Search

The purpose of this research is to study the changes in the market structure of China's pulp and paper product imports. In particular, the import trade environment and market layout of Chinese pulp and paper products have changed under the international context of the coronavirus pandemic and the Sino-US trade dispute and the domestic policy context of zero imports of Chinese waste paper. This study attempts to fill the gap regarding the influencing factors of market structure, while contributing new ideas on China's trade in pulp and paper products. Based on pulp and paper product import and export trade data from 2005 to 2021, a trade gravity model was used to explore the changes in the share of China's trade partners for pulp and paper product imports and their influencing factors. The results indicated that the outbreak of COVID-19 led to a significant increase in China's imports of packaging paper products, bringing about an increase in Indonesia's status as a partner in China's pulp and paper product trade. The US-China trade dispute had an impact on pulp and paper product trade between the two countries, with China's tax countermeasures causing the US to lose its status as a trading partner in China for pulp and paper product imports. The center of gravity for paper product imports has moved from the US and Japan to Indonesia and Russia. The restrictions on waste paper imports have shifted the focus of China's paper raw material imports, with the US no longer being the main importer of China's paper raw materials. Specifically, the main importers of wood pulp are Brazil and Chile, while the main importers of waste paper pulp are Thailand and Malaysia. In the future, China needs to continuously strengthen dialogue with the United States to resolve trade disputes and create a favorable environment for trade in pulp and paper products. At the same time, China's paper enterprises should strengthen the expansion of the Southeast Asian market and reduce dependence on the US market, and China should continue to improve the waste paper recycling system and improve the utilization rate of domestic waste paper. [ABSTRACT FROM AUTHOR]

China has been the world's largest producer and consumer of paper products. In the context of the "carbon peaking and carbon neutrality goals", China's papermaking industry which is traditionally a high energy-consuming and high-emissions industry, desperately needs a nationally appropriate low-carbon development path. From the consumption-side perspective, this paper calculates the CO2 emissions of China's papermaking industry from 2000 to 2019 by using carbon emission nuclear algorithm, grain-straw ratio, first-order attenuation method, and STIRFDT decomposition model, etc., to further explore the core stages and basic patterns affecting the industry's carbon peaking. The results show that the total CO2 emissions of China's papermaking industry showed an upward trend from 2000–2013, stable from 2013–2017, and a steady but slight decline from 2017–2019. Meanwhile, the total CO2 emissions of the full life cycle of paper products in China have decreased to a certain extent in the raw material acquisition, pulp, and paper making and shipping stages, with only the waste paper disposal stage showing a particular upward trend. We find that from 2000 to 2019, China's CO2 emissions in the pulping and papermaking stage of paper products accounted for 68% of the total emissions in the whole life cycle, of which 59% was caused by coal consumption. Moreover, the scenario prediction shows that improving the energy structure and increasing the waste paper recovery rate can reduce the CO2 emissions of the industry, and it is more significant when both work. Based on this and the four core stages of CO2 emissions of the papermaking industry we proposed ways to promote CO2 emissions peaking of China's paper products. [ABSTRACT FROM AUTHOR]

This study aims to systematically examine the developmental attributes and trends within China's forestry sector through the lens of a global value chain (GVC) framework. To this end, this research analyzes the Organization for Economic Co-operation and Development Inter-Country Input–Output (OECD-ICIO) database, using a cohesive set of GVC methods, including the forward decomposition of industry value-added, an assessment of industry upstream and downstream positions, the decomposition of export values, and analysis of trade competitiveness indicators. The trajectory of China's forestry industry hinges upon the interplay between foreign demand and domestic demand. The results reveal a transition in China's forestry sector development model from export-focused to a domestically driven approach. The proportion of value-added that is devoted to meeting domestic demands within the wood processing and papermaking industries has surged to 76% and 82%, respectively. Among the major economies, China has the highest output upstream index and input downstream index in the forestry industry, playing a vital role in propelling and pulling other industries into the global value chain system. The proportion of domestic added-value in China's forestry industry exports ranks among the top, reflecting strong self-sufficiency in export production. Although China's forestry industry possesses a high world market share, its overall international competitiveness is weak, especially with clear signs of weakening comparative advantages in the wood processing industry. [ABSTRACT FROM AUTHOR]

In recent years, bamboo has been well exploited in the pulp and paper industry. Moso bamboo (Phyllostachys edulis (Carriere) J. Houzeau; hereafter M), originated from China with a long history of cultivation as the most abundant resource with the widest distribution area among bamboo plants in China. In this study, Moso bamboo (M) and nine bamboo varieties were selected in the bamboo germplasm resources storage bank of the Anhui Taiping Experimental Station of ICBR. The characteristics of their cell structures were compared, and the differences were analyzed from a genetic perspective. The results showed that M had the highest fiber cell length, fiber cell width, length, and parenchyma width, while GJ showed the lowest of these measurements [P. edulis 'Kikko-chiku',G.H.Lai]. The fiber wall thickness of Q [P. edulis f. obliquinoda (Z.P.Wang et N.X.Ma) Ohrnberger] was the smallest, while its fiber lumen diameter was the highest in the group. The parenchyma wall thickness and parenchyma lumen diameter of Q were the smallest in the group. The fiber cells of M and Q had better flexibility, which is conducive to improving the tensile strength, break resistance, and folding resistance of paper made from these materials. SY and GJ may be more suitable for ornamental items because of their special appearances. The purpose of this study was to explore the genetic variation patterns of various cell structure indicators among Moso bamboo and its varieties, as well as to develop a strategy of bamboo growing and lumbering based on the local conditions, providing reference data for the utilization of non-woody forest resources. [ABSTRACT FROM AUTHOR]

In the critical period of strengthening the construction of ecological civilization, the construction of forest cities has become an important measure to promote urban ecosystem restoration and achieve sustainable development. Based on the mechanism of forest city promoting green development, the construction of a national forest city is regarded as a "quasi-natural experiment". Using China's urban panel data from 2005 to 2019, the impact of national forest city construction on urban green total factor productivity was evaluated using Multistage asymptotic double difference. The results show that National Forest Cities with environmental regulation can significantly promote regional green total factor productivity, which is still valid after a series of Robustness tests. Mechanism analysis shows that forest city construction not only affects territorial spatial planning but also forms a linkage with green technology innovation, mutual promotion and mutual promotion to jointly promote the sustainable development goals. This paper argues that building a national forest city is an important measure to achieve China's sustainable development goals in the new era, but in the process of policy implementation, it is necessary to implement the national forest city selection system according to local conditions. [ABSTRACT FROM AUTHOR]

Pine wilt disease (PWD) is a forest disease characterized by rapid spread and extremely high lethality, posing a serious threat to the ecological security of China's forests and causing significant economic losses in forestry. Given the extensive forestry area, limited personnel for inspection and monitoring, and high costs, utilizing UAV-based remote sensing monitoring for diseased trees represents an effective approach for controlling the spread of PWD. However, due to the small target size and uneven scale of pine wilt disease, as well as the limitations of real-time detection by drones, traditional disease tree detection algorithms based on RGB remote sensing images do not achieve an optimal balance among accuracy, detection speed, and model complexity due to real-time detection limitations. Consequently, this paper proposes Light-ViTeYOLO, a lightweight pine wilt disease detection method based on Vision Transformer-enhanced YOLO (You Only Look Once). A novel lightweight multi-scale attention module is introduced to construct an EfficientViT feature extraction network for global receptive field and multi-scale learning. A novel neck network, CACSNet(Content-Aware Cross-Scale bidirectional fusion neck network), is designed to enhance the detection of diseased trees at single granularity, and the loss function is optimized to improve localization accuracy. The algorithm effectively reduces the number of parameters and giga floating-point operations per second (GFLOPs) of the detection model while enhancing overall detection performance. Experimental results demonstrate that compared with other baseline algorithms, Light-ViTeYOLO proposed in this paper has the least parameter and computational complexity among related algorithms, with 3.89 MFLOPs and 7.4 GFLOPs, respectively. The FPS rate is 57.9 (frames/s), which is better than the original YOLOv5. Meanwhile, its mAP@0.5:0.95 is the best among the baseline algorithms, and the recall and mAP@0.5 slightly decrease. Our Light-ViTeYOLO is the first lightweight method specifically designed for detecting pine wilt disease. It not only meets the requirements for real-time detection of pine wilt disease outbreaks but also provides strong technical support for automated forestry work. [ABSTRACT FROM AUTHOR]

