Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.4
2.9
Journals
Forests
Special Issues
Advances in Monitoring and Assessment of Forest Carbon Storage
share announcement

Advances in Monitoring and Assessment of Forest Carbon Storage

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Inventory, Modeling and Remote Sensing".

Deadline for manuscript submissions: closed (20 March 2023) | Viewed by 19412

Special Issue Editors

Prof. Dr. Tianxiang Yue

E-Mail Website
Guest Editor
Institute of Geographic Science and Natural Resources Research, University of Chinese Academy of Sciences, Beijing 100101, China
Interests: spatial analysis; land cover; digital terrain modeling; ecological and environmental models; system simulation
Special Issues, Collections and Topics in MDPI journals
Dr. Yifu Wang

E-Mail Website
Guest Editor
The College of Forestry, Beijing Forestry University, Beijing 100083, China
Interests: forest carbon stock simulation; forest monitoring and management

Special Issue Information

Dear Colleagues,

Forests play an important role in the active mitigation of atmospheric CO2 through increased carbon stocks. Competition, site condition, climate, and forest management affect the accumulation rate of forest carbon stock by affecting the structure and function of the forest ecosystems. The approaches combining field data with remote sensing data and process-based models are effective to estimate forest biomass carbon stock, but there are still uncertainties.

This Special Issue is seeking contributions to simulation of forest growth and carbon sink potential of forest vegetation and soil based on field data, remote sensing data, and process-based models. It provides an opportunity for researchers to present the results of studies on (a) the impacts of competition, site condition, climate and forest management on forests growth and carbon sequestration; (b) novel data acquisition, optimization, and management techniques and methods for forest growth and carbon sink monitoring; and (c) integration of field data, ground sensor networks, and remote sensing datasets for forest monitoring.

It aims to provide an up-to-date compendium of recent research in this field from around the world.

Prof. Dr. Tianxiang Yue
Dr. Yifu Wang
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

  • forest biomass carbon
  • forest growth
  • site conditions
  • allometric growth equation

Published Papers (10 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Editorial

Jump to: Research, Review

2 pages, 622 KiB  
Editorial
Make Forests Better Play Their Role in Mitigating Climate Change
by Yifu Wang and Tianxiang Yue
Forests 2022, 13(2), 249; https://doi.org/10.3390/f13020249 - 6 Feb 2022
Cited by 1 | Viewed by 1157
Abstract
Climate change caused by industrial carbon emissions and land use/land cover changes is a widely concerning issue around the world and is closely related to the global carbon cycle [...] Full article
(This article belongs to the Special Issue Advances in Monitoring and Assessment of Forest Carbon Storage)

Research

Jump to: Editorial, Review

24 pages, 6759 KiB  
Article
Spatial–Temporal Changes and Prediction of Carbon Storage in the Tibetan Plateau Based on PLUS-InVEST Model
by Huihui Zhao, Bing Guo and Guojun Wang
Forests 2023, 14(7), 1352; https://doi.org/10.3390/f14071352 - 30 Jun 2023
Cited by 4 | Viewed by 1297
Abstract
The changes in the recent and future spatial–temporal patterns of carbon storage of the Tibetan Plateau and its dominant factors in different periods were unclear, and were conducive to optimizing the spatial layout of land. Exploring the spatial and temporal changes in terrestrial [...] Read more.
The changes in the recent and future spatial–temporal patterns of carbon storage of the Tibetan Plateau and its dominant factors in different periods were unclear, and were conducive to optimizing the spatial layout of land. Exploring the spatial and temporal changes in terrestrial ecosystem carbon storage and their influencing factors during a long study period had important theoretical and practical significance for achieving the goal of carbon neutrality. In this study, the Integrated Valuation of Ecosystem Services and Trade-offs model (InVEST) was used to analyze the changes in carbon storage based on vegetation-type data during 2000–2020. The Path-generating Land-Use Simulation model (PLUS) was then used to predict the spatial distribution of carbon storage in the Tibetan Plateau in 2030 and 2060 under inertial development, farmland protection and ecology priority scenarios. The results showed that: (1) The degradation of vegetation types reduced the carbon storage during the study period. During 2000–2020, the desert shrub and non-vegetation area expanded by 63.21% and 13.35%, respectively, while the deciduous scrub, mixed forest and low coverage grassland decreased accordingly. The carbon storage of the Tibetan Plateau showed a decreasing trend by 0.37 × 106 t. (2) The spatial distribution patterns of carbon storage were consistent with that of the vegetation types. (3) In 2030 and 2060, under the constraint of the ecological priority development, the reduction in carbon storage was the smallest, at 0.01 × 106 t and 0.16 × 106 t, respectively. Under the constraint of the inertial development, carbon storage had the largest reduction, at 0.12 × 106 t and 0.43 × 106 t, respectively. (4) During 2000–2020, the dominant single factor that had the greatest impacts on the changes in carbon storage was FVC (vegetation coverage), with q values of 0.616, 0.619 and 0.567, respectively. The interactive dominant effects were mainly nonlinear enhancement and double-factor enhancement. The interactive dominant factors that had the greatest impact were FVC and the DEM (Digital Elevation Model), with q values of 0.94, 0.92 and 0.90, respectively. Therefore, ecological land with a high FVC should be protected and the expansion of non-vegetation areas should be restricted in future planning to improve the carbon storage level of the Tibetan Plateau and achieve the goal of carbon neutrality. Full article
(This article belongs to the Special Issue Advances in Monitoring and Assessment of Forest Carbon Storage)
►▼ Show Figures

