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Sustainable Forest Management and Natural Hazards Prevention

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Forestry".

Deadline for manuscript submissions: 30 April 2024 | Viewed by 21519

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Special Issue Editors

Dr. Abolfazl Jaafari

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Guest Editor

Research Institute of Forests and Rangelands, Agricultural Research, Education, and Extension Organization (AREEO), Tehran 64414-356, Iran
Interests: forestry; forest engineering; data science; predictive modeling; vulnerability assessment

Dr. Davood Mafi-Gholami

E-Mail Website
Guest Editor

Department of Forest Sciences, Faculty of Natural Resources and Earth Sciences, Shahrekord University, Shahrekord 8818634141, Iran
Interests: forestry; climate change; spatial modeling; vulnerability assessment

Special Issue Information

Dear Colleagues,

The implementation and monitoring of sustainable forest management remains challenging in an era of increasing types and intensities of environmental hazards. While local and national governments might be able to address the anthropogenic threats that emerge locally, the threat of many natural hazards such as fires, storms, rainfall pattern changes and drought occurrence, insect pests, and extreme temperatures (heat wave, cold wave and extreme winter conditions), are existential and require a timely global response if forest resources are to be sustained. Sustainable forest management in combination with risk and vulnerability assessments facilitates decision making and the development of management strategies to mitigate the adverse effects of various stresses and protect ecosystems. This Special Issue welcomes studies that consider interdisciplinary perspectives of forest sustainability to address the management challenges posed by natural hazards. In particular, this Special Issue will include articles that examine one or more of the following general themes:

Innovative use of state-of-the-art strategies, technologies, and methods/models for sustainable forest management;
Innovative use of state-of-the-art strategies, technologies, and methods/models for environmental hazards prevention in forest ecosystems;
Developing new approaches to support risk and vulnerability assessment in forest ecosystems;
Adopting adaptation programs to enhance the resilience of forest ecosystems to environmental hazards;
Determining the level of forest ecosystems vulnerability to environmental hazards;
Determining the historical impact of environmental hazards on the sustainability of forest ecosystems;
Predicting the future vulnerability of forest ecosystems to different climate change scenarios;
Predicting the future species distributions in response to different climate change scenarios.

This Special Issue is also open to studies that model the probability of occurrence of any types of natural hazards (e.g., fire, wind, drought, deforestation, land degradation, landslide, flood, extreme temperature, earthquake, sea-level rise, or volcano) and man-made hazards (e.g., logging operations, road construction, oil spill, gas flare, or heavy metal contamination) at any spatial level (e.g., state/provincial, national, or international) and temporal scale (e.g., month, year, decade, or century).

Dr. Abolfazl Jaafari
Dr. Davood Mafi-Gholami
Guest Editors

Manuscript Submission Information

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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. Sustainability is an international peer-reviewed open access semimonthly 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 2400 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 ecosystems
natural hazards
man-made hazards
hazard assessment
risk assessment
vulnerability assessment
adaptation
modeling
prediction

Published Papers (13 papers)

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Research

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20 pages, 9112 KiB

Open AccessArticle

Peatmass Change and Water Level Influencing Regenerated Melaleuca Forest after a Fire in U Minh Thuong National Park, Vietnam

by Luom Thanh Thai, Thang Van Tran, Khai Viet Le and Maja Flörke Staats

Sustainability 2024, 16(2), 620; https://0-doi-org.brum.beds.ac.uk/10.3390/su16020620 - 10 Jan 2024