Park green space is a big part of public infrastructure in cities, and how to evaluate and optimize the mismatch of urban park green space (UPGS) has become the focus of current research in academia and industry. Taking China's 286 cities as an example, this paper used the spatial cluster and Boston Consulting Group Matrix to analyze the aggregation laws and changing modes of UPGS from 2010 to 2020, introduced the spatial mismatch model to analyze the matching of its supply and demand with GDP and population, and adopted the Geodetector to analyze the influencing factors. The findings: (1) The evolution of UPGS in China had long been characterized by a "pyramidal" pattern, i.e., limited green cities > developing green cities > steady green cities > booming green cities, exhibiting the spatial characteristics of gradient differences between the coasts and inland areas, and the aggregation of blocks in some areas. (2) The supply and demand mismatches of the UPGS were relatively stable, with negative matching being the main supply mismatch type, and positive matching being the main demand mismatch type. The contribution of supply and demand mismatches similarly showed a spatial pattern of a gradual decrease from the coast to inland and the aggregation of blocks in some areas. (3) Five types of factors played different driving roles on UPGS, with social development remaining a weak factor, and the strong factor switching from urban infrastructure to construction land scale. The interaction detection was dominated by a bilinear enhancement, with super-interaction factors changing from an output value of the tertiary industry and population urbanization rate to education expenditure in local general public budgets. (4) Based on the mismatch between the supply and demand for UPGS in China, 286 cities were classified into four types, namely a smart shrinking zone, smart growing zone, status quo zone, and overlay policy zone, and differentiated development proposals for the corresponding zoning were put forward. This paper constructed an application framework of "evolution pattern + supply demand match + driving factors + policy zoning" for UPGS at a large scale, which will effectively enhance the effective allocation of its resources across the country. [ABSTRACT FROM AUTHOR]

In the current context of carbon neutrality, afforestation is an effective means of absorbing carbon dioxide. Stock can be used not only as an economic value index of forest wood resources but also as an important index of biomass and carbon storage estimation in forest emission reduction project evaluation. In this paper, we propose a data-driven machine learning framework and method for predicting plantation stock based on airborne LiDAR + satellite remote sensing, and carried out experimental verification at the site of the National Forest emission reduction project in Southern China. We used step-up regression and random forest (RF) to screen LiDAR and Landsat 8 OLI multispectral indicators suitable for the prediction of plantation stock, and constructed a plantation stock model based on machine learning (support vector machine regression, RF regression). Our method is compared with traditional statistical methods (stepwise regression and partial least squares regression). Through the verification of 57 plantation field survey data, the accuracy of the stand estimation model constructed using the RF method is generally better (ΔR2 = 0.01~0.27, ΔRMSE = 1.88~13.77 m3·hm−2, ΔMAE = 1.17~13.57 m3·hm−2). The model evaluation accuracy based on machine learning is higher than that of the traditional statistical method, and the fitting R2 is greater than 0.91, while the fitting R2 of the traditional statistical method is 0.85. The best fitting models were all support vector regression models. The combination of UAV point clouds and satellite multi-spectral images has the best modeling effect, followed by LiDAR point clouds and Landsat 8. At present, this method is only applicable to artificial forests; further verification is needed for natural forests. In the future, the density and quality of higher clouds could be increased. The validity and accuracy of the method were further verified. This paper provides a method for predicting the accumulation of typical Chinese plantations at the forest farm scale based on the "airborne LiDAR + satellite remote sensing" data-driven machine learning modeling, which has potential application value for the current carbon neutrality goal of the southern plantation forest emission reduction project. [ABSTRACT FROM AUTHOR]

It is necessary for national parks to exert multiple forms of influence. One innovative function of national parks is leisure and recreation. By optimizing the recreation function, national parks can enhance public participation and tourists' willingness to pay to achieve sustainable development. This paper surveys 435 tourists in Wuyishan National Park with a discrete choice experiment, applies mixed logit models to explore their preferences for recreational attributes from three dimensions and analyzes the heterogeneity. The findings indicate that attributes such as the number of concession activities, transportation variety, the density of recreational facilities, biodiversity, sightseeing zone and combined ticket fee significantly impact tourists' willingness to pay. Higher-educated, younger and willing-to-revisit tourists are more likely to pay for the park and hope to optimize the facilities and activities. The estimated recreational value of the park is RMB 164.51 (about USD 22.75) per person. Here, heterogeneity exist: higher-educated tourists ask for lager sightseeing zone, younger ones prefer more diverse activities and those who are willing to revisit incline to variety means of transportation. [ABSTRACT FROM AUTHOR]

The rapid-developed scale of China's trade in wood forest products has undergone a considerable uptick. Concomitant with the evolution of high-quality development paradigms, product quality within trade frameworks has gained escalating scrutiny. Based on the statistical analysis of the export characteristics of China's wood forest products, this study leverages BACI data spanning from 1998 to 2017. Utilizing regression-based inverse methods, the study quantifies the quality attributes of these export products, dissects fluctuations in quality, and places particular emphasis on the markets within "Belt and Road Initiative" economies to elucidate dynamic trends and spatial distribution characteristics of export quality in this geoeconomic domain. Based on this, the fixed effect model, random effect model, and system GMM are used to empirically examine the influencing factors of China's wood forest product export quality. This study found that wood-based panel products have the highest quality, followed by paper products and wood furniture among the three major categories of wood forest products. Besides, the overall quality levels of the three products exported to countries participating in the Belt and Road initiative haven't significantly changed, while notable changes are evident across divergent export destination markets. In addition, an empirical study on the influencing factors of the export product quality of wood forest products is conducted, which indicates that total factor productivity, R&D investment, capital intensity, labor costs, and foreign direct investment are influencing factors. Finally, based on the research conclusions, suggestions are provided on how to improve the export quality of wood forest products. [ABSTRACT FROM AUTHOR]

With the increase in global temperature, the global change situation dominated by climate warming is becoming more and more serious. Climate change will cause differences in the suitable areas of species in different periods. Ginkgo biloba L., a rare and endangered wild plant protected at the national level in China, is the oldest relict plant in the world. Because of severe climate change, only China's wild Ginkgo biloba has been preserved, yet China's wild Ginkgo biloba population is facing extinction risk. Ginkgo biloba has rich ornamental value, application value, economic value, medicinal value and ecological value. Not only can it produce economic and ecological benefits, but it can also produce huge social benefits. Based on the data of Ginkgo biloba sample distribution, bioclimatic variables and soil variables, this paper uses the MaxEnt model to simulate Ginkgo biloba suitable area under current and future different climate scenarios, and analyzes the changes in the potential suitable area of Ginkgo biloba in the future through ArcGIS 10.6. The results are as follows: (1) the results simulated by the MaxEnt model are AUC > 0.9, showing that the simulation results have a high accuracy; (2) the min temperature of the coldest month, precipitation of the wettest month, elevation, and temperature seasonality are the main environmental variables affecting the change in the Ginkgo biloba suitable area; (3) under future climate scenarios, the suitable area of Ginkgo biloba is predicted to expand in the future, covering most of the south and some northeast regions, and moderate temperature and precipitation changes under climate change are conducive for the growth of Ginkgo biloba; and (4) in the future, the distribution center of the suitable area will move to the northeast. According to the conclusions in this paper, it is expected to provide theoretical reference for cultivation and management, sustainable utilization and solution of ecological environment problems of Ginkgo biloba. [ABSTRACT FROM AUTHOR]

Sustainable Forest Management (SFM) can fully use forest resources and improve the economic, environmental, and social sustainability of forest areas. Forestry enterprises play a crucial role in the implementation of SFM. However, the previous literature on SFM pays little attention to the subject of forestry enterprises. This paper aims to extend research on SFM from a macro perspective to the micro level of forestry enterprises. Taking the Triple Bottom Line (TBL) as a theoretical framework and the Montreal Process Criteria and Indicators (MP C&Is) as a basis, this paper constructs an indicator system to evaluate the performance of SFM of forestry enterprises from economic, social, and environmental aspects. Then, we apply the hybrid Multi-Criteria Decision-Making (MCDM) methods, i.e., the Best–Worst Method (BWM) and the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) method, to construct the methodological system for SFM performance evaluation of forestry enterprises. Through a questionnaire survey of 68 academics and researchers, we determine the weights of the SFM indicators and select a representative forestry enterprise as a case study. The effectiveness of this SFM performance evaluation model is then demonstrated through its application to the case study of forestry enterprises in China. Through the application of the model, this paper evaluates the enterprise's SFM performance over the five-year period 2017–2021 and proposes appropriate policy recommendations and improvements. It is found that environmental factors are the primary factors of SFM in forestry enterprises. Forestry enterprises should not only pay attention to economic benefits but also to the use of forest resources and the protection of forest ecosystems to better achieve SFM. [ABSTRACT FROM AUTHOR]