Figure 1

15 pages, 15854 KiB  
Article
Vegetation Greening Enhanced the Regional Terrestrial Carbon Uptake in the Dongting Lake Basin of China
by Shihan Wang, Huihui Feng, Bin Zou, Zhuolin Yang and Shu Wang
Forests 2023, 14(4), 768; https://doi.org/10.3390/f14040768 - 8 Apr 2023
Cited by 1 | Viewed by 1671
Abstract
Terrestrial ecosystem carbon uptake is essential to achieving a regional carbon neutrality strategy, particularly in subtropical humid areas with dense vegetation. Due to the complex spatial and temporal heterogeneity of the carbon uptake of ecosystems, it is difficult to quantify the influence and [...] Read more.
Terrestrial ecosystem carbon uptake is essential to achieving a regional carbon neutrality strategy, particularly in subtropical humid areas with dense vegetation. Due to the complex spatial and temporal heterogeneity of the carbon uptake of ecosystems, it is difficult to quantify the influence and contribution of different factors. With the aid of multisource remote sensing data, the spatiotemporal characteristics of carbon uptake and the impact of vegetation change were explored in the Dongting Lake Basin from 2001 to 2020. Based on the Conversion of Land Use and its Effects at Small regional extent (CLUE-S) model, we simulated the land use of the basin under different development scenarios in 2030. Our results showed that the basin has demonstrated a significant greening trend in the last 20 years, with a multiyear average NDVI (normalized difference vegetation index) of 0.60 and an increasing trend (y = 0.0048x − 9.069, R2 = 0.89, p < 0.01). In this context, the multiyear mean of net ecosystem productivity (NEP) was 314.95 g C·m−2·a−1 and also showed a significant increasing trend (y = 1.8915x + 295.09, R2 = 0.23, p < 0.05). Moreover, though the future carbon uptake might decrease because of the enhanced anthropogenic activities, the ecological conservation scenario might mitigate the reduction by 0.05 × 107 t. In conclusion, the greening trend enhanced the ecosystem carbon uptake in the Dongting lake basin. Considering the representativeness of the Dongting Lake Basin, the results of our study would provide useful clues for understanding the trend and pattern of terrestrial carbon uptake and for guiding the carbon neutrality strategy in the subtropical humid area. Full article
(This article belongs to the Special Issue Advances in Monitoring and Assessment of Forest Carbon Storage)
►▼ Show Figures

Graphical abstract

20 pages, 71765 KiB  
Article
Spatiotemporal Changes in Leaf Area and Carbon Sequestration of Terrestrial Vegetation in China over the Last Two Decades
by Qingfeng Hu, Enjun Gong, Zhihui Wang, Jing Zhang, Wenkai Liu and Feng Feng
Forests 2022, 13(10), 1623; https://doi.org/10.3390/f13101623 - 3 Oct 2022
Cited by 4 | Viewed by 1944
Abstract
Spatio-temporal change characteristic in leaf area index (LAI), gross primary productivity (GPP), total leaf area and total carbon sequestration of terrestrial vegetation at different geographic regions, provinces and land cover change types over China during 2000–2018 were clarified, respectively. The net increase in [...] Read more.
Spatio-temporal change characteristic in leaf area index (LAI), gross primary productivity (GPP), total leaf area and total carbon sequestration of terrestrial vegetation at different geographic regions, provinces and land cover change types over China during 2000–2018 were clarified, respectively. The net increase in total leaf area and carbon sequestration over China from 2000 to 2018 is 1.7491 × 106 km2 and 1957.36 TgC, and Southwestern part contributes the most with a contribution of 25.3% for leaf area and 20.1% for carbon sequestration, respectively. The overall contribution of northern provinces to enhanced carbon sequestration capacity is greater than that of southern provinces, with a maximum for Inner Mongolia, even though southern provinces have a much higher leaf area increase. The annual increase rates of LAI and GPP in returning cropland to forest–grassland and artificial restoration of forest–grassland are higher than that of self-rehabilitation of rapid growth stage for planted young vegetation. However, due to self-rehabilitation of forest–grassland has the largest area percentage of 59%, it contributes the most to the increases of leaf area and carbon sequestration among different land cover change types, except for northeastern China, where improved farmland productivity is a dominant factor. It should be noted that the leaf area and carbon sequestration exhibit upward trends in urbanized areas over China. whereas slight increasing and even negative trends are also observed in southwestern, southern, and eastern China (e.g., Shanghai), where artificial surface construction occupied more cropland during urbanization processing. Compared with climatic factors, LAI is the dominant factor influencing GPP increases over China since 2000, and gradually weakened coupling relationship between LAI and GPP is observed from north to south. For climatic factors, GPP is dominantly affected by precipitation in northern parts and by solar radiation in southern parts. Full article
(This article belongs to the Special Issue Advances in Monitoring and Assessment of Forest Carbon Storage)
►▼ Show Figures

