Search Results (16)

Amid accelerating global nitrogen deposition, China has emerged as the world’s third-largest hotspot after Western Europe and North America. Disentangling how elevated N inputs interact with intensifying precipitation and silvicultural practices is therefore essential for forecasting forest responses to ongoing climate change. Taking advantage of the “canopy-simulated nitrogen deposition” platform in Jigongshan National Nature Reserve, we compared tree-level census data from 2012 and 2022 to quantify decadal shifts in neighborhood competition under seven nitrogen addition and rainfall enhancement regimes. After using ordered-sample clustering to identify eight competitors as the optimal neighborhood size, we applied the Hegyi family of competitive indices (CI, CI1, CI2, mCI, mCI1 and mCI2) to analyze competitive responses at three hierarchical levels: the entire stand, all surviving trees and three dominant species (Quercus acutissima, Quercus variabilis, and Liquidambar formosana). The results indicate: (1) Nitrogen addition and rainfall enhancement did not alter the dominant tree species of the stand, which remained primarily Q. acutissima, Q. variabilis, and L. formosana. (2) The competition indices based on all trees showed an upward trend, whereas those calculated for surviving trees and for dominant species declined markedly (surviving trees p < 0.1, L. formosana CI1 p < 0.05). (3) Although nitrogen addition treatments did not alter overall stand competition intensity, it relieved competitive pressure on surviving trees by suppressing interspecific interactions (CI2 and mCI2); intraspecific competition also weakened, but at a slower rate. (4) Interspecific competition intensity for surviving L. formosana decreased significantly, whereas competition indices for Q. acutissima and Q. variabilis remained statistically unchanged. (5) Nitrogen addition methods (canopy vs. understory) had no significant effect on competition indices, while nitrogen addition intensity exhibited a dose-dependent effect: high nitrogen addition significantly reduced interspecific competition intensity more than low nitrogen addition (p < 0.05). In summary, nitrogen deposition primarily regulates interspecific competition through concentration rather than pathway, providing scientific basis for adaptive management of broad-leaved mixed forests in transitional zones under sustained nitrogen deposition scenarios. Full article

Bamboo, characterized by its high growth speed and short maturation period, occupies 0.875% of the global forest area and significantly contributes to terrestrial carbon cycling. The state of shoot growth can essentially indicate a bamboo forests’ health and productivity. This study explored the potential of backpack laser scanning (BLS) for monitoring the growth of Moso bamboo shoots (Phyllostachys edulis), a key economic species in subtropical China. Initially, the accuracy of BLS in extracting attributes of bamboo and shoots (including diameter at breast height (DBH), height, and real-world coordinates) was validated. An optimized method was developed to address the lower precision of BLS in extracting the DBH for thinner species. Subsequently, this research analyzed the impact of spatial structure and other indicators on shoot emergence stage and growth rate using a random forest model. The results indicate that BLS can accurately extract Moso bamboo and shoot height (RMSE = 0.748 m) even in dense bamboo forests. After optimization, the error in DBH extraction significantly decreased (RMSE = 0.835 cm), with the average planar and elevation errors for Moso bamboo being 0.227 m and 0.132 m, respectively. The main indicators affecting the coordinate error of Moso bamboo were the distance to the start (DS) and the distance to the trajectory (DT). The emergence time of shoots was mainly influenced by the surrounding Moso bamboo quantity, with the leaf area index (LAI) and competition index (CI) positively related to the growth rate of shoots. The importance ranking of spatial structure for the carbon storage of shoots was similar to that of the growth rate of shoots, with both identifying LAI as the most significant indicator. This study has validated the value of BLS in monitoring the growth of shoots, providing a theoretical support for the sustainable management and conservation of bamboo forests. Full article

