 Dec 2023
Viewed by 1143
Abstract
Planting trees is considered a crucial factor in mitigating the increase in carbon emissions in the atmosphere by generating plant biomass. In addition to advancing our understanding of how tree biomass is allocated in desert environments, we explore potential variations in biomass partitioning [...] Read more.
Planting trees is considered a crucial factor in mitigating the increase in carbon emissions in the atmosphere by generating plant biomass. In addition to advancing our understanding of how tree biomass is allocated in desert environments, we explore potential variations in biomass partitioning based on the irrigation regimes (4, 8, and 12 L h−1) supporting the growth of these trees. Specifically, this study compares the pattern of biomass distribution between above-ground and belowground organs of 11-year-old trees (U. pumila, E. moorcroftii, and T. ramosissima) planted in a desert site in Mongolia. An interesting result of this study is the demonstration that biomass partitioning among roots of different diameter classes differs between the tree species tested, suggesting that each tree species establishes its own type of root/soil interaction. The differences in biomass partitioning in roots could determine specificity in the strength of anchorage and efficiency of nutrition for the trees. We also demonstrate that the presence of plantations influences certain chemical properties of the desert soil, with differences depending on the tree species planted. In addition to presenting a method for planting trees in desert sites, this study underscores that a reliable evaluation of atmospheric carbon sequestration in trees must necessarily include root excavation to obtain an accurate measurement of biomass stored in belowground structures. Assessing the overall biomass produced by these trees allows us to determine the potential for carbon sequestration achievable through plantations established in desert sites. Full article
(This article belongs to the Special Issue Biomass Estimation and Carbon Stocks in Forest Ecosystems—Volume II)
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20 pages, 15127 KiB  
Article
Estimation of Above-Ground Biomass for Pinus densata Using Multi-Source Time Series in Shangri-La Considering Seasonal Effects
by Chaoqing Chen, Yunrun He, Jialong Zhang, Dongfan Xu, Dongyang Han, Yi Liao, Libin Luo, Chenkai Teng and Tangyan Yin
Forests 2023, 14(9), 1747; https://doi.org/10.3390/f14091747 - 29 Aug 2023
Cited by 1 | Viewed by 1142
Abstract
Forest above-ground biomass (AGB) is the basis of terrestrial carbon storage estimation, and making full use of the seasonal characteristics of remote sensing imagery can improve the estimation accuracy. In this study, we used multi-source time series and sample plots with the Random [...] Read more.
Forest above-ground biomass (AGB) is the basis of terrestrial carbon storage estimation, and making full use of the seasonal characteristics of remote sensing imagery can improve the estimation accuracy. In this study, we used multi-source time series and sample plots with the Random Forest (RF) model to estimate the AGB. The sources included Sentinel-1 (S-1), Sentinel-2 (S-2), and the S-1 and S-2 combination (S-1S-2). Time series included single season, annual, and multi-season. This study aims to (1) explore the optimal image acquisition season to estimate AGB; (2) determine whether the ability to estimate the AGB of multi-seasonal imagery exceeded that of annual and single-season imagery; (3) discover the sensitivity of different data to AGB according to phenological conditions. The results showed that: (1) images acquired in autumn were more useful for AGB estimation than spring, summer, and winter; (2) the S-1 multi-seasonal AGB model had higher accuracy than the annual or single-season one; (3) in autumn and spring, S-1 had higher estimation accuracy than S-2, and in autumn and spring, estimation accuracy from S-1S-2 was higher than that from S-1 and S-2; (4) in 16 AGB estimation models, the best estimation accuracy was achieved by the autumn AGB model from S-1S-2 (R2 = 0.90, RMSE = 16.26 t/ha, p = 0.82, and rRMSE = 18.97). This study could be useful to identify the optimal image acquisition season for AGB estimation, thus reducing the economic cost of image acquisition and improving the estimation accuracy. Full article
(This article belongs to the Special Issue Biomass Estimation and Carbon Stocks in Forest Ecosystems—Volume II)
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19 pages, 2618 KiB  
Article
Estimation of Biomass and Carbon Sequestration Potential of Dalbergia latifolia Roxb. and Melia composita Willd. Plantations in the Tarai Region (India)
by Neha Chopra, Lalit Mohan Tewari, Ashish Tewari, Zishan Ahmad Wani, Mohd Asgher, Shreekar Pant, Sazada Siddiqui and Ayesha Siddiqua
Forests 2023, 14(3), 646; https://doi.org/10.3390/f14030646 - 21 Mar 2023
Viewed by 1718
Abstract
This study was carried out in the Tarai region of Uttarakhand, India to estimate the carbon stock and sequestration potential of Dalbergia latifolia and Melia composita plantations of different ages (4 and 6 years old). A total of 14 regression equations using one [...] Read more.