Figure 1

15 pages, 3944 KiB  
Article
Dynamic Model for Caragana korshinskii Shrub Aboveground Biomass Based on Theoretical and Allometric Growth Equations
by Xuejuan Jin, Hao Xu, Bo Wang and Xiaohua Wang
Forests 2022, 13(9), 1444; https://doi.org/10.3390/f13091444 - 8 Sep 2022
Cited by 1 | Viewed by 1124
Abstract
As one of the ways to achieve carbon neutralization, shrub biomass plays an important role for natural resource management decision making in arid regions. To investigate biomass dynamic variations of Caragana korshinskii, a typical shrub found in the arid desert area of [...] Read more.
As one of the ways to achieve carbon neutralization, shrub biomass plays an important role for natural resource management decision making in arid regions. To investigate biomass dynamic variations of Caragana korshinskii, a typical shrub found in the arid desert area of Ningxia, northwest China, we combined a nonlinear simultaneous (NLS) equation system with theoretical growth (TG) and allometric growth (AG) equations. On the basis of a large biomass survey dataset and analytical data of shrub stems, four methods (NOLS, NSUR, 2SLS, and 3SLS) of the NLS equations system were combined with the TG and AG equations. A model was subsequently established to predict the AGB growth of C. korshinskii. The absolute mean residual (AMR), root mean system error (RMSE), and adjusted determination coefficient (adj-R2) were used to evaluate the performance of the equations. Results revealed that the NSUR method of the NLS equations had better performance than other methods and the independent equations for BD and H growth and AGB. Additionally, the NSUR method exhibited extremely significant differences (p < 0.0001) when compared with the equations without heteroscedasticity on the basis of the likelihood ratio (LR) test, which used the power function (PF) as the variance function. The NSUR method of the NLS equations was an efficient method for predicting the dynamic growth of AGB by combining the TG and AG equations and could estimate the carbon storage for shrubs accurately, which was important for stand productivity and carbon sequestration capacity. Full article
(This article belongs to the Special Issue Advances in Monitoring and Assessment of Forest Carbon Storage)
►▼ Show Figures

Figure 1

13 pages, 1827 KiB  
Article
Response of Moso Bamboo Growth and Soil Nutrient Content to Strip Cutting
by Xiao Zhou, Fengying Guan, Xuan Zhang, Chengji Li and Yang Zhou
Forests 2022, 13(8), 1293; https://doi.org/10.3390/f13081293 - 15 Aug 2022
Cited by 5 | Viewed by 1669
Abstract
Moso bamboo (Phyllostachys edulis) is a critical forest resource in subtropical China, and reasonable cutting management of moso bamboo forests is essential for improving the productivity of bamboo forests, increasing the income of farmers, and improving the ecological environment. Therefore, we [...] Read more.
Moso bamboo (Phyllostachys edulis) is a critical forest resource in subtropical China, and reasonable cutting management of moso bamboo forests is essential for improving the productivity of bamboo forests, increasing the income of farmers, and improving the ecological environment. Therefore, we set up sample plots with different cutting widths at the Yixing Forest Farm in Jiangsu Province in December 2017. Moso bamboo growth surveys and soil sampling were conducted in May 2018 to study the effects of different cutting widths on the growth and nutrient content of moso bamboo forests. Our results indicate that strip cutting had significant effects on degraded bamboo shoots, the number of new bamboos, and their ratios. Soil elements showed surface aggregation, and cutting increased the soil nutrient content. Principal component analysis showed that stand characteristics (diameter at breast height and number of new bamboo shoots) were positively associated with total phosphorus and available phosphorus but negatively correlated with available potassium, total potassium, and soil organic carbon. A cutting width of 8 m resulted in rich nutrient content, which is suitable for bamboo cultivation. These results will provide theoretical guidance for the formulation of scientific and reasonable strip cutting methods for moso bamboo forests. Full article
(This article belongs to the Special Issue Advances in Monitoring and Assessment of Forest Carbon Storage)
►▼ Show Figures