Background/Objectives: Alzheimer’s disease (AD) is the most common form of dementia and affects approximately 50 million individuals worldwide. Interest in coconut oil (CO) as a potential dietary intervention has surged owing to its substantial medium-chain triglyceride (MCT) content. Therefore, sustaining cognitive function and potentially slowing the progression of AD are crucial. This systematic review and meta-analysis evaluated the effects of CO and its bioactive metabolites on AD and dementia. Methods: The review protocol is registered in PROSPERO (CRD42023450435). Relevant research articles published between January 2015 and June 2023 were systematically searched. Seven studies met the predetermined eligibility criteria. Thematic analysis was utilized to synthesis the data about the qualitative features, while meta-analysis was employed for the quantitative findings. A meta-analysis was conducted to assess the standardized mean difference (SMD) and the corresponding 95% confidence interval (CI). Forest plots were generated using Review Manager 5.3 (RevMan 5.3). Results: The analysis revealed that all studies showed consistent results regarding the effects of CO on cognitive scores, with little variability in the true effects of CO on cognitive scores across the studies included in the meta-analysis. Conclusions: CO improved cognitive scores in patients with AD compared with those in the control group (p < 0.05). The results of this study add to the increasing amount of evidence indicating that MCTs found in CO might be a way to improve abilities and potentially slow the advancement of AD. The findings of this study may encourage the development of targeted dietary strategies and interventions for individuals at risk of or diagnosed with AD. Full article

Forest ecosystems, as the primary component of terrestrial ecosystems, provide essential ecosystem services (ESs) critical for sustainable human development. However, changes in climate and vegetation can alter these forest ESs. Understanding the complex relationships between regional climate, vegetation, and ESs is key to ensuring the sustainable management of forest ESs. Therefore, this study, using Baishanzu National Park as a case example, analyzed the impacts of regional climate and vegetation dynamics (vegetation coverage, forest type, and forest structure) on forest ESs, specifically water yield (WY), soil conservation (SC), net primary productivity (NPP), and habitat quality (HQ). The results indicate that from 2000 to 2020, the forest Composite Index of Ecosystem Services (CIES) in Baishanzu National Park increased. Climate and vegetation dynamics have significant effects on forest ESs. Specifically, changes in WY and SC are primarily influenced by climate change, while changes in NPP and HQ are mainly affected by changes in forest type and structure. Complex trade-offs and synergies exist among different ESs, and the driving mechanisms of climate and vegetation changes on ES variations are also complex, involving both direct and indirect effects, with significant spatial heterogeneity. This study provides important references for the sustainable management and appropriate restoration of regional forest ESs. Full article

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. Full article

Due to the geographical structure of the Eastern Black Sea Region, agricultural activities are carried out in high-sloped areas that should ideally be used solely for forestry purposes. The region is characterized by an intricate intertwining of forested areas, agricultural fields, pasture lands, and residential areas, giving rise to a distinct and unique way of life. Within this framework, forest resources have been constantly under pressure and fragmented. This study, therefore, aims to determine the fragmentation status of forests, particularly due to various anthropogenic activities, such as agricultural activities, using the example of Trabzon Province in the Eastern Black Sea Region of Türkiye. Utilizing Geographic Information Systems (GIS), a comprehensive “forest fragmentation map” was meticulously crafted, drawing upon the land-use plans and cadastral maps specific to the study area. Spatial land metrics were calculated using patch analysis. In the study area, there is a total of 31,153.2 hectares of registered state forests. These forests consist of 423 separate and independent fragments. The average forest fragment size in the area is 73.6 hectares. The smallest fragment measures 0.01 hectares (100 square meters), while the largest one covers an area of 18,002 hectares. The area-weighted average figure index of the forest fragments is 9.4. This study quantified fragmented forests, providing evidence of forest fragmentation due to various anthropogenic activities, primarily agricultural activities. This study also proposed an integrated planning approach for the management of fragmented forests. Full article