Nitrogen (N), an indispensable mineral nutrient element for plant growth and development, is a major limiting source of productivity in many terrestrial ecosystems. Soil organic nitrogen (SON) is a crucial form of nitrogen (N) in the N cycle within terrestrial ecosystems, acting as either a "source" or a "sink" for environmental N release. In order to illustrate the research trends, evolution process and hotspots of SON, a bibliometric analysis was used to analyze 906 documents based on the ISI (Institute of Scientific Information) Web of Science (WoS) database. The results indicated that (1) the number of published papers on SON research showed a wavy growth from 2000 to 2022 and the research has entered a mature development period; China has been increasing its number of publications and has long been in the lead; (2) the most productive institutions and authors in this subject area are in the USA and China, with the Chinese Academy of Sciences being the key institution performing such research; (3) in the sample, Soil Biology and Biochemistry, Science of the Total Environment, and Biogeochemistry are the leading international journals that have played a key role in the evolution of the field and have laid a solid foundation for future research; (4) the characteristics and maintenance of SON in farmland and SON migration in small watersheds under forest conversion have become research hotspots. Through the in-depth analysis of SON research, this paper provides a better understanding of the development trends of SON over the past 20 years, which can also provide reference for future research. [ABSTRACT FROM AUTHOR]

The research on picking robots is vital to the transformation and upgrading of the agroforestry industry and the revitalization and development of rural areas. This paper examines the research field of agroforestry picking robots by meticulously combing and analyzing 623 CNKI and 648 WoS core literature from 2004 to 2022 selected in China Knowledge Network (CNKI) and Web of Science (WoS) databases using Cite Space 6.1R3 software. The analysis includes the quantity of literature, issuing countries, organizations, keywords, keyword clustering, emerging terms, etc. On this basis, research hotspots in the field of agroforestry picking robots are identified, such as research based on the identification of picking targets, the control of motion planning, structural design and simulation, and the planning of walking paths. This paper analyzes and discusses these research hotspots and main lines, providing a reference for future studies in this field. This bibliometric approach can provide comprehensive literature information for research in related fields, as well as identify and summarize the major research hotspots in a shorter time, allowing new researchers to enter the field more quickly and obtain more valuable scientific information. [ABSTRACT FROM AUTHOR]

The digital economy is an important engine for promoting green economic development, and the integration of the digital and real economies can accelerate the transformation of the real economy. In order to explore the multifaceted influence of digital economy on forestry green total factor productivity and its specific presentation form, based on the panel data of 277 cities in China from 2013 to 2019, this paper first used the super SBM model to measure the level of forestry green total factor productivity and adopted the entropy method to measure the level of the digital economy in each region. Secondly, the influence and mechanism of the digital economy on green total factor productivity in forestry were explored by using fixed-effect and intermediate-effect models, and the heterogeneity of the digital economy on forestry green total factor productivity was analyzed based on different regional classification methods. Finally, the spatial spillover effect of the digital economy was explored in depth by the spatial Durbin model. The results are as follows: firstly, there is a significant inverted U-shaped relationship between the digital economy and forestry green total factor productivity, which first promotes and then inhibits. Secondly, the relationship between the digital economy and the level of urban green innovation shows a positive U-shaped relationship, first inhibiting and then promoting, and can have an indirect impact on forestry green total factor productivity by promoting the level of green innovation. Third, China is still on the left side of the inverted U-shaped relationship between the digital economy and forestry green total factor productivity, i.e., it is at a stage where the digital economy can significantly contribute to forestry green total factor productivity. Fourth, the effect of the digital economy on green total factor productivity in forestry is heterogeneous in the east, central, and west and is more pronounced in regions with faster economic development or rich natural resources. Fifth, the impact of the digital economy on forestry green total factor productivity has a significant positive spatial spillover effect. [ABSTRACT FROM AUTHOR]

Karst desertification (KD) is a major ecological and environmental problem threatening human survival and development in karst areas. In order to explore the research situation and development trend of KD based on forest ecology, this paper provides a systematic literature review based on the CNKI and WoS databases, which involves search, appraisal, synthesis, and analysis. We performed a statistical and visual analysis of 2955 studies acquired between 1 January 1995 and 30 June 2023, including the time distribution of the studies, hot research trends, pivotal research clusters, literature co-citations, main publishing trends, and keyword bursts. The results show the following. (1) The literature shows a fluctuating growth trend, and the research trends are divided into accumulation, development, and expansion stages. (2) The pivotal research clusters comprised three major aspects: study area and method, driving and genetic mechanisms, and control technology and models. (3) KD research forms a China-centered research network, dominated by institutions and scholars in southwestern China. (4) Future research needs to solve a series of related scientific issues and technological needs for forest ecosystem function optimization, ecological product supply capacity enhancement, ecological product value realization, ecological industry formation, and rural revitalization in KD control. The purpose of this paper is to reveal research trends relating to KD and highlight the future direction of KD research and control. [ABSTRACT FROM AUTHOR]

Extracting street trees from mobile Light Detection and Ranging (LiDAR) point clouds is still encountering challenges, such as low extraction accuracy and poor robustness in complex urban environment, and difficulty in the segmentation of overlapping trees. To solve these problems, this paper proposed a street tree extraction and segmentation method based on spatial geometric features of object primitives. In this paper, mobile LiDAR point clouds were first segmented into object primitives based on the proposed graph segmentation method, which can release the computation burden effectively. According to the spatial geometric features of the segmented object primitives, stem points were extracted. In doing so, the robustness and accuracy for stem detecting can be improved. Furthermore, voxel connectivity analysis and individual tree optimization were combined successively. In doing so, the neighboring trees could be separated successfully. Four datasets located in Henan Polytechnic University, China, were used for validating the performance of the proposed method. The four mobile LiDAR point clouds contained 106, 45, 76, and 46 trees, respectively. The experimental results showed that the proposed method can achieve the performance of individual tree separation in all the four testing plots. Compared to the other three methods, the proposed method can make a good balance between the commission and omission errors and achieved the highest average F1 scores. [ABSTRACT FROM AUTHOR]

At the present stage, China's ecological civilization construction has entered a strategic period focusing on carbon reduction, which is also a critical period for achieving the improvement of ecological environment quality. The prosperity of bamboo culture and the development of the bamboo industry are of great significance in promoting the construction of an ecological civilization in China. Festival activities often have lasting impacts on the development of the host city. They not only promote urban development but also spur the growth of local enterprises in related industries. However, these impacts have been rarely explored by researchers. This paper analyzes how festival activities influence the behavior of host city enterprises from the perspective of stakeholders with a theoretical model. Taking the China Bamboo Culture Festival as an example, micro-data on bamboo enterprises in 1999–2015 were collected from the Chinese Industrial Enterprise Database and analyzed with a theoretical model to empirically verify the influence of the festival over the production behavior of bamboo enterprises. The research shows that the China Bamboo Culture Festival has a significant positive impact on the total output value and total factor productivity of bamboo product enterprises, which in turn affects the production behavior of the enterprises. In the host province/city, the enterprises that engaged in the festival surpassed the other enterprises by 1.0764% in terms of gross output; export enterprises were less affected by the festival than domestic market enterprises. The China Bamboo Culture Festival makes bamboo enterprises more sustainable and competitive in the industry, and the holding of festival activities enhances the sustainable development capabilities of enterprises by improving their business environment. In addition, significant differences were observed between enterprises in different geographical locations, of different ownerships, and in different subdivided industries. Enterprises in the eastern region are least affected by the China Bamboo Culture Festival, while those in the western region are the most impacted; those in the central region fall in the middle by the degree of influence. Bamboo, rattan, palm, and grass products are influenced by the China Bamboo Culture Festival, while the production of other manufacturing industries is basically unaffected. [ABSTRACT FROM AUTHOR]

Wildfire is a pressing global issue that transcends geographic boundaries. Many areas, including China, are trying to cope with the threat of wildfires and manage limited forest resources. Effective forest fire detection is crucial, given its significant implications for ecological balance, social well-being and economic stability. In light of the problems of noise misclassification and manual design of the components in the current forest fire detection model, particularly the limited capability to identify subtle and unnoticeable smoke within intricate forest environments, this paper proposes an improved smoke detection model for forest fires utilizing YOLOv8 as its foundation. We expand the channel depth for fine-grain feature learning and retain more feature information. At the same time, lightweight convolution reduces the parameters of the model. This model enhances detection accuracy for smoke targets of varying scales and surpasses the accuracy of mainstream models. The outcomes of experiments demonstrate that the improved model exhibits superior performance, and the mean average precision is improved by 3.3%. This model significantly enhances the detection ability while also optimizing the neural network to make it more lightweight. These advancements position the model as a promising solution for early-stage forest fire smoke detection. [ABSTRACT FROM AUTHOR]

