ALBERT

Description: A total of 344 soil cores were taken in annually cropped fields of Alberta, Saskatchewan, Manitoba, and Ontario from 2011 to 2013 in areas where the field shapes, or obstacles within fields, required the driving pattern of farm operations to overlap. Soil nitrate-N concentrations in overlapping areas were 60% greater, soil Olsen-P concentrations were 23% greater, and pH was 0.5 units greater at 0–15 cm depth compared with non-overlapping areas, suggesting smaller nutrient use efficiency and potential for greater nutrient loss.

Description: Differences in soil water retention (SWR) characteristics between soil types and the factors driving those differences provide important information for land management, particularly in regions such as the Colombian Andes, which have limited water-storage infrastructure and where soils provide plant-available water and other ecosystem services. The objective of this study was to explore relationships between SWR and physical, chemical, and mineralogical properties of Andisols and Inceptisols through a case study of two watersheds in the Colombian Andes. This study identified a complex relationship between total carbon (TC), short-range order (SRO) minerals, and SWR. Both soil types had high SWR, with volumetric water content at permanent wilting point between 39% and 53%. Principal component analysis showed association of SWR with TC, SRO minerals, and % clay in both soil types. The Andisols of this study were coarse textured, allophanic (rich in allophane and imogolite — up to 17% in the B horizon), and with up to 15% TC in the A horizon. In contrast, the Inceptisols were fine textured (〉30% clay) and higher in ferrihydrite than the Andisols. The formation of organo-metallic complexes was observed in A horizons; however, TC was lower under pasture than forest in both soil types. The addition of organic matter to soils with SRO minerals, such as the soils of this study, may foster the formation of organo-metallic complexes, stabilize soil C, and enhance SWR. Consequently, both study sites may benefit from management practices that increase soil organic matter.

Description: This study investigated differences in forest structure, organic layer thickness, soil organic carbon, and permafrost depth between late successional (LS) and post fire (PF, 90 to 120 years since burn) plots under black spruce (Picea mariana (Mill.) BSP) on fine-textured, poorly drained lacustrine sediments in the Copper River Basin, Alaska. We found that although live stem and seedling density and organic layer thickness (OLT) was not significantly different between PF and LS plots (28 ± 7 cm and 31 ± 10 cm, respectively), soil organic carbon (SOC) stocks (30 ± 10 kg m-2 and 46 ± 12 kg m-2, respectively), and permafrost depth (90 ± 28 cm and 56 ± 12 cm, respectively) remain significantly different. OLT was linearly related to 1 m SOC stocks for LS plots but not for PF plots, and LS plots had a greater proportion of highly decomposed (humic) material in the organic layer. Soil properties on PF plots appear to be on a trajectory of recovery towards LS plots with respect to SOC stocks, permafrost depth, and organic layer composition, but remain different despite nearly 100 years since fire disturbance and therefore potentially sensitive to changes in future fire frequency or climate.

Description: Global change-driven droughts are triggering worldwide forest dieback which are predicted to increase even further. Here, we combined genome-wide single nucleotide polymorphisms (SNPs) and dendrochronological approaches to assess genetically-based individual tree vulnerability to past extreme droughts that caused massive mortality of Nothofagus dombeyi forests in northern Patagonia. We collected fresh leaves and wood cores from pairs of Healthy Crown (HC) and Partially Affected crown (PA) trees at four sites impacted by 1998, 2008 and 2014 droughts. We used dendrochronological techniques to estimate parameters in terms of growth trends due to drought and genomic analysis to assess its relationship with water stress. While 5,155 neutral loci did not discriminate PA from HC trees, a set of 33 adaptive SNPs did so, 8 of which were related to hydric stress. Association analysis between genomic variants and dendrophenotypic traits yielded 6 SNPs that were associated with a growth measure as resilience to cope with drought. Our preliminary results indicate that susceptibility to drought in N. dombeyi could be determined at the genomic level. The combination of both approaches provides a framework for the identification and analysis of candidate genes for stress response in non-model species.

Description: With the increasingly close relations between cities in China, it is of great significance to explore the regular characteristics of the intercity connection. Through Tencent’s population migration heat and Baidu map big data, this paper analyzes the regular characteristics of the relations between complex cities based on such index as the rich node propensity index, preference level index, and relative heat index and also investigates the influence of geographical proximity factors on the external relations of different cities. The research has the following results. Firstly, the relations between cities have obvious club characteristics. The rich nodes tend to connect with the rich nodes, while the nonrich nodes tend to connect with the nonrich nodes. Secondly, the connection between cities has the effect of hierarchical proximity, and cities mainly establish spatial connections with cities of the same level and adjacent level. Thirdly, the relations between cities also have the effect of geographical proximity, and the degree of influence of geographical proximity in low-level cities is greater than that in high-level cities. Fourthly, the external connection mode of high-level cities is to establish close contact with high-level cities adjacent to the level, with strong attraction to low-level cities adjacent to the location at the same time. The low-level cities are closely related to the high-level cities adjacent to the location and other cities of geographical proximity or adjacent level. This study helps to further understand the complex characteristics and laws of intercity connections and urban networks.