Site class is a quantitative indicator used to evaluate site quality. It reflects site conditions, mainly climate, the suitability of soil for tree species and soil fertility. Despite the economic and ecological importance of tree competition and site class in sustainable forest management, there has been little research on its impact on the stump and coarse root biomass allocation within plantations. The stump and coarse roots were divided into five components ((stump disc (SD), stump knot (SK), coarse roots (>10 cm in diameter) (CR1), medium coarse roots (5–10 cm) (CR2) and fine coarse roots (2–5 cm) (CR3)), and the biomass of each component was obtained via the weighing method. It was found that the biomass of SD, CR1, CR2 and CR3 was mainly affected by competition (p ≤ 0.01). In the three site classes, the biomass of CR3 increased significantly with the increase in the competition index (CI) (p < 0.01); the biomass of CR1 decreased gradually. In site V, the biomass of SK, sapwood and heartwood increased significantly with the increase in CI. The results show that competition affects the allocation of stump and coarse root biomass mainly by changing the coarse root biomass. The development of stump knots is greatly influenced by site class. This study provides a reference for solving the competition mechanism underlying larch wood forest development, which will in turn promote more effective utilization of larch wood forests. This study also provides a scientific basis for accurately estimating the belowground biomass and carbon storage of artificial plantation forests. Full article

The conservation and sustainable management of forests across ownership groups of the conterminous USA was assessed using the Montréal Process Criteria and Indicators (C&I) framework using national forest inventory and other data. Sixty-one percent of the forest area in the USA is Privately owned (20% Corporate, 39% Family, and 2% Other Private), 37% is Public (28% Federal, 2% Local, and 7% State), and 2% is within Native American Tribal Reservation boundaries. There are many commonalities across ownership categories, but there are also important differences. A 1.1 million ha yr⁻¹ decrease in Family forestland and a 1.0 million ha yr⁻¹ increase in Corporate forestland (C&I 1.1.a) between 2012 and 2019 are among the main trends with implications for sustainability and influence all other aspects considered through the C&I. The majority of annual timber harvests (C&I 2.d) comes from Corporate (46%) and Family (42%) forestlands. Of the most common species, net growth to removal ratios (C&I 2.d) are less than 1.0 for three species on Tribal forestland, two species on Federal forestlands, and two species on Corporate forestlands. Disturbances (C&I 3.a and 3.b) are relatively common (ranging from 4 to 15% of forestland within an ownership category) across ownership categories with the highest proportion of disturbances being caused by diseases and pests on Federal forestland. Differences in the legal and institutional frameworks across ownership categories (Criterion 7) influence how the forest resources can be managed and how policies, programs, and services can be designed and implemented to help maintain and enhance the flow of forest-based goods and services. This analysis helps illustrate that sustainability is complex, C&I are imperfect, and there are additional elements, such as recreational access and ownership/management objectives, that would be helpful for comparing across ownership categories. But the Montréal Process C&I framework helps elucidate the relative threats among ownership categories, in particular the loss of Family forestland to non-forest uses and the increase in disturbances across most ownership categories, and the relative opportunities across ownership categories, including the sustainable supply of timber from Corporate and Family forestlands and the relatively high tree, and presumably broader, biodiversity especially on Local and Other Private forestlands. Full article

The development of criteria and indicators (C&I) to generate information about the status quo and measure changes in sustainable forest management (SFM) has become ever more important. Forest Europe has developed C&I as a policy instrument to monitor and report about SFM. Forest Europe signatories considered the definition of SFM and related C&I as the most recognized achievements of the process. The results of our survey verify this statement. C&I for SFM are implemented at the national level in half of the Forest Europe signatory countries. C&I have served as a structure and framework for the national derivations. Our results confirm the importance of C&I for monitoring and reporting on the status and trend of forests and forestry in Europe. However, Forest Europe has failed so far to go beyond description toward target-based assessments. This was originally not envisaged for the indicators but is increasingly requested by decision-makers and stakeholders. The future development of indicators for SFM should focus on their appropriateness for the assessment of objectives, goals, or targets, because the ability to monitor the respective national efforts has become a critical tool of international but also national governance. Full article