Viewed by 553

Abstract

Following the largest forest fire in Vietnam in 2002, various activities were undertaken to sustain the mangrove forest on peat soil remnants in the Mekong Delta region. These activities included promoting natural regeneration, afforestation, and rapid forest restoration measures, in addition to other protective measures such as rainwater retention to maintain moisture levels for fire prevention. However, two critical challenges emerged: allowing the forest to naturally regenerate would lead to annual forest fires but maintaining a constant water level through year-round water retention would harm biodiversity. The study was conducted in U Minh Thuong National Park to address forest regeneration. After a major forest fire in Vietnam, various measures were taken to promote forest regeneration, including afforestation, silvicultural solutions, and hydrological techniques such as rainwater storage to maintain humidity and prevent future fires. A hand drill was used to collect samples, and a total of 15 plots were set up to survey the growth of the forest at three peat thickness levels. At each of the three collection sites, samples of one kg were collected and labeled according to the site as UTM1, UTM2, and UTM3. The samples were then sent to the laboratory of the Southern Institute of Forestry Science for analysis. There was a relationship between the chemical indicators of peat and the evolution of the Melaleuca forest. Peat thickness and flooding regime significantly influenced the growth of the Melaleuca forest, while another identified relationship was between peat chemical indicators and forest growth. The chemical composition of peat water changed significantly due to the rainy and dry seasons, with nutrient content and pH affecting forest growth. Peat thickness and flooding regime were essential in regulating forest growth. These studies highlight the importance of considering multiple factors, such as peat thickness and chemical properties, when developing effective forest restoration strategies. By understanding the relationship between peat thickness, chemical properties, and forest growth, forest managers can develop targeted strategies to promote regeneration while minimizing negative impacts on biodiversity. Full article

(This article belongs to the Special Issue Sustainable Forest Management and Natural Hazards Prevention)

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17 pages, 2006 KiB

Open AccessFeature PaperArticle

The Effect of Clearing Diseased Wood on the Soil’s Physicochemical Properties in Black Pine Forests

by Chuchen Wu, Chengyi Tu, Zhengyu Wang, Jingjing Fan, Zhenglin Lv and Ying Fan

Sustainability 2023, 15(22), 15980; https://0-doi-org.brum.beds.ac.uk/10.3390/su152215980 - 15 Nov 2023

Viewed by 782

Abstract

Clearing diseased wood is a common measure used to reduce the continued spread of pine wilt disease and prevent infecting other pines. However, the impact of clearing diseased wood on the physicochemical properties of the soil is still unclear. To elucidate this matter, we conducted a series of soil experiments and observations in Changdao, mainly focused on uncut black pine, cut black pine, and the inter-forest zone. The results showed the following. (1) The soil beneath the forest underwent a transition towards the characteristics of forest and grassland after clearing diseased wood, which indicated a potential shift in the ecosystem’s structure and function. (2) Clearing diseased wood led to an increase in the soil pH of 0.15, indicating that it facilitated the recovery of acidic soil. (3) The clearing of diseased wood can coarsen the soil’s texture. Moreover, it effectively reduced the surface soil temperature (0–20 cm) in summer by 1.52 °C, as well as significantly decreasing the surface (0–20 cm) soil moisture in spring and summer by 1.3% and 2.43%, respectively. (4) Clearing diseased wood clearing can effectively modify the content of essential nutrients in the soil. It reduced the available nitrogen by 26.86 mg·kg⁻¹, increased the available phosphorus by 0.57 mg·kg⁻¹, and decreased the available potassium by 1.68 mg·kg⁻¹. Meanwhile, clearing diseased wood exacerbated soil salinization and increased the soil’s salt content by 0.70 g·kg⁻¹. The findings of this study provide scientific solutions for the sustainable ecological development of black pine forests in Changdao. Full article

(This article belongs to the Special Issue Sustainable Forest Management and Natural Hazards Prevention)

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19 pages, 316 KiB

Open AccessArticle

A Model Proposal for Measuring Performance in Occupational Health and Safety in Forest Fires

by Ali Bahadır Küçükarslan, Mustafa Köksal and Ismail Ekmekci

Sustainability 2023, 15(20), 14729; https://0-doi-org.brum.beds.ac.uk/10.3390/su152014729 - 11 Oct 2023