Figure 1

22 pages, 4332 KiB  
Article
Global Sensitivity Analysis of the LPJ Model for Larix olgensis Henry Forests NPP in Jilin Province, China
by Yun Li, Yifu Wang, Yujun Sun and Jie Li
Forests 2022, 13(6), 874; https://doi.org/10.3390/f13060874 - 2 Jun 2022
Cited by 4 | Viewed by 1497
Abstract
Parameter sensitivity analysis can determine the influence of the input parameters on the model output. Identification and calibration of critical parameters are the crucial points of the process model optimization. Based on the Extended Fourier Amplitude Sensitivity Test (EFAST) and the Morris method, [...] Read more.
Parameter sensitivity analysis can determine the influence of the input parameters on the model output. Identification and calibration of critical parameters are the crucial points of the process model optimization. Based on the Extended Fourier Amplitude Sensitivity Test (EFAST) and the Morris method, this paper analyzes and compares the parameter sensitivity of the annual mean net primary productivity (NPP) of Larix olgensis Henry forests in Jilin Province simulated by the Lund–Potsdam–Jena dynamic global vegetation model (LPJ model) in 2009–2014 and 2000–2019, and deeply examines the sensitivity and influence of the two methods to each parameter and their respective influence on the model’s output. Moreover, it optimizes some selected parameters and re-simulates the NPP of Larix olgensis forests in Jilin Province from 2010 to 2019. The conclusions are the following: (1) For the LPJ model, the sensitive and non-influential parameters could be identified, which could guide the optimization order of the model and was valuable for model area applications. (2) The results of the two methods were similar but not identical. The sensitivity parameters were significantly correlated (p < 0.05); parameter krp was the most sensitive parameter, followed by parameters αm, αa and gm. These sensitive parameters were mainly found in the photosynthesis, water balance, and allometric growth modules. (3) The EFAST method had a higher precision than the Morris method, which could calculate quantitatively the contribution rate of each parameter to the variances of the model results; however, the Morris method involved fewer model running times and higher efficiency. (4) The mean relative error (MRE) and mean absolute error (MAE) of the simulated value of LPJ model after parameter optimization decreases. The optimized annual mean value of NPP from 2010 to 2019 was 580 g C m−2 a−1, with a mean annual growth rate of 2.13%, exhibiting a fluctuating growth trend. The MAE of the simulated value of LPJ model after parameter optimization decreases. Full article
(This article belongs to the Special Issue Advances in Monitoring and Assessment of Forest Carbon Storage)
►▼ Show Figures

Figure 1

19 pages, 3912 KiB  
Article
The Carbon Neutral Potential of Forests in the Yangtze River Economic Belt of China
by Huiling Tian, Jianhua Zhu, Zunji Jian, Qiangxin Ou, Xiao He, Xinyun Chen, Chenyu Li, Qi Li, Huayan Liu, Guosheng Huang and Wenfa Xiao
Forests 2022, 13(5), 721; https://doi.org/10.3390/f13050721 - 5 May 2022
Cited by 6 | Viewed by 2129
Abstract
Prediction of forest carbon sink in the future is important for understanding mechanisms concerning the increase in carbon sinks and emission reduction, and for realizing the climate goals of the Paris Agreement and global carbon neutrality. Based on stand volume data of permanent [...] Read more.
Prediction of forest carbon sink in the future is important for understanding mechanisms concerning the increase in carbon sinks and emission reduction, and for realizing the climate goals of the Paris Agreement and global carbon neutrality. Based on stand volume data of permanent monitoring plots of the successive national forest inventories from 2004 to 2018, and combined with multiple variables, such as climatic factors, soil properties, stand attributes, and topographic features, the random forest algorithm was used to predict the stand volume growth-loss and then calculated the forest biomass and its carbon sink potential between 2015 to 2060 in the Yangtze River Economic Belt of China. From 2015 to 2060, the predicted forest biomass carbon storage and density increased from 3053.27 to 6721.61 Tg C and from 33.75 to 66.12 Mg C hm−2, respectively. The predicted forest biomass carbon sink decreased from 90.58 to 73.98 Tg C yr−1, and the average forest biomass carbon storage and sink were ranked in descending order: Yunnan, Sichuan, Jiangxi, Hunan, Guizhou, Hubei, Zhejiang, Chongqing, Anhui, Jiangsu, and Shanghai. The forest biomass carbon storage in the Yangtze River Economic Belt will increase by 3.67 Pg C from 2015 to 2060. The proportion of forest C sinks on the regional scale to C emissions on the national scale will increase from 2.9% in 2021–2030 to 4.3% in 2041–2050. These results indicate higher forest carbon sequestration efficiency in the Yangtze River Economic Belt in the future. Our results also suggest that improved forest management in the upper and middle reaches of the Yangtze River will help to enhance forest carbon sink in the future. Full article
(This article belongs to the Special Issue Advances in Monitoring and Assessment of Forest Carbon Storage)
►▼ Show Figures