Environmental regulatory instruments are key to achieving synergy between high-quality economic development and ecological civilization construction. This paper measures the green overall factor productivity of the forestry in the Yangtze River Economic Belt by using the super-efficient nonexpected output SBM-ML index model. Additionally, it investigates the environmental regulation's impact on forestry's overall green factor productivity by using the conventional panel regression and panel smooth transformation model. The model was based on the relevant data obtained from eleven provinces along the Yangtze River Economic Belt in China from 2006 to 2021. This study concludes that command-and-control regulation of the environment and public engagement with environmental regulation can significantly promote the forestry green overall factor productivity in the Yangtze River Economic Belt, and the environmental regulation's effects on the forestry green overall efficiency in the economic region of the Yangtze River are regionally and temporally heterogeneous. The command-and-control environmental regulation also needs to exceed a certain level of regulatory coercion to promote the forestry green overall factor productivity positively. The effects of market-incentive environmental regulation were more pronounced with the increase in the regulatory intensity. When the regulation intensity surpasses the threshold, the public participation form of environmental regulation has a depressing impact on the forestry green overall factor output. To promote the development of the forestry industry in the Yangtze River Economic Zone, it is therefore necessary to strengthen the coordination of different environmental regulations, implement measures in each region, build a market-oriented green innovation system, and promote the structuralization and upgrading of the forestry industry. [ABSTRACT FROM AUTHOR]

In case of a shortage of China's domestic timber, the research of China's timber security has become increasingly more important. Using the pressure-state–response (PSR) conceptual model and the entropy method, the timber security of China during 1997–2017 was evaluated and analyzed to understand and master the situation of timber security in this paper. The results showed that: (1) The pressure of timber security in China during 1997–2017 was increasing in waves, with the condition of timber imports as the main factor; (2) the state of timber security in China presented a downward-then-upward tendency during 1997–2017, the main influencing factors of which were the domestic timber supply and forest resources condition; (3) responses to ensure the timber security of China almost indicated a steep rising trend, because both the timber industry technical progress index and the waste paper recovery rate improved the safety of timber in China; and (4) the changing trend of the comprehensive evaluation of timber security in China approximately agrees with that of the state evaluation, which showed that state indicators were key factors affecting the timber security of China. The pressures influencing the timber security of China are rising, while the state of timber security and the responses of the high-tech industry have been improving at a higher range than the pressures, which has led to an improvement of China's timber security. [ABSTRACT FROM AUTHOR]

Drought intensity and frequency have increased in recent years, which poses significant threats to forest ecosystems, especially in the context of global climate change. This paper is aimed at summarizing the current state of research and global development trends regarding drought-induced tree mortality mechanisms in tree physiology. Developing a robust literature foundation will facilitate in-depth research and foster the exchange of knowledge related to this subject. A literature review was conducted using tools such as VOSviewer, CiteSpace, and the Bibliometrix R-package to review the literature from the Web of Science's core database from 1985 to 2023. We intend to determine the current state and evolution of global research on drought-induced tree mortality mechanisms. The results reveal that research on drought-induced tree mortality mechanisms gained momentum predominantly in the last two decades, with a marked surge post-2012. The United States is the epicenter of research, leading the global scientific community with its preeminence in publication volume, citation rates, and the scope of collaborative networks, with China in close pursuit. Tree Physiology stands out as the leading journal in this domain, boasting 129 articles. McDowell NG emerges as the most prolific author, with an H-index of 41, underscoring his influence in the field. There is a clear upward trend in collaborations spanning authors, journals, research institutions, and countries. The analysis of frequently cited keywords and topic evolution suggests that drought and tree mortality will likely remain key research areas for the foreseeable future. The future of research on drought-induced tree mortality mechanisms in physiology is promising, as it emphasizes multidisciplinary approaches and global collaborations. [ABSTRACT FROM AUTHOR]

To achieve a sustainable development path that harmonizes ecological and economic considerations, China has advocated the "two mountains" concept: "lucid waters and lush mountains are invaluable assets". This idea posits that those who protect the environment can economically benefit by selling pristine landscapes and utilizing rich ecological resources. This paper use "the equivalence factor method" to calculate ecological benefits, introduces a technical measure—the conversion rate of ecosystem service value—and analyzes its temporal and spatial evolution from 2003 to 2020 in the operational areas of 87 state-owned forestry enterprises in Northeast China. The findings show: (1) a significant improvement in ecosystem-service quality, with its value increasing from 404.7 to 850.2 billion CNY between 2003 and 2020. The restoration of the ecological environment in China's KSFR provides a foundation for economic and social development. (2) A decrease in the economic gains derived by operators from developing protected ecosystems, with the most significant decline observed in economic benefits generated from the supply product, including timber harvesting. However, the industrial structure in KSFR shifted from being dominated by timber production to diversified development, with non-timber forest resources becoming an important part of regional economic growth. (3) Significant potential for realizing the value of ecosystem services, evidenced by an increasing trend in the conversion rates of cultural, regulatory, and supporting services. These findings underscore the effectiveness of China's natural forest protection and restoration policies in optimizing forest ecology and realizing the "two mountains" concept through appropriate market transactions and ecological compensation mechanisms. [ABSTRACT FROM AUTHOR]

Despite growing recognition of nature-based solutions (NBS), there remains a research gap in understanding their implementation in urban areas, which poses a significant challenge for urban forest development. Therefore, our paper aims to explore the intersection of NBS with urban forests (UF), identify current barriers, propose strategies to maximize the potential of urban forests as nature-based solutions (UF-NBS) in effectively improving the resilience of urban forests, and enhance the service capacity of urban forest ecosystems. To achieve our objective, we conducted a comprehensive analysis that included a bibliometric review to summarize the evolution of the UF-NBS literature and classify UF-NBS types for the first time. Subsequently, we identified and organized current challenges faced by UF-NBS. Additionally, we proposed an original technological framework system for urban forest development based on NBS principles. The results show the significance of UF-NBS for enhancing urban resilience and human wellbeing, with multiple successful implementations in both China and Europe, validating their effectiveness. However, the implementation of UF-NBS faces several challenges, including inadequate financing, the gap between scientific knowledge and practical implementation, the absence of region-specific information, and the need for interdisciplinary collaboration. This study contributes to establishing a scientific theoretical basis for integrating UF and NBS and provides a systematic approach for decision-makers in urban forest management. Future research should focus on exploring the integration of UF within the NBS framework and prioritize knowledge sharing, international cooperation, and education initiatives to promote the global adoption of UF-NBS and address pressing urban challenges. [ABSTRACT FROM AUTHOR]

Forest fires are a type of disaster with both human and natural factors; they differ from other forest disasters, in that they can cause significant damage not only to the ecological environments but also to the economy and society in many irreversible ways. While the risk factor of forest fires has been large, systematic studies on economic losses caused by forest fires have been lacking in recent years, and there is also a lack of analysis on forest fire economic losses in both spatial and temporal dimensions. Therefore, based on the forest fire data from 2006 to 2018, this paper establishes a forest fire economic loss evaluation system to calculate the economic losses in China and analyzes the spatial distribution characteristics and change trends of the forest fire economic losses in each province through thermal mapping. The results show the following. (1) The economic loss from forest fires in China is generally characterized by a fluctuating decline, but anomalous values due to human factors may occur. (2) The spatial heterogeneity of economic loss in China's provinces is limited by many factors, such as the differences in resource endowments, showing the characteristics of "low in the eastern and western regions and high in the central region". (3) Forest fires in China cause the most serious losses to forest ecological benefits. (4) Forest resources and fires are not independent of each other between regions, and areas with similar economic losses related to forest fires are often found in blocks. (5) Although the overall economic losses caused by forest fires in China are fluctuating and decreasing, some provinces are showing signs of increasing economic losses, most notably in Inner Mongolia. Therefore, this paper suggests targeted recommendations based on forest fires in different regions and with reference to the changing trends of economic loss caused by forest fires. For low-loss areas, we can further reduce the economic loss per unit area while ensuring that the losses do not increase any further. For high-loss areas, the main focus should be to find the weak points in the adaptation to forest fires. The right way to permanently reduce the damage caused by forest fires is to improve the adaptive and symbiotic capacity of the ecosystems and residential communities in relation to fires in a targeted manner and to improve the capacity for quick economic recovery after a fire. [ABSTRACT FROM AUTHOR]

Corporate social responsibility (CSR) disclosure serves as a vital bridge for forestry firms to communicate with their stakeholders and obtain legitimacy support. Existing studies focus on forestry firms' CSR disclosures based on CSR reports but lack consideration of such disclosures on social media. In this study, based on WeChat, the most widely used social media platform in China, we obtained 3311 tweets from 36 WeChat Official Accounts (WOA) of 63 Chinese-listed forestry firms in 2018 and used content analysis to classify the CSR information involved in these tweets based on the stakeholder dimensions. The main analysis results show that the top three CSR dimensions disclosed by Chinese forestry firms in social media are the shareholder (28.21%), customer (26.20%), and employee (23.64%) dimensions, and there are also great differences in the subcontent of disclosure concerns in each stakeholder dimension, e.g., approximately 86% of CSR disclosures for customers are product and service information. Additionally, we conducted a content analysis on the CSR reports of forestry firms using WOA. The results show that firms express different concerns in CSR reports than on social media, and the most mentioned dimensions in their reports are the environment (23.69%), employees (20.91%), and shareholders (20.21%). This indicates that there is a significant difference between the stakeholders that Chinese forestry firms focus on in social media and those that they focus on in CSR reports. This paper is the first study to focus on the CSR disclosure of Chinese forestry firms in social media and provides a reference for scholars to understand the information activities of forestry firms in social media. [ABSTRACT FROM AUTHOR]