Cited by 1 | Viewed by 778

Abstract

This study endeavors to prioritize occupational health and safety (OHS) accomplishments across ten forest management directorates in a specified province of Turkey, utilizing multi-criteria decision-making techniques (MCDMT). In a rigorous evaluation across four applied methodologies, the alternative P5 (amount of risk before measures) consistently exhibited superior performance. A notable emphasis of this research lies in the employment of a sophisticated OHS performance model, developed herein, to critically assess the OHS performance within these forest management directorates. In our evaluations, static variables such as land use and land cover, slope, vegetation type, soil characteristics, and distance from highways and human settlements were considered. Similarly, dynamic variables including temperature, wind speed and direction, and humidity were also factored in. Our findings corroborate the substantial ramifications, both tangible and intangible, of workplace accidents, hence underscoring the imperativeness of extensive, inter-industrial research initiatives geared towards effective accident prevention. This research is particularly focused on fortifying accident prevention measures in the arena of occupational health and safety during forest fires—an area with substantial economic and social implications, and of escalating importance in light of the expanding prominence of clean energy sources. Specifics pertaining to the forest fire rate within the studied directorates, as well as the criteria bearing the most and least impact as determined by this study, will be explicated in the full text, accompanied by their corresponding percentage values. Through the employment of Analytical Hierarchy Process (AHP), Fuzzy Analytical Hierarchy Process (F-AHP), and the Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE) method, this study demonstrates the efficacy of MCDMTs in assessing and categorizing OHS performance, hence contributing valuable insights to managers, OHS experts, and future research undertakings. In conclusion, this research concentrates on the formulation of employee-centric occupational health and safety systems, with a specific emphasis on forest fires. The proposed OHS performance index model represents a tool of exceptional potential in the evaluation of performance measurement, while addressing uncertainties across diverse sectors. This underscores the urgency of addressing health and sustainability issues within economic, social, and ecological domains through the rigorous examination and implementation of effective OHS practices. Full article

(This article belongs to the Special Issue Sustainable Forest Management and Natural Hazards Prevention)

20 pages, 1727 KiB

Open AccessArticle

Sustainability of Forest Development in China from the Perspective of the Illegal Logging Trade

by Jiping Sheng, Xiaoge Gao and Zhao Zhang

Sustainability 2023, 15(16), 12250; https://0-doi-org.brum.beds.ac.uk/10.3390/su151612250 - 10 Aug 2023

Viewed by 1107

Abstract

The illegal logging trade (ILT) is considered one of the major causes of global deforestation and ecological unsustainability. To prevent the price-suppressing damage caused by ILT to the local wood market and global ecological environment, the Chinese government and non-governmental organizations have taken many actions to deal with it. This study used wood trade data to analyze the current status of ILT in China, summarized the efforts and shortcomings of ILT response actions taken by China, and discussed the possible strategies and sustainable development prospects for combating ILT in China’s future. After studying China’s situation in the field of ILT and analyzing the advantages and disadvantages of China’s measures to deal with ILT, this study found that the volume of ILT gradually increased in China from 2013 to 2020, which might also be one of the reasons for the slowdown in global ecological sustainability. The Chinese government and non-governmental organizations have taken many actions to deal with ILT through legislation, industry supervision, and international cooperation; to date, these response actions have achieved some positive results. Therefore, on this basis, this study proposed that China needs to further limit and manage ILT to achieve sustainable development of forest resources in the future. Strengthening the legislation, especially the restriction of ILT clauses, as a mandatory policy is the most important means to solve the ILT problem, which can provide the legal basis and a reference for other actions. Using economic means to encourage the import of legal wood is also a viable action to crowd out the trade of illegal wood. It is also necessary to promote an international certification system for wood and the standardization and systematization of logging is also a good way to mitigate ILT. Improving the management of wood being imported into China will fill a critical gap at the global scale in dealing with ILT and have positive impacts on combating global ILT. Full article