The forest landscape pattern evolution can reveal the intensity and mode of action of human–land relationships at different times and in different spaces, providing scientific support for regional ecological security, human settlement health, and sustainable development. In this study, we proposed a novel method for analyzing the dynamics of landscape patterns. First, patch density (PD), largest patch index (LPI), landscape shape index (LSI), and contiguity index (CI) were used to identify the types of forest spatial patterns. The frequent sequential pattern mining method was used to detect the frequent subsequences from the time series of landscape pattern types from 1991 to 2020 and further evaluate the forest landscape stability of the Fenhe River Basin in China. The results show that different frequent sequence patterns have conspicuous spatial and temporal differences, which describe the evolution processes and stability changes during a certain period of forest evolution and play an important role in the analysis of forest dynamics. The proportion of the disturbed regions to the total forest area exhibited a downward trend. The long-term evolution pattern indicates that there are many evolution processes and trends in the forest at the same time, showing an aggregation distribution law. Compared with 2016, the forest landscape has become complete in 2020, and the overall stability of the Fenhe River Basin has improved. This study can provide scientific support to land managers and policy implementers and offer a new perspective for studying forest landscape pattern changes and evaluating landscape stability. Full article

Knowledge about forest road networks is essential for sustainable forest management and fire management. The aim of this study was to assess the accuracy of a new hierarchical-hybrid classification tool (HyClass) for mapping paved and unpaved forest roads with LiDAR data. Bare-earth and low-lying vegetation were also identified. For this purpose, a rural landscape (area 70 ha) in northwestern Spain was selected for study, and a road network map was extracted from the cadastral maps as the ground truth data. The HyClass tool is based on a decision tree which integrates segmentation processes at local scale with decision rules. The proposed approach yielded an overall accuracy (OA) of 96.5%, with a confidence interval (CI) of 94.0–97.6%, representing an improvement over pixel-based classification (OA = 87.0%, CI = 83.7–89.8%) using Random Forest (RF). In addition, with the HyClass tool, the classification precision varied significantly after reducing the original point density from 8.7 to 1 point/m${}^2$. The proposed method can provide accurate road mapping to support forest management as an alternative to pixel-based RF classification when the LiDAR point density is higher than 1 point/m${}^2$. Full article

Competition is an essential driving factor that influences forest community sustainability, yet measuring it poses several challenges. To date, the Competition Index (CI) has generally been the tool of choice for quantifying actual competition. In this study, we proposed using the Total Overlap Index (TOI), a CI in which the Area Overlap (AO) index has been adapted and modified to consider the “shading” and “crowding” effects in the vertical dimension. Next, based on six mixed forest plots in Xiaolong Mountain, Gansu, China, we assessed the results to determine the TOI’s evaluation capability. Individual-tree simulation results showed that compared to the modified Area Overlap index (AO_M), the TOI has superior quantification capability in the vertical direction. The results of the basal area increment (BAI) model showed that the TOI offers the best evaluation capability among the four considered CIs in mixed forest (with Akaike Information Criterion (AIC) of 1041.60 and log-likelihood (LL) of −511.80 in the model fitting test, mean relative error of −28.67%, mean absolute percent error of 117.11%, and root mean square error of 0.7993 in cross-validation). Finally, the TOI was applied in the Kaplan–Meier survival analysis and Cox proportional-hazards analysis. The Kaplan–Meier survival analysis showed a significant difference between the low- (consisting of trees with the TOI lower than 1) and high-competition (consisting of trees with the TOI higher than 1) groups’ survival and hazard curves. Moreover, the results of the Cox proportional-hazards analysis exhibited that the trees in the low-competition group only suffered 34.29% of the hazard risk that trees in the high-competition group suffered. Overall, the TOI expresses more dimensional information than other CIs and appears to be an effective competition index for evaluating individual tree competition. Thus, the competition status quantified using this method may provide new information to guide policy- and decision-makers in sustainable forest management planning projects. Full article