Improving the income and assets of forest farmers is the basis for realizing the sustainable development of forestry. In this paper, we tested the impact of membership in herbal medicine planting cooperatives on forest farmer household income and assets using the propensity score matching (PSM) method and household surveys of the study area. The results showed that cooperative membership can greatly improve forest farmer household income and assets; the higher the accumulation of forest farmer household social capital and human capital, the more farmers were inclined to participate in cooperatives. Householders who were migrant workers were more likely to make the decision to participate in cooperatives compared with those without migrant work experiences. The results of ATT further verified the conclusion that cooperative membership can significantly improve income and assets, which increased by 7.04% and 4.19%, respectively. In addition, according to the survey, the current development of cooperatives in the forestry area experienced problems such as inconsistent quantitative and qualitative development, insufficient driving force, irregular operating mode, inaccurate policy support, and inadequate guidance mechanisms. This paper focused on innovating cooperation mechanisms, enriching joint forms, enhancing driving capacity, stimulating internal driving forces, strengthening system construction, improving standards, enhancing guidance services, and strengthening institutional guarantees. These recommendations have been put forward to guide policy for sustainable forest development. [ABSTRACT FROM AUTHOR]

Forest floor dead fuel moisture content (DFMC) is an important factor in the occurrence of forest fires, and predicting DFMC is important for accurate fire risk forecasting. Large areas of forest surface DFMC are difficult to predict via manual methods. In this paper, we propose an unmanned aerial vehicle (UAV)-based forest surface DFMC prediction method, in which a UAV is equipped with a multispectral camera to collect multispectral images of dead combustible material on the forest surface over a large area, combined with a deep-learning algorithm to achieve the large-scale prediction of DFMC on the forest surface. From 9 March to 23 March 2023, 5945 multispectral images and 480 sets of dead combustible samples were collected from an urban forestry demonstration site in Harbin, China, using an M300 RTK UAV with an MS600Pro multispectral camera. The multispectral images were segmented by a K-means clustering algorithm to obtain multispectral images containing only dead combustibles on the ground surface. The segmented multispectral images were then trained with the actual moisture content measured by the weighing method through the ConvNeXt deep-learning model, with 3985 images as the training set, 504 images as the validation set, and 498 images as the test set. The results showed that the MAE and RMSE of the test set are 1.54% and 5.45%, respectively, and the accuracy is 92.26% with high precision, achieving the accurate prediction of DFMC over a large range. The proposed new method for predicting DFMC via UAV multispectral cameras is expected to solve the real-time large-range accurate prediction of the moisture content of dead combustible material on the forest surface during the spring fire-prevention period in northeast China, thus providing technical support for improving the accuracy of forest fire risk-level forecasting and forest fire spread trend prediction. [ABSTRACT FROM AUTHOR]

Considering the majority of previous assessment perspectives on tourism carrying capacity are limited by "the number of visitors", this paper develops an innovative approach from the "visitors' experience utility" perspective. Using the choice experiment method, tourism carrying capacity is assessed by exploring the marginal utility and sensitivity of visitors to changes in recreational attributes. Xian-Ren-Tai National Forest Park in China is employed as the case park to demonstrate the application of this assessment method. The conclusions are as follows: the carrying capacity threshold of the crowding level in this urban forest park ranges from 20–35 people/100 m2, the threshold of "vegetation coverage" ranges from 70% to 80%, and the "number of garbage" is 3–10 pieces/200 m. The acceptable traffic accessibility level for visitors is within 3 h. At present, Xian-Ren-Tai National Forest Park as a whole is in a state of "low carrying capacity", there are potential risks of underutilization in this park. In addition, this paper provides the carrying capacity state of 27 potential recreational attribute sets. [ABSTRACT FROM AUTHOR]

Both in Germany and in China, there is strong expertise regarding the different aspects of forest management, as well as forest products management. Nevertheless, forestry in both countries is facing challenges, some of which are regional, but many of which are shared. Therefore, experts from both countries (Technical University of Munich Germany; Northwest A&F University Yangling, China; Forestry Academy of Shaanxi, China; Thünen Institut, Germany; FEDRC GIZ Forest Policy Facility (Forestry Economics Development and Research Center of the Deutsche Gesellschaft für Internationale Zusammenarbeit GmbH), Germany; and Center for Natural Forest Protection in Shaanxi, China) met to share their knowledge and deduce recommendations for future multifunctional forest management for the temperate zone. The workshop, held at the Northwest A&F University in September 2018, included presentations and intensive discussions, as well as a field tour. The results of the workshop that are summarized in this white paper are meant to provide an overview of the multi-faceted nature of the topic for interested scientists and forest practitioners, describe tools that can be used to analyze various aspects of multifunctionality and, in an exemplary fashion, highlight gathered experience from long- and short-term experiments. Included are social demands, economic goals, and scientific baselines. The topics reach from economic evaluations of forest ecosystem services over forest management practices, including afforestation, restoration, and preparations to face climate change, to wood/forest products utilization and participation of local people for poverty reduction. Overall, an optimistic picture emerges, showing that by using adapted forest management practices, which try to embrace the concept of multifunctionality, various use schemes and demands can be integrated at single sites, allowing us to achieve both environmental protection and productive forests, including societal demands, as well as aspects of tradition and national identity. [ABSTRACT FROM AUTHOR]

In order to address the challenges posed by elevated manual labor costs and limited automation in traditional log diameter grading and sorting processes, this paper centers on the design and research of an intelligent log diameter grading and sorting line utilizing machine vision. The study focuses on logs with smaller diameters located in Fujian province, China. By analyzing production requirements, the study formulates the structure of the feeding, alignment, detection, and sorting zones to fulfill sorting functions. Using the YOLOv5 model, the system achieves accurate log end face positioning, and the diameter is computed through a designated algorithm. The operational process of the system is examined, and the control logic governing the production line is elucidated. Evaluating the practical performance of the production line, the study assesses the accuracy of diameter recognition, precision in grading, and operational efficiency. The results reveal that the absolute error in diameter detection for the sorting line averages 1.12 mm, with sorting accuracy exceeding 95%. The sorting line can automatically categorize logs with diameters ranging from 60 mm to 300 mm and lengths ranging from 2 m to 6 m, achieving an annual sorting capacity of 120,000 to 130,000 cubic meters. The research findings illustrate that the system fulfills the industry's demands for log diameter grading and sorting, thereby enhancing economic efficiency for enterprises. [ABSTRACT FROM AUTHOR]

Despite their relatively small numbers, large old trees play disproportionately important roles in global biodiversity and ecosystem functions. There is a lack of systematic reviews and quantitative analyses of the accumulated literature. Understanding the research context and evolution could pump prime research and conservation endeavors. Using the comprehensive Web of Science, we applied VOSviewer (1.6.19) and CiteSpace (6.1R2) bibliometric software to examine the large old tree research field in 2000–2022. The queries of the bibliographic database generated quantitative–visual depictions in the form of knowledge maps. The nodes denote research intensity, and inter-node linkages denote the pathways and frequencies of collaborative activities. The research outputs differed significantly in terms of regions, countries, institutions, high-citation articles, productive researchers, hot topics, and research frontiers. Conspicuous spatial disparities were displayed, with the U.S.A., China, and Australia leading in publication counts and a cluster of European countries making considerable collective contributions. The research collaboration demonstrated a dichotomy: European countries networked more by geographical propinquity, and the top three countries connected by long-distance leap-frog jumps. The entrenched discrepancies between the endowed developed domains vis-à-vis the deprived developing domains were clearly expressed. The research productivity progressed through three stages: initial, growth, and flourishing. The leading institutions, researchers, and highly cited papers were recognized. The keyword analysis pinpointed diverse research hotspots: growth dynamics, conservation and management, ecological functions, and environmental response. This study informs recommendations for future research directions and cooperation on longevity mechanisms, evolutionary adaptation, dynamic monitoring, and temporal–spatial patterns. The integrated application of GIS, machine learning, and big data technologies could strengthen research capability. [ABSTRACT FROM AUTHOR]