(This article belongs to the Special Issue Sustainable Forest Management and Natural Hazards Prevention)

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20 pages, 6404 KiB

Open AccessArticle

Country-Level Modeling of Forest Fires in Austria and the Czech Republic: Insights from Open-Source Data

by Slobodan Milanović, Zoran Trailović, Sladjan D. Milanović, Eduard Hochbichler, Thomas Kirisits, Markus Immitzer, Petr Čermák, Radek Pokorný, Libor Jankovský and Abolfazl Jaafari

Sustainability 2023, 15(6), 5269; https://0-doi-org.brum.beds.ac.uk/10.3390/su15065269 - 16 Mar 2023

Cited by 1 | Viewed by 1546

Abstract

Forest fires are becoming a serious concern in Central European countries such as Austria (AT) and the Czech Republic (CZ). Mapping fire ignition probabilities across countries can be a useful tool for fire risk mitigation. This study was conducted to: (i) evaluate the contribution of the variables obtained from open-source datasets (i.e., MODIS, OpenStreetMap, and WorldClim) for modeling fire ignition probability at the country level; and (ii) investigate how well the Random Forest (RF) method performs from one country to another. The importance of the predictors was evaluated using the Gini impurity method, and RF was evaluated using the ROC-AUC and confusion matrix. The most important variables were the topographic wetness index in the AT model and slope in the CZ model. The AUC values in the validation sets were 0.848 (AT model) and 0.717 (CZ model). When the respective models were applied to the entire dataset, they achieved 82.5% (AT model) and 66.4% (CZ model) accuracy. Cross-comparison revealed that the CZ model may be successfully applied to the AT dataset (AUC = 0.808, Acc = 82.5%), while the AT model showed poor explanatory power when applied to the CZ dataset (AUC = 0.582, Acc = 13.6%). Our study provides insights into the effect of the accuracy and completeness of open-source data on the reliability of national-level forest fire probability assessment. Full article

(This article belongs to the Special Issue Sustainable Forest Management and Natural Hazards Prevention)

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18 pages, 1986 KiB

Open AccessArticle

Analysis of the Evolution of Mangrove Landscape Patterns and Their Drivers in Hainan Island from 2000 to 2020

by Yi Li, Hui Wen and Fengxia Wang

Sustainability 2023, 15(1), 759; https://0-doi-org.brum.beds.ac.uk/10.3390/su15010759 - 31 Dec 2022

Cited by 6 | Viewed by 2051

Abstract

The ecological services provided by mangroves are of great value and significance in regard of the achievement of the major strategic goals of carbon neutrality and the carbon peak. Here, we first evaluated the uses of five machine learning methods combined with Sentinal-2A data band features to identify and extract mangrove forests in Dongzhai Harbor, northeast Hainan Province, China. Then, the XGBoost algorithm with the highest accuracy was selected to identify and extract information on mangrove forests on Hainan Island, focusing on five periods from 2000 to 2020. The landscape pattern index, dynamic attitude model, and mathematical statistics were integrated to analyze trends over this 20-year period. The results revealed the following: (1) The total mangrove landscape area of Hainan Island between 2000 and 2020 showed a trend of first decreasing and then increasing. In the past 20 years, the mangrove area has increased by 1315.75 ha, with an annual change rate of 65.79 ha/a. (2) From 2000 to 2020, the mangroves in Hainan Island were characterized by increased fragmentation, increased heterogeneity, decreased connectivity, and increased richness, while proportion of each landscape type tends to be equilibrated. (3) Natural factors such as the annual average temperature in the study area were the main factors driving the large-scale reduction in mangroves and the deepening of landscape fragmentation, followed by human factors, and the impact of macro-policies cannot be ignored. The results of this study can provide a significant reference for future remote sensing data extraction from mangrove forests and their ecological protection and restoration on Hainan Island. Full article

(This article belongs to the Special Issue Sustainable Forest Management and Natural Hazards Prevention)

