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Forests
Special Issues
Forest Disturbance and Management
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Forest Disturbance and Management

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

Deadline for manuscript submissions: 31 December 2024 | Viewed by 4785

Special Issue Editors

Dr. Jie Zhao

E-Mail Website
Guest Editor
Shandong Provincial Key Laboratory of Water and Soil Conservation and Environmental Protection, College of Resources and Environment, Linyi University, Linyi 276000, China
Interests: forest disturbance; global climate change; remote sensing; GIS
Special Issues, Collections and Topics in MDPI journals
Dr. Chao Yue

E-Mail Website
Guest Editor
State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling 712100, China
Interests: forest disturbance; forest management; carbon cycle; land use change; ecosystem modeling; climate change
Special Issues, Collections and Topics in MDPI journals
Dr. Zhiwei Wu

E-Mail Website
Guest Editor
Key Laboratory of Poyang Lake Wetland and Watershed Research, Ministry of Education, Jiangxi Normal University, Nanchang 330022, China
Interests: spatial ecology; fire ecology; forest ecology
Special Issues, Collections and Topics in MDPI journals
Dr. Ziqiang Du

E-Mail Website
Guest Editor
Institute of Loess Plateau, Shanxi University, Taiyuan 030006, China
Interests: climate change; ecosystem service; remote sensing; land use and land cover change
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Forests cover approximately 31% of the global land area and are home to an estimated 80% of the world’s terrestrial biodiversity, playing a crucial role in providing ecosystem services such as carbon sequestration, watershed protection and timber resources. However, forests are increasingly threatened by a variety of disturbances, including wildfires, insect outbreaks, diseases and human activities such as deforestation and land use change.

Climate change is exacerbating these threats, leading to more frequent and severe disturbances in many forested regions. For example, warmer temperatures and changing precipitation patterns are altering the frequency and intensity of wildfires, while also affecting the distribution and abundance of forest pests and diseases. These disturbances can have profound impacts on forest ecosystems, leading to a loss of biodiversity, changes in forest structure and composition and reduced ecosystem resilience.

In response to these challenges, there is a growing need for effective forest management strategies that can help mitigate the impacts of disturbances and ensure the long-term sustainability of forest ecosystems. This Special Issue aims to address this need by bringing together the latest research on forest disturbance and management from around the world. By advancing our understanding of the drivers, impacts and management strategies related to forest disturbances, this Special Issue will contribute to the conservation and sustainable management of forests globally.

This Special Issue aims to bring together cutting-edge research in the field of forest disturbance and management. It will cover a wide range of topics, including, but not limited to:

  • Spatial and temporal patterns of forest disturbance;
  • Drivers and mechanisms of forest disturbances;
  • Impacts of disturbances on forest ecosystems and biodiversity;
  • Innovative approaches for monitoring and assessing forest disturbances;
  • Sustainable forest management practices and their implications;
  • Restoration and rehabilitation of disturbed forest ecosystems;
  • Socio-economic aspects of forest management and conservation.

Dr. Jie Zhao
Dr. Chao Yue
Dr. Zhiwei Wu
Dr. Ziqiang Du
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 disturbance
  • forest management
  • climate change
  • climate impacts
  • sustainable management
  • vegetation responses
  • biodiversity
  • forest restoration

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (4 papers)