Sustainable forest management increasingly highlights the maintenance of biological diversity and requires up-to-date information on the occurrence and distribution of key ecological features in forest environments. European aspen (Populus tremula L.) is one key feature in boreal forests contributing significantly to the biological diversity of boreal forest landscapes. However, due to their sparse and scattered occurrence in northern Europe, the explicit spatial data on aspen remain scarce and incomprehensive, which hampers biodiversity management and conservation efforts. Our objective was to study tree-level discrimination of aspen from other common species in northern boreal forests using airborne high-resolution hyperspectral and airborne laser scanning (ALS) data. The study contained multiple spatial analyses: First, we assessed the role of different spectral wavelengths (455–2500 nm), principal component analysis, and vegetation indices (VI) in tree species classification using two machine learning classifiers—support vector machine (SVM) and random forest (RF). Second, we tested the effect of feature selection for best classification accuracy achievable and third, we identified the most important spectral features to discriminate aspen from the other common tree species. SVM outperformed the RF model, resulting in the highest overall accuracy (OA) of 84% and Kappa value (0.74). The used feature set affected SVM performance little, but for RF, principal component analysis was the best. The most important common VI for deciduous trees contained Conifer Index (CI), Cellulose Absorption Index (CAI), Plant Stress Index 3 (PSI3), and Vogelmann Index 1 (VOG1), whereas Green Ratio (GR), Red Edge Inflection Point (REIP), and Red Well Position (RWP) were specific for aspen. Normalized Difference Red Edge Index (NDRE) and Modified Normalized Difference Index (MND705) were important for coniferous trees. The most important wavelengths for discriminating aspen from other species included reflectance bands of red edge range (724–727 nm) and shortwave infrared (1520–1564 nm and 1684–1706 nm). The highest classification accuracy of 92% (F1-score) for aspen was achieved using the SVM model with mean reflectance values combined with VI, which provides a possibility to produce a spatially explicit map of aspen occurrence that can contribute to biodiversity management and conservation efforts in boreal forests. Full article

Growing concern about forest degradation and loss, combined with the political impetus supplied by the Earth Summit in 1992, led to the establishment of eleven intergovernmental, regional, and international forest-related processes focused on the use of criteria and indicators (C&I) for sustainable forest management (SFM). Up to 171 countries have participated in these processes to apply C&I frameworks as a tool for data collection, monitoring, assessment, and reporting on SFM and on achieving various forest-related UN Sustainable Development Goals. Based on an expert survey and literature analysis we identify six interlinked impact domains of C&I efforts: (1) enhanced discourse and understanding of SFM; (2) shaped and focused engagement of science in SFM; (3) improved monitoring and reporting on SFM to facilitate transparency and evidence-based decision-making; (4) strengthened forest management practices; (5) facilitated assessment of progress towards SFM goals; and (6) improved forest-related dialog and communication. We conclude that the 25-year history of C&I work in forestry has had significant positive impacts, though challenges do remain for the implementation of C&I and progress towards SFM. The work should be continued and carried over to other sectors to advance sustainability goals more broadly. Full article

The use of criteria and indicators (C&I) for data collection, monitoring, assessing and reporting on sustainable forest management (SFM) has been growing since the Earth Summit in 1992, supported by eleven intergovernmental, regional and international forest-related C&I processes. The initial effort led to varying levels of implementation across countries. Several processes never went much beyond the adoption of a first set of C&I while others have made substantial progress. In recent years, interest in C&I for SFM has again increased. In light of the Sustainable Development Goals and emerging global challenges the contribution of C&I to monitor, assess and report on forest conditions and trends is increasingly important. We compare and analyse the structure, activities and progress of the intergovernmental C&I processes. The work is based on document analysis and questionnaires sent to the secretariats of the processes and C&I experts. We found many similarities but also major differences in the structure and content of the C&I sets. The results provide a context for discussing and understanding why some of the C&I processes are successful in their work while others have stalled. Finally, we propose the required ingredients for success for the future activities of the forest-related intergovernmental C&I processes. Full article