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13 pages, 3660 KiB

Open AccessArticle

How Do Different Land Uses/Covers Contribute to Land Surface Temperature and Albedo?

by Saeid Varamesh, Sohrab Mohtaram Anbaran, Bagher Shirmohammadi, Nadir Al-Ansari, Saeid Shabani and Abolfazl Jaafari

Sustainability 2022, 14(24), 16963; https://0-doi-org.brum.beds.ac.uk/10.3390/su142416963 - 17 Dec 2022

Viewed by 1737

Abstract

Land surface temperature (LST) and land surface albedo (LSA) are the two key regional and global climate-controlling parameters; assessing their behavior would likely result in a better understanding of the appropriate adaptation strategies to mitigate the consequences of climate change. This study was conducted to explore the spatiotemporal variability in LST and LSA across different land use/cover (LULC) classes in northwest Iran. To do so, we first applied an object-oriented algorithm to the 10 m resolution Sentinel-2 images of summer 2019 to generate a LULC map of a 3284 km² region in northwest Iran. Then, we computed the LST and LSA of each LULC class using the SEBAL algorithm, which was applied to the Landsat-8 images from the summer of 2019 and winter of 2020. The results showed that during the summer season, the maximum and minimum LSA values were associated with barren land (0.33) and water bodies (0.11), respectively; during the winter season, the maximum LSA value was observed for farmland and snow cover, and the minimum value was observed in forest areas (0.21). The maximum and minimum LST values in summer were acquired from rangeland (37 °C) and water bodies (24 °C), respectively; the maximum and minimum values of winter values were detected in forests (4.14 °C) and snow cover (−21.36 °C), respectively. Our results revealed that barren land and residential areas, having the maximum LSA in summer, were able to reduce the heating effects to some extent. Forest areas, due to their low LSA and high LST, particularly in winter, had a greater effect on regional warming compared with other LULC classes. Our study suggests that forests might not always mitigate the effects of global warming as much as we expect. Full article

(This article belongs to the Special Issue Sustainable Forest Management and Natural Hazards Prevention)

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23 pages, 13642 KiB

Open AccessArticle

Impact of COVID-19 Lockdown on Vegetation Indices and Heat Island Effect: A Remote Sensing Study of Dhaka City, Bangladesh

by Mizbah Ahmed Sresto, Md. Manjur Morshed, Sharmin Siddika, Hussein Almohamad, Motrih Al-Mutiry and Hazem Ghassan Abdo

Sustainability 2022, 14(13), 7922; https://0-doi-org.brum.beds.ac.uk/10.3390/su14137922 - 29 Jun 2022

Cited by 6 | Viewed by 2101

Abstract

It is predicted that the COVID-19 lockdown decreased environmental pollutants and, hence, urban heat island. Using the hypothesis as a guide, the objective of this research is to observe the change in vegetation pattern and heat-island effect zones in Dhaka, Bangladesh, before and after COVID-19 lockdown in relation to different forms of land use and land cover. Landsat-8 images were gathered to determine the vegetation pattern and the heat island zones. The normalized difference vegetation index (NDVI) and the modified soil-adjusted vegetation index (MSAVI12) were derived for analyzing the vegetation pattern. According to the results of the NDVI, after one month of lockdown, the health of the vegetation improved. In the context of the MSAVI12, the highest MSAVI12 coverages in March of 2019, 2020, and 2021 (0.45 to 0.70) were 22.15%, 21.8%, and 20.4%, respectively. In May 2019, 2020, and 2021, dense MSAVI12 values accounted for 23.8%, 25.5%, and 18.4%, respectively. At the beginning of lockdown, the calculated LST for March 2020 was higher than March 2019 and March 2021. However, after more than a month of lockdown, the LST reduced (in May 2020). After the lockdown in May 2020, the highest UHI values ranging from 3.80 to 5.00 covered smaller land-cover regions and reduced from 22.5% to 19.13%. After the end of the lockdown period, however, industries, markets, and transportation resumed, resulting in the expansion of heat island zones. In conclusion, strong negative correlations were observed between the LST and vegetation indices. The methodology of this research has potential for scholarly and practical implications. Secondly, urban policymakers can use the methodology of this paper for the low-cost monitoring of urban heat island zones, and thus take appropriate spatial counter measures. Full article