Globally, forest ecosystems, especially subtropical forests, play a central role in biogeochemical cycles and climate regulation, demonstrating their irreplaceable function. The subtropical region of China, characterized by its unique forest ecosystem, complex terrain, climate heterogeneity, diverse vegetation types, and frequent human activities, underscores the importance of the in-depth study of its net primary productivity (NPP). This paper employs the eddy covariance–light use efficiency (EC-LUE) model to quantitatively estimate the gross primary productivity (GPP) of this region from 2001 to 2018, followed by an estimation of the actual net primary productivity (ANPP) using the carbon use efficiency (CUE). The results showed that over these 18 years, the annual average ANPP was 677.17 gC m−2 a−1, exhibiting an overall increasing trend, particularly in mountainous areas, reserves, and the cultivated lands of the northeastern plains, whereas a significant decrease was observed around the urban agglomerations on the southeast coast. Furthermore, the Thornthwaite memorial model was applied to calculate the potential net primary productivity (PNPP), and diverse scenarios were set to quantitatively evaluate the impact of climate change and human activities on the vegetation productivity in the study area. It was found that in areas where the ANPP increased, both human activities and climate change jointly influenced ANPP dynamics; in areas with a decreased ANPP, the impact of human activities was particularly significant. Additionally, the heterogeneous distribution of ANPP across different altitudinal gradients and the driving effects of various climatic factors were analyzed. Finally, a partial correlation analysis was used to examine the relationships between the temperature, precipitation, and ANPP. This study indicated that temperature and precipitation have a substantial impact on the growth and distribution of vegetation in the region, yet the extent of this influence shows considerable variation among different areas. This provides a robust scientific basis for further research and understanding of the carbon dynamics of subtropical forest ecosystems and their role in the global carbon cycle. [ABSTRACT FROM AUTHOR]

Castanopsis hystrix, a dominant canopy species in the subtropical forests of south China, is renowned for its high natural regeneration ability. Therefore, this paper took C. hystrix as the subject of study. Examining the variations in microbial diversity and community composition within the soil rhizosphere of C. hystrix across different elevation gradients, we explored how this community-forming species impacts soil microbial diversity and community structure and how soil microorganisms respond to changes in soil physicochemical properties due to altitude gradients. The results show: (1) soil samples from five altitudes established 1078 fungal OTU and 5595 bacterial OTUs. (2) Basidiomycota and ascomycota are dominant fungal groups in the soil, with Acidobacteria being the predominant bacteria for C. hystrix. (3) As altitude increases, fungal communities' richness and diversity index peaks at 849 m; for bacterial communities, the richness index peaks at 387 m and the diversity index at 670 m. (4) Total phosphorus (TP), nitrate nitrogen (NO3−-N), hydrolyzed nitrogen (HN), total nitrogen (TN), and organic matter (SOM) are significant environmental factors affecting fungal community structure. At the same time, available potassium (AK) significantly influences the composition of bacterial communities. The study underscores the intricate relationship between altitude, soil properties, and microbial diversity, offering insights into how C. hystrix contributes to ecosystem resilience. Recommendations include enhancing phosphorus supplementation and controlling nitrogen deposition to maintain forest ecological integrity, additionally, the supply of potassium in the soil should also be a key consideration. Further research is necessary to understand the broader implications for biodiversity conservation and adaptive management strategies in the face of climate change. [ABSTRACT FROM AUTHOR]

The study of the ecological effects of the Sloping land conversion program (SLCP) has great significance for afforestation optimization policies based on cost-effectiveness. This paper uses the panel fixed effect model and the panel threshold model to study the ecological effects of fiscal investments in the SLCP at the county level in Shaanxi Province of China. The regional ecological performance indicated by the normalized difference vegetation index (NDVI) has improved after the implementation of the SLCP, but the vegetation suffers degradation risks due to the cessation of subsidies. The results demonstrate strong support for a time lag effect, an effect of diminishing marginal returns, and a threshold effect whereas a significant but negative direct effect of SLCP's fiscal investments on the vegetation. Specifically, it takes approximately four years after fiscal investments for the NDVI to realize the greatest investment performance. The marginal contribution of fiscal investments to ecological performance reveals an increasing trend initially, followed by a decreasing trend. In addition, the ecological effects of fiscal investments in the SLCP are moderated negatively by ecological endowments. The results indicate that fiscal investments in the SLCP should consider its cost-effectiveness in policy design and improvements. [ABSTRACT FROM AUTHOR]

Resource depletion, land-use change, and population growth triggered by the industrial revolution represent serious issues shared globally that have altered the structure, processes, and functions of ecosystems and had significant impacts on human well-being and survival security. This paper assesses changes in ecosystem service values (ESVs) in karst areas based on the perspective of land-use change. Guizhou province, which is typical of the South China Karst (SCK) ecologically fragile areas, was taken as a research subject. The past, current, and future spatial-temporal evolution of karst ESVs were assessed, using equivalence factors and CA-Markov modelling methods. The results show that: (1) from 1980 to 2040, arable land, woodland, and grassland occupy the main land types in the study area; at the same time, the water and built-up areas show a steady growth trend, with dramatic land use shifts occurring in the western, middle, and northern parts. (2) The overall ESVs increased by US$ 31.12 million during the study period, showing a temporal change trend of first decreasing and then increasing; forest land, grassland, and arable land area shift are the main factors of ESVs change; soil conservation, biodiversity conservation, and gas regulation functions are enhanced and play a vital role in the single ESVs increase; ESVs show a basin-type spatial distribution pattern. (3) The sensitivity index is <1, the ESV is inelastic to the VC factor adjustment, and the results are true and valid. This paper found that using quantitative methods to predict land use change of the South China Karst can provide accurate assessment of the differences in supply and demand for natural and social ecosystem services (ES) in a region, clarifying the trade-offs and synergies of ecosystem service functions, contributing to the achievement of sustainable development, and providing a practical reference for global land landscape optimization and land resource planners. [ABSTRACT FROM AUTHOR]

The forestry industry is a low-carbon green industry with great potential for development, but its current development model is facing multiple dilemmas that urgently require a shift to high-quality forestry development. Neoclassical theory and endogenous growth theory consider technology innovation as the foundation of economic growth. In order to explore the impact of forestry technology innovation (FTI) on the economic growth of forestry industry, this paper uses the entropy method, spatial Durbin model, and threshold model to explore the spatial effect of forestry technology innovation on forestry industry economy for analysis and exploration of the non-linear relationship between the two, and the panel data from 31 provinces in China from 2002 to 2020 are used as the sample for empirical study. Results show that: (1) Forestry technology innovation has a significant role in promoting the economic growth of the forestry industry and has obvious spatial spillover effects, which also promotes the economic growth of forestry in neighboring regions. (2) There is a threshold effect of forestry technology innovation on the economic growth of the forestry industry. When the forestry technology innovation exceeds its optimal interval, its effect on the economic growth of forestry industry shows diminishing marginal benefits. (3) Forestry technology innovation has industrial heterogeneity on the economic growth of the forestry industry. Therefore, managers should take advantage of the growth effect of forestry technology innovation in the forestry industry at the level of sustainability, and further make full use of the spatial effect resulting from the flow of technology to establish a system of communication and learning to form a virtuous coordination of the forestry economic environment for the high-quality development of the forestry industry. [ABSTRACT FROM AUTHOR]

This paper adopts the super-efficient DEA (data envelopment analysis) model to measure the forestry eco-efficiency (FECO) of 30 Chinese provinces and cities from 2008 to 2021, and then introduces the Tobit model to explore the influencing factors of FECO to better understand the sustainable development level of forestry. It draws the following conclusions: (1) The average value of FECO in China is 0.504, which is still at a low level, and the FECO of each region has significant regional heterogeneity; the provinces with higher FECO are mainly concentrated in the eastern region, while the FECO of the central and western regions is lower; (2) In terms of the main factors affecting FECO in China, the regression coefficients of market-based environmental regulations are significantly positive in the national, eastern and central regions, while they are significantly negative in the western region. The coefficient of impact of scientific research funding investment on forestry industry eco-efficiency is negative and shows a significant promotion effect in the eastern region, but the elasticity coefficient in the central and western regions is negative but not significant. Economic development has a positive but insignificant effect on FECO, with the eastern region showing a positive correlation, while the central and western regions are insignificant. Industrial structure has a significant negative effect on FECO in the national, eastern and central regions, but the effect of industrial structure on FECO in the western region is not significant. The effect of foreign direct investment on FECO was negative for the national, central and western regions, but the central region did not pass the significance test, while the eastern region reflected a significant promotion effect. [ABSTRACT FROM AUTHOR]