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Research

22 pages, 16916 KiB  
Article
Estimation of Understory Fine Dead Fuel Moisture Content in Subtropical Forests of Southern China Based on Landsat Images
by Zhengjie Li, Zhiwei Wu, Shihao Zhu, Xiang Hou and Shun Li
Forests 2024, 15(11), 2002; https://doi.org/10.3390/f15112002 - 13 Nov 2024
Viewed by 345
Abstract
The understory fine dead fuel moisture content (DFMC) is an important reference indicator for regional forest fire warnings and risk assessments, and determining it on a large scale is a critical goal. It is difficult to estimate understory fine DFMC directly from satellite [...] Read more.
The understory fine dead fuel moisture content (DFMC) is an important reference indicator for regional forest fire warnings and risk assessments, and determining it on a large scale is a critical goal. It is difficult to estimate understory fine DFMC directly from satellite images due to canopy shading. To address this issue, we used canopy meteorology estimated by Landsat images in combination with explanatory variables to construct random forest models of in-forest meteorology, and then construct random forest models by combining the meteorological factors and explanatory variables with understory fine DFMC obtained from the monitoring device to (1) investigate the feasibility of Landsat images for estimating in-forest meteorology; (2) explore the feasibility of canopy or in-forest meteorology and explanatory variables for estimating understory fine DFMC; and (3) compare the effects of each factor on model accuracy and its effect on understory fine DFMC. The results showed that random forest models improved in-forest meteorology estimation, enhancing in-forest relative humidity, vapor pressure deficit, and temperature by 50%, 34%, and 2.2%, respectively, after adding a topography factor. For estimating understory fine DFMC, models using vapor pressure deficit improved fit by 10.2% over those using relative humidity. Using in-forest meteorology improved fits by 36.2% compared to canopy meteorology. Including topographic factors improved the average fit of understory fine DFMC models by 123.1%. The most accurate model utilized in-forest vapor pressure deficit, temperature, topographic factors, vegetation index, precipitation data, and seasonal factors. Correlations indicated that slope, in-forest vapor pressure deficit, and slope direction were most closely related to understory fine DFMC. The regional understory fine-grained DFMC distribution mapped according to our method can provide important decision support for forest fire risk early warning and fire management. Full article
(This article belongs to the Special Issue Forest Disturbance and Management)
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15 pages, 3864 KiB  
Article
Quantitative Study on the Effects of Vegetation and Soil on Runoff and Sediment in the Loess Plateau
by Gaohui Duan, Chunqian Leng, Zeyu Zhang, Cheng Zheng and Zhongming Wen
Forests 2024, 15(8), 1341; https://doi.org/10.3390/f15081341 - 1 Aug 2024
Cited by 1 | Viewed by 903
Abstract
Runoff and sediment (RAS) are important indicators of soil erosion in a watershed, playing a significant role in the migration of surface material and landform development. Previous studies have extensively documented the effects of trees, shrubs, herbs, and soil on runoff and sediment [...] Read more.
Runoff and sediment (RAS) are important indicators of soil erosion in a watershed, playing a significant role in the migration of surface material and landform development. Previous studies have extensively documented the effects of trees, shrubs, herbs, and soil on runoff and sediment during erosive rainfall; however, the precise interactions among these factors and their influence on RAS yield within the vegetation hierarchy remain unclear. Using the random forest algorithm and the structural equation model, this research aimed to quantify the interaction of numerous variables within diverse vegetation hierarchies and how they affect RAS, as well as to identify critical indicators that influence RAS. The structural equation model results show that the grass properties have a direct effect on soil properties, and the grass properties and soil properties both affect the canopy properties directly; the soil properties and canopy properties are the main factors influencing runoff and sediment directly. In addition, the grass properties could affect RAS by influencing the soil properties indirectly, and the soil properties could also affect RAS indirectly by influencing the canopy properties. Height difference (HD) between two layers of vegetation had the highest weight of 1.043 among the canopy variables, showing that HD has a substantial effect on RAS. Among the soil properties, soil bulk density and maximum field capacity have a significant impact on RAS. We conclude that canopy properties have the greatest impact on RAS. In the future, more Caragana microphylla Lam and Robinia pseudoacacia Linn plants should be planted to prevent soil erosion. This study provides a scientific basis for vegetation planting management and soil erosion control on the Loess Plateau. Full article
(This article belongs to the Special Issue Forest Disturbance and Management)
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15 pages, 3497 KiB  
Article
Understorey Plant Functional Traits of Platycladus orientalis Depends on Crown Closure and Soil Properties in the Loess Plateau, China
by Gaohui Duan, Lifeng Liu, Zhongming Wen, Yu Tang and Boheng Wang