(This article belongs to the Special Issue Sustainable Forest Management and Natural Hazards Prevention)

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17 pages, 6098 KiB

Open AccessArticle

Projection Matrix Models: A Suitable Approach for Predicting Sustainable Growth in Uneven-Aged and Mixed Hyrcanian Forests

by Abotaleb Salehnasab, Harold E. Burkhart, Mahmoud Bayat, Bagher Khaleghi, Sahar Heidari and Hafiz Umair Masood Awan

Sustainability 2022, 14(11), 6777; https://0-doi-org.brum.beds.ac.uk/10.3390/su14116777 - 01 Jun 2022

Cited by 3 | Viewed by 1454

Abstract

The Hyrcanian forests of Iran are mainly managed with the single-selection silvicultural technique. Despite significant ecological benefits associated with selection cutting, this type of forest management leads towards more challenging situations where it is difficult to maintain and practice successful forestry than in even-aged systems. Therefore, this study provides relevant management tools in the form of models to estimate low growth levels in Hyrcanian forests. In the present study, estimation of the population growth rate and then the allowable cut rate of these forests using a matrix model have been calculated in the Gorazbon district. For this purpose, the data of 256 permanent sample plots measured during the years between 2003 and 2012, as well as the data recorded about the trees harvested according to the forestry plan, have been used. As a first step, the most frequently occurring tree species were divided into four groups (beech, hornbeam, chestnut-leaved oak, and other species). Compartments of the district were divided into two groups of logged and unlogged compartments. The purpose of this division was to estimate the allowable cut and compare its volume with the volumes of observed and predicted allowable cuts obtained from forestry plans. The results showed that the total operated allowable cut (OAC) in logged compartments was more than the estimated allowable cut (EAC). In unlogged compartments, the total predicted allowable cut (PAC) was more than EAC. A comparison of EAC and OAC showed that hornbeam has been harvested more than its potential. However, chestnut-leaved oak and other species group have depicted opposite trends. Our models provide important advancements for estimating allowable cut that can enhance the goal of practicing sustainable forestry. Full article

(This article belongs to the Special Issue Sustainable Forest Management and Natural Hazards Prevention)

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20 pages, 34136 KiB

Open AccessArticle

GIS-Based Frequency Ratio and Analytic Hierarchy Process for Forest Fire Susceptibility Mapping in the Western Region of Syria

by Hazem Ghassan Abdo, Hussein Almohamad, Ahmed Abdullah Al Dughairi and Motirh Al-Mutiry

Sustainability 2022, 14(8), 4668; https://0-doi-org.brum.beds.ac.uk/10.3390/su14084668 - 13 Apr 2022

Cited by 31 | Viewed by 3045

Abstract

Forest fires are among the most major causes of global ecosystem degradation. The integration of spatial information from various sources using statistical analyses in the GIS environment is an original tool in managing the spread of forest fires, which is one of the most significant natural hazards in the western region of Syria. Moreover, the western region of Syria is characterized by a significant lack of data to assess forest fire susceptibility as one of the most significant consequences of the current war. This study aimed to conduct a performance comparison of frequency ratio (FR) and analytic hierarchy process (AHP) techniques in delineating the spatial distribution of forest fire susceptibility in the Al-Draikich region, located in the western region of Syria. An inventory map of historical forest fire events was produced by spatially digitizing 32 fire incidents during the summers of 2019, 2020, and 2021. The forest fire events were divided into a training dataset with 70% (22 events) and a test dataset with 30% (10 events). Subsequently, FR and AHP techniques were used to associate the training data set with the 13 driving factors: slope, aspect, curvature, elevation, Normalized Difference Vegetation Index (NDVI), Normalized Difference Moisture Index (NDMI), Topographic Wetness Index (TWI), rainfall, temperature, wind speed, TWI, and distance to settlements, rivers and roads. The accuracy of the maps resulting from the modeling process was checked using the validation dataset and receiver operating characteristics (ROC) curves with the area under the curve (AUC). The FR method with AUC = 0.864 achieved the highest value compared to the AHP method with AUC = 0.838. The outcomes of this assessment provide constructive spatial insights for adopting forest management strategies in the study area, especially in light of the consequences of the current war. Full article