Figure 1

22 pages, 4330 KiB  
Article
Development of a Climate-Sensitive Matrix Growth Model for Larix gmelinii Mixed-Species Natural Forests and Its Application for Predicting Forest Dynamics under Different Climate Scenarios
by Liang Zhang, Youjun He, Jianjun Wang and Jinghui Meng
Forests 2022, 13(4), 574; https://doi.org/10.3390/f13040574 - 5 Apr 2022
Cited by 1 | Viewed by 1973
Abstract
Larix gmelinii natural forests, which are of great ecological and economic importance, are mainly distributed in northeast China. Sustainable management of these forests play a vital role in ecological security in northeast China, especially in the context of climate change. Forest growth models, [...] Read more.
Larix gmelinii natural forests, which are of great ecological and economic importance, are mainly distributed in northeast China. Sustainable management of these forests play a vital role in ecological security in northeast China, especially in the context of climate change. Forest growth models, which support forest management decision-making, are lacking for Larix gmelinii natural forests, hampering the prescription of forest management strategies. In this study, we produced a climate-sensitive, transition-matrix model (CM) for Larix gmelinii natural forests. For comparison, a variable transition model without including climate change effects (NCM) and a fixed-parameter model (FM) were also built. We examined the performance of the CM, NCM, and FM by conducting short- (5 years) and long-term (100 years) simulations. The results showed that for short-term prediction, no significant difference was observed among the three predictive models. However, the long-term prediction ability of the CM under the three different RCPs was superior to that of the FM and NCM. The number of trees and basal area were predicted to increase under climate change, which might result in natural disasters, such as snow break, windthrow, and forest fire. Silvicultural practices, such as reducing the intermediate thinning interval and the enrichment planting of slow-growing trees, should be implemented to mitigate the deleterious effects of climate change. Full article
(This article belongs to the Special Issue Advances in Monitoring and Assessment of Forest Carbon Storage)
►▼ Show Figures

Figure 1

Review

Jump to: Editorial, Research

21 pages, 2577 KiB  
Review
Net Primary Productivity of Forest Ecosystems in the Southwest Karst Region from the Perspective of Carbon Neutralization
by Binghuang Zhou, Zhangze Liao, Sirui Chen, Hongyu Jia, Jingyu Zhu and Xuehai Fei
Forests 2022, 13(9), 1367; https://doi.org/10.3390/f13091367 - 27 Aug 2022
Cited by 14 | Viewed by 3757
Abstract
The net primary productivity (NPP) of forest ecosystems is an important factor for understanding the carbon budget of forest ecosystems. There have been many studies on the spatialtemporal characteristics and change trends of the NPP in southwest areas based on observation and remote [...] Read more.
The net primary productivity (NPP) of forest ecosystems is an important factor for understanding the carbon budget of forest ecosystems. There have been many studies on the spatialtemporal characteristics and change trends of the NPP in southwest areas based on observation and remote sensing models. A comprehensive view of the overall state of the research on the carbon budget and a deeper exploration of its laws and effects are needed to reach a clear conclusion and accurately assess the NPP of forests in southwest China. Therefore, in this paper, we aim to highlight the relevant achievements in the study of the NPP of forest ecosystems, to summarize the research progress and spatial–temporal distribution law of the estimation of the NPPs of forest ecosystems, to analyse the relationship between the NPP and climate factors (such as temperature, precipitation and VPD), and to identify the main unsolved issues and suggest directions for future research. Our summary is expected to serve as a reference for forest ecosystem carbon budget management in the southwest and as a starting place for further research, and to promote the realization of the “double carbon” goal. Full article
(This article belongs to the Special Issue Advances in Monitoring and Assessment of Forest Carbon Storage)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-10
Back to TopTop