Sensory perception of forests is closely related to human health and well-being. Based on attention recovery theory and stress relief theory, this paper investigates the influence of sensory perception of forests on visitors' restoration effects from a multidimensional and multisensory perspective, integrating the use of a generative large language model, regression analysis, and semantic analysis. The results of the study show that (1) the application of a generative large language model provides new ideas and methods to solve the dilemma caused by the traditional self-report scale measurement and provides a possible way to explore a new research paradigm in the context of the rapid development of generative artificial intelligence; (2) the effects of each sensory quantity differed, with the sensory quantities of sight, hearing, touch, and taste having a significant positive effect on visitors' restoration effects, and the sense of smell having a significant negative effect on visitors' restoration effects; (3) sensory psychological distance partially had a significant effect on visitors' restoration effects, both proximal psychological distance and distal psychological distance were significantly correlated with visitors' restoration effects, and intermediate psychological distance had a negative effect on visitors' restoration effects, but the effect was not significant; (4) the sensory dimension has a significant positive effect on visitors' restoration effects, the integration and synergistic effect of the senses are enhanced, and multidimensional sensory cross-perception has a positive effect on visitors' restoration effects at the social health level; and (5) the sensory elements of National Forest Parks that influence visitors' restoration effects are mainly natural attributes, and the elements related to "people" also play an important role in visitors' restoration effects. This study provides a useful complement to the study of forest sensory perception, and at the same time has an important reference value for exploring the management of forest recreation experience and sensory marketing practices. [ABSTRACT FROM AUTHOR]

Forestry's high-quality development is crucial for China's sustainable ecological, economic, and social progress. To elevate the efficiency of carbon sequestration in forestry, continuously improve the increment of carbon sinks, and contribute to achieving carbon neutrality, it is crucial to accurately assess the level of carbon sequestration efficiency in China's forestry and explore its long-term evolution trend. In this paper, a super-efficiency SBM model, which combines the SBM model with the super-efficiency method and considers the relaxation variables, was selected to evaluate the forestry carbon sequestration efficiency of 31 provinces in China; likewise, the temporal development features of the efficacy of Chinese forests in sequestering carbon were examined using the nuclear density estimation method. Secondly, the study constructed traditional and spatial Markov probability transfer matrices to further explore the spatiotemporal evolution of carbon sequestration efficiency within Chinese forestry. Finally, combined with the Markov chain infinite distribution matrix, the future trajectory of carbon sequestration efficiency in China's forestry was scientifically forecasted. The findings indicate that: (1) The average carbon sequestration efficiency of forestry in China showed a stable increase with fluctuations and reached the optimal state in 2018. The carbon sequestration efficiency level of various forest regions was always portrayed as southwest forest region > southern forest region > northeast forest region > northern forest region. From 2003 to 2018, there were significant differences in forestry carbon sequestration efficiency among provinces. The distribution of forestry carbon sequestration efficiency exhibited a "three-pillar" distribution pattern with Xizang, Zhejiang, and Heilongjiang as the core, and the marginal regions continuously promoted the carbon sequestration efficiency to the inland. (2) The type of transfer of forestry carbon sequestration efficiency in China is stable, and it is difficult to achieve cross-stage transfer in the short term. Moreover, the forestry carbon sequestration efficiency of each province tended to converge to a high (low) level over time, showing a "bimodal distribution" of low efficiency and high efficiency, indicating the existence of the obvious "club convergence phenomenon". (3) Forecasting from a long-term evolution trend perspective, the outlook for the future evolution of forestry carbon sequestration efficiency in China is optimistic, and the overall trend was concentrated in the high-value area. Therefore, future forestry development in China should contemplate both internal structure optimization and coordinated regional development. Attention should be placed on forestry carbon sequestration's role while considering the distinctive endowments of each region and developing reasonable, differentiated, and collaborative forestry management strategies. [ABSTRACT FROM AUTHOR]

This paper investigates the changes in species diversity and the spatial pattern of the population of a moso bamboo (Phyllostachys edulis) forest community in the Wuyi Mountain Nature Reserve in Fujian Province, China. Using the method of space–time substitution, the composition of species and changes in the spatial patterns of different communities were analyzed by taking Phyllostachys edulis mixed forests after 0, 3, 5, 10, 15, and 40 years of enclosure as the survey object. The results showed that as the number of years of enclosure extended, the important values of the Japanese bay tree (Machilus thunbergii Sieb. & Zucc.), chinquapin (Castanopsis faberi Hance), and Masson's pine (Pinus massoniana Lamb.) increased continuously. These trees became the dominant species of mature forest after 40 years of enclosure. The species diversity of mature and young trees in the community generally increased in parallel with the years of enclosure, and the species diversity of the shrubs generally increased first and then decreased as the number of years of enclosure increased. With the extension of enclosure years, the average diameter at breast height of the mature trees tended to increase, indicating that there were increasing advantages of mature growth as the time of enclosure increased. With the extension of enclosure years, the pattern of spatial distribution of the mature trees in the forest community was generally an aggregated distribution. The Phyllostachys edulis forest community under the prolonged enclosure conditions responded in a positive direction and ultimately formed a more stable Phyllostachys edulis mixed forest community. [ABSTRACT FROM AUTHOR]

Forest aboveground biomass (AGB) retrieval using synthetic aperture radar (SAR) backscatter has received extensive attention. The water cloud model (WCM), because of its simplicity and physical significance, has been one of the most commonly used models for estimating forest AGB using SAR backscatter. Nevertheless, forest AGB estimation using the WCM is usually based on simplified assumptions and empirical fitting, leading to results that tend to overestimate or underestimate. Moreover, the physical connection between the model and the polarimetric synthetic aperture radar (PolSAR) is not established, which leads to the limitation of the inversion scale. In this paper, based on the fully polarimetric SAR data from the Advanced Land Observing Satellite-2 (ALOS-2) Phased Array-type L-band Synthetic Aperture Radar (PALSAR-2), the relative contributions of the three major scattering mechanisms were first analyzed in a hilly area of southern China. On this basis, the traditional WCM was extended by considering the secondary scattering mechanism. Then, to establish the direct relationship between the vegetation scattering mechanism and forest AGB, a new relationship equation between the PolSAR decomposition model and the improved water cloud model (I-WCM) was constructed without the help of external data. Finally, a nonlinear iterative method was used to estimate the forest AGB. The results show that volume scattering is the dominant mechanism, accounting for more than 60%. Double-bounce scattering accounts for the smallest fraction, but still about 10%, which means that the contribution of the double-bounce scattering component is not negligible in forested areas because of the strong penetration capability of the long-wave SAR. The modified method provides a correlation coefficient R2 of 0.665 and a root mean square error (RMSE) of 21.902, which is an improvement of 36.42% compared to the traditional fitting method. Moreover, it enables the extraction of forest parameters at the pix scale using PolSAR data without the need for low-resolution external data and is thus helpful for high-resolution mapping of forest AGB. [ABSTRACT FROM AUTHOR]

The MYB transcription factor family is one of the largest families of plant transcription factors (TFs), and it plays a vital role in the entire process of a plant's growth and development. Well known in China, Eucommia ulmoides (E. ulmoides) produces a form of natural rubber called Eucommia ulmoides gum (EUG). Nevertheless, there is little research on the evolutionary history and expression patterns of its MYBs, as well as on the regulation of EUG by MYB TFs. This research provides a comprehensive description, classification, and potential functional analysis of the EuMYB gene family. A total of 119 MYB members of E. ulmoides were identified based on the whole genome sequencing data, and their gene structure, phylogenetics, chromosome location, conserved motifs, etc., were analyzed. Based on the phylogenetic tree results, EuMYBs could be divided into 35 sub-groups. In addition, chromosomal localization and collinearity analysis revealed the heterogeneous distribution of the MYB family in the E. ulmoides' genome, indicating the expansion of its gene family. Moreover, promoter cis-acting elements showed that the promoter contained abundant light-responsive elements, anaerobic-induction-responsive elements, and abscisic-acid-responsive elements. A co-expression regulatory network between the EUG biosynthesis genes and the EuMYBs was built. Meanwhile, regarding the six EuMYBs with high expression in the gum-forming tissues selected that correlated with the farnesyl diphosphate synthase (FPS1) structural gene, RT-qPCR experiments showed a possible regulatory relationship between EuMYBs and FPS1, which played an important role in EUG biosynthesis. In conclusion, this paper defines a research gap and lays a foundation for further studies on the biological functions of EuMYBs. [ABSTRACT FROM AUTHOR]

Tree peony (Paeonia section Moutan DC.) is a traditional ornamental flower of China, which has thousands of varieties with different flower colors and types after a long history of natural selection and artificial breeding. However, tree peony is a perennial woody plant with a long breeding, and there are still significant challenges to accelerate the process of genetic improvement of important ornamental traits. In this study, a total of sixteen primer pairs with high polymorphism and good universality were selected from the initial pool of 115 SSR markers. The SSR marker set was derived from published papers on the genetic linkage map and association analysis of tree peony. Furthermore, we conducted a genetic diversity and population structure analysis on 322 tree peony cultivars using molecular markers with functional. These SSRs amplified a total of 391 alleles, the average number of different alleles was 5.113 alleles across all loci. The average Shannon's information index, gene diversity and polymorphism information content were 0.842, 0.532, and 0.503 over all loci, respectively. Population genetic diversity analysis indicated that the average expected heterozygosity of the total population was larger than the observed heterozygosity, showing the presence of a certain degree of heterozygous deletion phenomenon. The Japan varieties had the richest diversity with the highest H (0.508) and PIC (0.479) values. The Zhongyuan varieties showed the greatest variation may be related to its longstanding cultivation history. Moreover, the STRUCTURE and principal coordinate analyses indicated that 322 tree peony individuals from five populations were grouped into two clusters. An analysis of molecular variance demonstrated significant genetic diversity among different populations. This research may contribute to the sustainable management, conservation, and utilization of tree peony resources. [ABSTRACT FROM AUTHOR]