Description: In Nepal, forest management priority is shifting to scientific management from conventional management. Though, the forest officials claims that scientific management is beneficial to the forest user groups, comparative financial assessment with conventional management remains unexplored. Following a case study approach, this study compares financial efficiency of two forest management systems in the community forests, focusing on benefit-cost ratio. The study conducted documents review, focus group discussions, and rapid survey to quantify costs and benefits from each forest management system. Conventional management gave a higher benefit-cost ratio to the forest user groups, irrespective of whether forest products are sold at a subsidized price or par with the market price. However, scientific management required high forest management costs and thus had a lower benefit-cost ratio. Sensitivity analysis between two systems revealed that conventional management gave a higher benefit-cost ratio in all cases. The study concludes that forest user groups would bear financial loss if they do not fix the price of the timber at par with the market in scientific management, and in such a case, the tagged price will be beyond affordability of the forest users. Furthermore, scientific management has discouraged kind contribution of users in managing forest. Besides, social and environmental consequences of scientific management cannot be ignored. Hence, the study argues for reconsidering current scientific management considering likely economic and social consequences to the forest user groups.

Description: Electroencephalography-(EEG-) based control is a noninvasive technique which employs brain signals to control electrical devices/circuits. Currently, the brain-computer interface (BCI) systems provide two types of signals, raw signals and logic state signals. The latter signals are used to turn on/off the devices. In this paper, the capabilities of BCI systems are explored, and a survey is conducted how to extend and enhance the reliability and accuracy of the BCI systems. A structured overview was provided which consists of the data acquisition, feature extraction, and classification algorithm methods used by different researchers in the past few years. Some classification algorithms for EEG-based BCI systems are adaptive classifiers, tensor classifiers, transfer learning approach, and deep learning, as well as some miscellaneous techniques. Based on our assessment, we generally concluded that, through adaptive classifiers, accurate results are acquired as compared to the static classification techniques. Deep learning techniques were developed to achieve the desired objectives and their real-time implementation as compared to other algorithms.

Description: As the externalized carrier of intrinsic value, value decision-making is an important factor affecting the social value system. As an old Chinese saying goes, “A friend in need is a friend indeed,” crisis environment provides the background for the conflicts of multiple values, while individual social value orientation (SVO) determines the ranking of the value states. This paper defined the SVO types by means of Slider Measure method on the basis of environment description, constructed a decision-making game model in accordance with SVO differences, and finally analysed the mechanism of people’s decision-making. Taking the epidemic situation as the background, this paper conducted an empirical analysis with the sample of college students. The results showed that the most SVO types of college students were prosocial orientation, followed by individualistic orientation, altruistic orientation, and competitive orientation. In the crisis environment, individual SVO type and decision-making constituted a mapping relationship. There was an equilibrium point in the decision of prosocial orientation, and the dominant decision of altruistic orientation or individualistic orientation is relatively stable.

Description: To solve the problems of current short-term forecasting methods for metro passenger flow, such as unclear influencing factors, low accuracy, and high time-space complexity, a method for metro passenger flow based on ST-LightGBM after considering transfer passenger flow is proposed. Firstly, using historical data as the training set to transform the problem into a data-driven multi-input single-output regression prediction problem, the problem of the short-term prediction of metro passenger flow is formalized and the difficulties of the problem are identified. Secondly, we extract the candidate temporal and spatial features that may affect passenger flow at a metro station from passenger travel data based on the spatial transfer and spatial similarity of passenger flow. Thirdly, we use a maximal information coefficient (MIC) feature selection algorithm to select the significant impact features as the input. Finally, a short-term forecasting model for metro passenger flow based on the light gradient boosting machine (LightGBM) model is established. Taking transfer passenger flow into account, this method has a low space-time cost and high accuracy. The experimental results on the dataset of Lianban metro station in Xiamen city show that the proposed method obtains higher prediction accuracy than SARIMA, SVR, and BP network.

Description: People are the most important factors of economy and the primary carriers of social culture. Cross-border migration brings economic and cultural impacts to the origin and destination and is also a key to reflect the international relations of related countries. In fact, the migration relationships of countries are complex and multilateral, but most traditional migration models are bilateral. Network theories could provide a better description of global migration to show the structure and statistical characteristics more clearly. Based on the estimated migration data and disparity filter algorithm, the networks describing the global multilateral migration relationships have been extracted among 200 countries over fifty years. The results show that the global migration networks during 1960–2015 exhibit a clustering and disassortative feature, implying globalized and multipolarized changes of migration during these years. The networks were embed into a Poincaré disk, yielding a typical and hierarchical “core-periphery” structure, which is associated with angular density distribution, and has been used to describe the “multicentering” trend since 1990s. Analysis on correlation and evolution of communities indicates the stability of most communities, yet some structural changes still exist since 1990s, which reflect that the important historical events are contributable to regional and even global migration patterns.