(This article belongs to the Special Issue Sustainable Forest Management and Natural Hazards Prevention)

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16 pages, 953 KiB

Open AccessArticle

Applicability Evaluation of Landslide Vulnerability Criteria for Decision on Landcreep-Vulnerable Areas in South Korea

by Jae-Hyeon Park, Seong-Gyun Park and Hyun Kim

Sustainability 2022, 14(8), 4447; https://0-doi-org.brum.beds.ac.uk/10.3390/su14084447 - 08 Apr 2022

Cited by 1 | Viewed by 1406

Abstract

Landcreep, which is a natural hazard, frequently occurs in South Korea. However, despite many differences between general landslides and landcreep, landcreep is still treated as a kind of landslide. A bigger problem in this reality is that no verification has been made on whether the national landslide vulnerability criteria can be applied to the decision on landcreep-vulnerable areas. Therefore, this study was conducted to examine the applicability of the landslide vulnerability criteria for the decision on landcreep-vulnerable areas. For verification, first, as a result of a correlation analysis that extracted seven types of geomorphological environment criteria that are used in deciding landslide-vulnerable areas from 57 landcreep areas, a positive correlation was shown only in the slope type and the parent rock. Second, as a result of the evaluation of the landcreep area by applying the landslide vulnerability criteria, it was analyzed that 61.4% were areas with low or no possibility of the occurrence of landslides. Third, on the basis of the overlapping analysis of the landslide hazard map and landcreep areas, 67.6% were in Level 3 or lower, except for Levels 1 and 2, which had high hazards, and 21.5% were landcreep areas that were not included in the hazard levels. Applying the landslide vulnerability criteria for deciding on landcreep-vulnerable areas is not appropriate, and it is urgent to prepare landcreep vulnerability criteria. Full article

(This article belongs to the Special Issue Sustainable Forest Management and Natural Hazards Prevention)

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17 pages, 2227 KiB

Open AccessArticle

Machine Learning for the Estimation of Diameter Increment in Mixed and Uneven-Aged Forests

by Abotaleb Salehnasab, Mahmoud Bayat, Manouchehr Namiranian, Bagher Khaleghi, Mahmoud Omid, Hafiz Umair Masood Awan, Nadir Al-Ansari and Abolfazl Jaafari

Sustainability 2022, 14(6), 3386; https://0-doi-org.brum.beds.ac.uk/10.3390/su14063386 - 14 Mar 2022