Populus euphratica and Tamarix chinensis hold significant importance in wind prevention, sand fixation, and biodiversity conservation. The precise extraction of these species can offer technical assistance for vegetation studies. This paper focuses on the Populus euphratica and Tamarix chinensis located within Daliyabuyi, utilizing PointCNN as the primary research method. After decorrelating and stretching the images, deep learning techniques were applied, successfully distinguishing between various vegetation types, thereby enhancing the precision of vegetation information extraction. On the validation dataset, the PointCNN model showcased a high degree of accuracy, with the respective regular accuracy rates for Populus euphratica and Tamarix chinensis being 92.106% and 91.936%. In comparison to two-dimensional deep learning models, the classification accuracy of the PointCNN model is superior. Additionally, this study extracted individual tree information for the Populus euphratica, such as tree height, crown width, crown area, and crown volume. A comparative analysis with the validation data attested to the accuracy of the extracted results. Furthermore, this research concluded that the batch size and block size in deep learning model training could influence classification outcomes. In summary, compared to 2D deep learning models, the point cloud deep learning approach of the PointCNN model exhibits higher accuracy and reliability in classifying and extracting information for poplars and tamarisks. These research findings offer valuable references and insights for remote sensing image processing and vegetation study domains. [ABSTRACT FROM AUTHOR]

In order to deal with the threat of forest fire to the original forest resources, improve the efficiency of firefighting, and better protect the forest ecological resources in the original forest area. In this paper, the ant colony algorithm is used as the search algorithm for the firefighting path, and the Qiqian Forestry Bureau in the northern primitive forest region of the Great Xing'an Range in Inner Mongolia is taken as the research object to select road entry points with different linear distances from the fire poin. By adjusting the pheromone volatility coefficient, the improved ant colony algorithm can better deal with the off-road firefighting path planning in forest environment. The simulation results show that using the road entry point with linear distance of 24.5 km as the starting point for the path planning of off-road firefighting in the northern the Great Xing'an Range can effectively shorten the path and minimize the loss caused by forest fire. At the same time, it verifies the effectiveness and rationality of the path planning of the improved ant colony algorithm under such environmental conditions. The optimization scheme meets the needs of forest fire fighting in the original forest area, and can play a guiding role in design of the forest fire path planning in the original forest area in the northern Great Xing'an Range of Inner Mongolia and a reference for fire path planning in other forest areas in China. [ABSTRACT FROM AUTHOR]

Forests are threatened globally by deforestation. Forest restoration at the landscape scale can reduce these threats. Ground-based and remote sensing inventories are needed to assess restoration success. Fractional canopy cover estimated from forest algorithms can be used to monitor forest loss, growth, and health via remote sensing. Various studies on the fractional cover of forest have been published. However, none has yet conducted a bibliometric analysis. Bibliometrics provide a detailed examination of a topic, pointing academics to new research possibilities. To the best of the authors' knowledge, this is the first bibliometric study screening publications to assess the incidence of studies of the fractional cover of forests in Web of Science (WoS) and Scopus databases. This research analyses WoS and Scopus publications on the fractional cover of forest dating from 1984 to 2021. The current study uses the Bibliometrix R-package for citation metrics and analysis. The first paper on the fractional cover of forest was published in 1984 and annual publication numbers have risen since 2002. USA and China were the most active countries in the study of fractional cover of forests. A total of 955 documents from 69 countries with multiple languages were retrieved. Vegetation, forestry, and remote sensing were the most discussed topics. Findings suggest more studies on the fractional cover of forests algorithms should be conducted in tropical forest from developing countries. [ABSTRACT FROM AUTHOR]

Mangroves are a key type of protected coastal wetland, with a range of benefits such as protection from wave damage, sand fixation, water purification and ecological tourism. As the academic knowledge of mangroves has gradually increased, the use of remote sensing to monitor their dynamic changes in China has become a hot topic of discussion and has received attention in academic circles. Remote sensing has also provided necessary auxiliary decision-making suggestions and data support for the scientific and rational conservation, restoration and management of mangrove resources. In this paper, we used Landsat satellite series data combined with the normalized difference vegetation index (NDVI) and adaptive threshold partitioning (OTSU method) to monitor mangrove dynamics in coastal China from 1986 to 2021 based on Google Earth Engine (GEE), with three main results. (1) Based on the massive data and efficient computational capability of the GEE platform, we achieved large-scale interannual mangrove distribution extraction. The overall classification accuracy for 2019 exceeded 0.93, and the mangrove distribution extraction effect was good. (2) The total mangrove area and the mean patch size in China showed overall increasing trends, and Guangdong and Guangxi were the top two provinces in China in terms of the largest mangrove area. (3) Except for Dongzhaigang National Nature Reserve, the mangrove areas in other national mangrove reserves mainly showed increasing trends, confirming the effectiveness of the reserves. Data on the spatial structure and area trends of mangroves in China can provide scientific references for mangrove conservation and development, and serve in the further restoration of mangrove ecosystems. [ABSTRACT FROM AUTHOR]

As one of the most serious health issues facing trees, the occurrence of decay and hollowing not only reduces the stability and quality of living trees but also leads to the deterioration of their eco-physiological functions, which creates great challenges to the conservation and sustainable management of forest resources. In recent years, the study of tree decay and hollow rot have attracted more and more attention from scholars at home and abroad. The relevant research results have a great significance for the prevention and control of affected living trees and the conservation and sustainable management of endangered species. However, there is a lack of systematic literature review and an insufficient understanding of research hotspots and trends in this field. This paper selects literature retrieved from the CNKI and Web of Science core databases as data sources, the number of publications, research topics, research status, hot spots, and trends, as well as the main research countries, institutions, and co-cited authors in the field of tree decay are visualized by using bibliometrics software CiteSpace (V.5.8.R3), and the current international research hotspots and development trends in this field were systematically summarized. The results showed that the number of papers in this field at home and abroad showed rapid growth in general, and the number of Chinese papers showed a slow growth after 2009. The number of papers published in English by Chinese authors was more than the number of papers published in Chinese in the field. From 2002 to 2021, the research hotspots in this field are constantly changing. Cluster analysis shows that the main themes of the relevant research are as follows: "Eastern Canada" tree species, "hydraulic vulnerability segmentation", "dead wood management", and "hydraulic safety". The advantages and disadvantages of hollow/dead wood on forest ecosystems were explored from different perspectives, providing a theoretical basis and scientific support for the forest health and sustainable management. The United States dominates the research in this field, while China is a relatively late comer but is catching up fast, and the Chinese Academy of Sciences is the most prolific publisher on this topic in China. The influence of Chinese research in this field on relevant international publications is gradually increasing. In short, the research in this field is still in the phase of rapid development, and both the breadth and depth of quantitative research are increasing. How to accurately diagnose and quantify the internal decay of tree trunks and its relationship with tree death and forest decline under the interference and pressure of climate change and human activities is still a hot and difficult issue in this field. [ABSTRACT FROM AUTHOR]

Pinus massoniana (Lamb.) is an important plantation species in southern China. Accurate measurement of P. massoniana seedling morphological indicators is crucial for accelerating seedling quality assessment. Machine vision, with its objectivity and stability, can replace human eyes in performing these measurements. In this paper, a measurement method for seedling morphological indicators based on Euclidean distance, Laplacian contraction, PointNet++, and 3D reconstruction is proposed. Firstly, multi-angle sequence images of 30 one-year-old P. massoniana seedlings were collected, distorted, and corrected to generate a sparse point cloud through the Structure-from-Motion (SFM) and dense point cloud through the Patch-Based Multiple View Stereo (PMVS). Secondly, a Dense Weighted Semantic Segmentation Model based on PointNet++ was designed, achieving effective segmentation of the P. massoniana seedling point clouds. Finally, a multi-iteration plane method based on Laplacian contraction was proposed. The new skeleton points were refined by minimizing the Euclidean distance, iteratively generating the optimal morphological skeleton, thus facilitating the extraction of morphological indicators. The experimental results demonstrated a good correlation between the machine vision-extracted morphological indicators (including plant height, ground diameter, and height-to-diameter ratio) and manually measured data. The improved PointNet++ model achieved an accuracy of 0.9448 on the training set. The accuracy and Mean Intersection over Union (MIoU) of the test set reached 0.9430 and 0.7872, respectively. These findings can provide reliable technical references for the accurate assessment of P. massoniana seedling quality and the promotion of digital forestry construction. [ABSTRACT FROM AUTHOR]