This study was carried out in the Tarai region of Uttarakhand, India to estimate the carbon stock and sequestration potential of Dalbergia latifolia and Melia composita plantations of different ages (4 and 6 years old). A total of 14 regression equations using one variable, dbh (diameter at breast height), were primarily selected for both of the tree species component-wise. Tree density was 880 and 960 individuals ha−1 in D. latifolia and M. composita monoplantations, respectively. These equations were statistically significant (p < 0.01, p < 0.05) at 95% confidence interval. The total biomass of trees, shrubs, and herbs at the different-aged plantations varied from 68.86 to 145.14 Mg ha−1, 1.29 to 2.41 Mg ha−1, and 1.14 to 3.68 Mg ha−1, respectively. Among the studied plantations, the maximum total biomass of 145.14 Mg ha−1 was recorded at the M. composita plantation (7 years old), resulting in the maximum carbon stock of 68.94 Mg C ha−1. Total NPP ranged from 5.6 Mg ha−1yr−1 to 16.01 Mg ha−1yr−1 for both plantations of different ages. The carbon sequestration in the M. composita 7-year-old plantation was 7.6 Mg Cha−1yr−1. Quantified carbon sequestration among different tree components must be considered for tree-level inventories for carbon trading schemes when determining the long-term carbon pools under the Paris agreement. Full article
(This article belongs to the Special Issue Biomass Estimation and Carbon Stocks in Forest Ecosystems—Volume II)
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Review

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15 pages, 3967 KiB  
Review
Evaluating the Research Status of the Remote Sensing-Mediated Monitoring of Forest Biomass: A Bibliometric Analysis of WOS
by Yonglei Shi, Zhihui Wang, Guojun Zhang, Xiaoyan Wei, Wentao Ma and Haoran Yu
Forests 2024, 15(3), 524; https://doi.org/10.3390/f15030524 - 12 Mar 2024
Viewed by 704
Abstract
Forests serve as the largest carbon reservoir in terrestrial ecosystems, playing a crucial role in mitigating global warming and achieving the goal of “carbon neutrality”. Forest biomass is intrinsically related to carbon sinks and sources in forest ecosystems, and thus, the accurate monitoring [...] Read more.
Forests serve as the largest carbon reservoir in terrestrial ecosystems, playing a crucial role in mitigating global warming and achieving the goal of “carbon neutrality”. Forest biomass is intrinsically related to carbon sinks and sources in forest ecosystems, and thus, the accurate monitoring of forest biomass is of great significance in ensuring ecological security and maintaining the global carbon balance. Significantly, remote sensing is not only able to estimate forest biomass at a large spatial scale but does so quickly, accurately, and without loss. Moreover, it can obtain forest biomass in areas inaccessible to human beings, which have become the main data source for forest biomass estimation at present. For this reason, this study analyzes the current research status, research hotspots, and future research trends in the field of remote sensing monitoring of forest biomass based on 1678 forest biomass remote sensing monitoring results from 1985 to 2023 obtained from the Web of Science Core Collection database. The results showed that the following: (1) The number of publications showed an exponential upward trend from 1985 to 2023, with an average annual growth rate of 2.64%. The top ten journals contributed to 53.76% of the total number of publications and 52.89% of the total number of citations in the field. (2) In particular, Remote Sensing of Environment has maintained a leading position in the field for an extended period, boasting the highest impact factor. Additionally, the author Saatchi S. stands out with the highest total number of citations for articles. (3) Keyword clustering analysis revealed that the main research topics in the remote sensing monitoring of forest biomass can be categorized into the following: optical remote sensing, LiDAR remote sensing, SAR remote sensing, and carbon stock. The explosion of keywords in the last six years indicates that an increasing number of researchers are focusing on carbon, airborne LiDAR data, biomass mapping, and constructing optimal biomass models. Full article
(This article belongs to the Special Issue Biomass Estimation and Carbon Stocks in Forest Ecosystems—Volume II)
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