Cited by 8 | Viewed by 1942

Abstract

Estimating the diameter increment of forests is one of the most important relationships in forest management and planning. The aim of this study was to provide insight into the application of two machine learning methods, i.e., the multilayer perceptron artificial neural network (MLP) and adaptive neuro-fuzzy inference system (ANFIS), for developing diameter increment models for the Hyrcanian forests. For this purpose, the diameters at breast height (DBH) of seven tree species were recorded during two inventory periods. The trees were divided into four broad species groups, including beech (Fagus orientalis), chestnut-leaved oak (Quercus castaneifolia), hornbeam (Carpinus betulus), and other species. For each group, a separate model was developed. The k-fold strategy was used to evaluate these models. The Pearson correlation coefficient (r), coefficient of determination (R²), root mean square error (RMSE), Akaike information criterion (AIC), and Bayesian information criterion (BIC) were utilized to evaluate the models. RMSE and R² of the MLP and ANFIS models were estimated for the four groups of beech ((1.61 and 0.23) and (1.57 and 0.26)), hornbeam ((1.42 and 0.13) and (1.49 and 0.10)), chestnut-leaved oak ((1.55 and 0.28) and (1.47 and 0.39)), and other species ((1.44 and 0.32) and (1.5 and 0.24)), respectively. Despite the low coefficient of determination, the correlation test in both techniques was significant at a 0.01 level for all four groups. In this study, we also determined optimal network parameters such as number of nodes of one or multiple hidden layers and the type of membership functions for modeling the diameter increment in the Hyrcanian forests. Comparison of the results of the two techniques showed that for the groups of beech and chestnut-leaved oak, the ANFIS technique performed better and that the modeling techniques have a deep relationship with the nature of the tree species. Full article

(This article belongs to the Special Issue Sustainable Forest Management and Natural Hazards Prevention)

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Review

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21 pages, 830 KiB

Open AccessReview

Working in (Slow) Progress: Socio-Environmental and Economic Dynamics in the Forestry Sector and the Contribution to Sustainable Development in Europe

by Vito Imbrenda, Rosa Coluzzi, Francesca Mariani, Bogdana Nosova, Eva Cudlinova, Rosanna Salvia, Giovanni Quaranta, Luca Salvati and Maria Lanfredi

Sustainability 2023, 15(13), 10271; https://0-doi-org.brum.beds.ac.uk/10.3390/su151310271 - 28 Jun 2023

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Abstract

Forest ecosystems are increasingly subject to disturbances, such as extreme (climate) events, fires and pathological outbreaks, which exert significant (and still poorly quantified) economic impacts, despite their intrinsic resilience. How forest management addresses these challenges will have profound effects on human health, environmental diversity, (ecological and economic) productivity and the ability of forest ecosystems to recovery from exogenous shocks. Assuming forests as ensuring ecosystem services that are vital to society and human well-being, in addition to providing wood material, a better knowledge of forest ecosystems appears a key requirement to delineate a developmental strategy that guarantees environmental protection objectives and achievement of climate and energy targets. In the context of Sustainable Development Goals of the United Nations 2030 Agenda, the information available on forest management practices in Europe still seems not completely suitable to provide a comprehensive overview of ecosystem conditions, their economic value, and their biodiversity. Based on a literature review, the present contribution focuses on recent dynamics of the forestry sector in Europe, delineating the inherent complexity in the environmental-economic nexus. Additionally, the extensive use of a key natural resource such as wood exerts social implications for local districts adapting to ecological change—from climate warming to landscape transformations. In line with earlier studies, our paper confirms the role of the technical-economic dimension of forestry in sustainable development paths of districts and regions, affecting together (i) short-term economic dynamics, (ii) the growth prospects of the sector, (iii) the organization of the supply chain, (iv) the interconnections between companies, and (v) investment strategies at large. One of the major issues is the low reliability of official statistics to provide a coherent picture of the actual status of forest resources. At the same time, forestry practices are pivotal in maintaining habitats and species while increasing the timber production that remains (too) sustainable. This is the policy direction constantly given by the European Commission to stimulate over time public bodies and private (in whose hands is about 60% of European forests) to start virtuous paths in the circular economy with considerable repercussions in terms of additional jobs, recycled materials, mt of CO₂ equivalent avoided, and increase in community added value. In this context, forestry should assure a more ‘holistic’ contribution to sustainable development paths at various spatial scales. This means concentrating on both economic and environmental targets based on the identification of significant (ecological-economic) dimensions that may delineate future lines of investigation and policy intervention, while increasing between member countries and regional authorities. Full article

(This article belongs to the Special Issue Sustainable Forest Management and Natural Hazards Prevention)

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