Forests 2024, 15(6), 1042; https://doi.org/10.3390/f15061042 - 16 Jun 2024
Cited by 1 | Viewed by 1016
Abstract
The crown closure of Platycladus orientalis forests has a wide-ranging impact on vegetation and soil, thereby affecting the overall functioning of the ecosystem. There is limited research on the effects of the Platycladus orientalis forest crown closure on changes in community plant functional [...] Read more.
The crown closure of Platycladus orientalis forests has a wide-ranging impact on vegetation and soil, thereby affecting the overall functioning of the ecosystem. There is limited research on the effects of the Platycladus orientalis forest crown closure on changes in community plant functional traits, and their interactions are not yet clear. Therefore, we investigated 50 plots of different types of Platycladus orientalis crown closure, and we measured the functional traits of nine shrub species and 68 herb species in 50 plots under five different densities of Platycladus orientalis forests in the Loess Plateau. The consequence of Pearson’s correlation analysis showed significant positive correlations between LC and LTD, LN and LP, LN and LNP, LN and LV, LN and H, LP and LV, LP and H, and SLA and LV (p < 0.05). LC was significantly negatively correlated with LP, LC with SLA, LC with LV, LN with LTD, LP with LNP, LP with LTD, and LTD with H (p < 0.05). Only the soil phosphorus content (SP) and soil water content (SWC) showed a significant positive correlation with multiple plant functional traits. The crown closure of Platycladus orientalis forests increased significantly, as did the plant functional features. Changes in the Platycladus orientalis forest crown closure significantly increased the LC, LV, LN, LP, and SLA in plant functional traits. An increase in Platycladus orientalis forest crown closure significantly increased the soil organic carbon (SC), soil phosphorus content (SP), soil nitrogen content (SN), soil water content (SWC), field capacity (FC), and soil porosity (PO). Based on a structural equation model, we found that, while changes in the Platycladus orientalis forest crown closure did not directly affect plant functional traits, they could indirectly influence these traits through soil factors, primarily the soil water content (SWC) and soil phosphorus content (SP) (p < 0.05). Additionally, the mechanisms of the Platycladus orientalis forest crown closure’s impact on different functional traits vary. The research results provide scientific elements for the ecological restoration of Platycladus orientalis forests on the Loess Plateau. Full article
(This article belongs to the Special Issue Forest Disturbance and Management)
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17 pages, 6410 KiB  
Article
Comparative Analysis of Machine Learning-Based Predictive Models for Fine Dead Fuel Moisture of Subtropical Forest in China
by Xiang Hou, Zhiwei Wu, Shihao Zhu, Zhengjie Li and Shun Li
Forests 2024, 15(5), 736; https://doi.org/10.3390/f15050736 - 23 Apr 2024
Cited by 2 | Viewed by 1941
Abstract
The moisture content of fine dead surface fuel in forests is a crucial metric for assessing its combustibility and plays a pivotal role in the early warning, occurrence, and spread of forest fires. Accurate prediction of the moisture content of fine dead fuel [...] Read more.
The moisture content of fine dead surface fuel in forests is a crucial metric for assessing its combustibility and plays a pivotal role in the early warning, occurrence, and spread of forest fires. Accurate prediction of the moisture content of fine dead fuel on the forest surface is a critical challenge in forest fire management. Previous research on fine surface fuel moisture content has been mainly focused on coniferous forests in cold temperate zones, but there has been less attention given to understanding the fuel moisture dynamics in subtropical forests, which limits the development of regional forest fire warning models. Here, we consider the coupled influence of multiple meteorological, terrain, forest stand, and other characteristic factors on the fine dead fuel moisture content within the subtropical evergreen broadleaved forest region of southern China. The ability of five machine learning algorithms to predict the moisture content of fine dead fuel on the forest surface is assessed, and the key factors affecting the model accuracy are identified. Results show that when a single meteorological factor is used as a forecasting model, its forecasting accuracy is less than that of the combined model with multiple characteristic factors. However, the prediction accuracy of the model is improved after the addition of forest stand factors and terrain factors. The model prediction ability is the best for the combination of all feature factors including meteorology, forest stand, and terrain. The overall prediction accuracy of the model is ordered as follows: random forest > extreme gradient boosting > support vector machine > stepwise linear regression > k-nearest neighbor. Canopy density in forest stand factors, slope position and altitude in terrain factors, and average relative air humidity and light intensity in the previous 15 days are the key meteorological factors affecting the prediction accuracy of fuel moisture content. Our results provide scientific guidance and support for understanding the variability of forest surface fuel moisture content and improved regional forest fire warnings. Full article
(This article belongs to the Special Issue Forest Disturbance and Management)
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