Description: Most of the existing knowledge graph embedding models are supervised methods and largely relying on the quality and quantity of obtainable labelled training data. The cost of obtaining high quality triples is high and the data sources are facing a serious problem of data sparsity, which may result in insufficient training of long-tail entities. However, unstructured text encoding entities and relational knowledge can be obtained anywhere in large quantities. Word vectors of entity names estimated from the unlabelled raw text using natural language model encode syntax and semantic properties of entities. Yet since these feature vectors are estimated through minimizing prediction error on unsupervised entity names, they may not be the best for knowledge graphs. We propose a two-phase approach to adapt unsupervised entity name embeddings to a knowledge graph subspace and jointly learn the adaptive matrix and knowledge representation. Experiments on Freebase show that our method can rely less on the labelled data and outperforms the baselines when the labelled data is relatively less. Especially, it is applicable to zero-shot scenario.

Description: Portfolio investment is adopted by the venture capital to diversify those risks involved in project selection, investing or operating so that the venture capitalist can expect a relatively stable income and lower financing risks. Based on the design of portfolio investment contract with unlimited funds developed by Kanniainen and Keuschnigg, and Inderst et al., this article makes a modification and presents a model given the limitation of funds available for the venture capitalist. It is demonstrated that the marginal benefit of efforts paid by the entrepreneurs exceeds the marginal cost, given the limitation of funds available, which will conduce to a high-level engagement of the entrepreneurs. Thus, by adopting the design of renegotiation contract, the venture capitalist can manage to stimulate the entrepreneurs to make efforts, which is to result in moral hazard reduction.

Description: Huge data on the web come from discussion forums, which contain millions of threads. Discussion threads are a valuable source of knowledge for Internet users, as they have information about numerous topics. The discussion thread related to single topic comprises a huge number of reply posts, which makes it hard for the forum users to scan all the replies and determine the most relevant replies in the thread. At the same time, it is also hard for the forum users to manually summarize the bulk of reply posts in order to get the gist of discussion thread. Thus, automatically extracting the most relevant replies from discussion thread and combining them to form a summary are a challenging task. With this motivation behind, this study has proposed a sentence embedding based clustering approach for discussion thread summarization. The proposed approach works in the following fashion: At first, word2vec model is employed to represent reply sentences in the discussion thread through sentence embeddings/sentence vectors. Next, K-medoid clustering algorithm is applied to group semantically similar reply sentences in order to reduce the overlapping reply sentences. Finally, different quality text features are utilized to rank the reply sentences in different clusters, and then the high-ranked reply sentences are picked out from all clusters to form the thread summary. Two standard forum datasets are used to assess the effectiveness of the suggested approach. Empirical results confirm that the proposed sentence based clustering approach performed superior in comparison to other summarization methods in the context of mean precision, recall, and F-measure.

Description: This paper considers the two-player location game in a closed-loop market with quantity competition. Based on the Cournot and Hotelling models, a circle model is established for a closed-loop market in which two players (firms) play a location game under quantity competition. Using a two-stage (location-then-quantity) pattern and backward induction method, the existence of subgame-perfect Nash equilibria is proved for the location game in the circle model with a minimum distance transportation cost function. In addition, sales strategies are proposed for the two players for every local market on the circle when the players are in the equilibrium positions. Finally, an algorithm for simulating the competitive dynamics of the closed-loop market is designed, and two numerical simulations are provided to substantiate the effectiveness of the obtained results.

Description: A novel posture motion-based spatiotemporal fused graph convolutional network (PM-STGCN) is presented for skeleton-based action recognition. Existing methods on skeleton-based action recognition focus on independently calculating the joint information in single frame and motion information of joints between adjacent frames from the human body skeleton structure and then combine the classification results. However, that does not take into consideration of the complicated temporal and spatial relationship of the human body action sequence, so they are not very efficient in distinguishing similar actions. In this work, we enhance the ability of distinguishing similar actions by focusing on spatiotemporal fusion and adaptive feature extraction for high discrimination information. Firstly, the local posture motion-based attention (LPM-TAM) module is proposed for the purpose of suppressing the skeleton sequence data with a low amount of motion in the temporal domain, and the representation of motion posture features is concentrated. Besides, the local posture motion-based channel attention module (LPM-CAM) is introduced to make use of the strongly discriminative representation between different action classes of similarity. Finally, the posture motion-based spatiotemporal fusion (PM-STF) module is constructed which fuses the spatiotemporal skeleton data by filtering out the low-information sequence and enhances the posture motion features adaptively with high discrimination. Extensive experiments have been conducted, and the results demonstrate that the proposed model is superior to the commonly used action recognition methods. The designed human-robot interaction system based on action recognition has competitive performance compared with the speech interaction system.

Description: In this paper, a delayed control strategy for a class of nonlinear underactuated fourth-order systems is developed. The proposal is based on the implementation of the tangent linearization technique, differential flatness, and a study of the σ-stabilization of the characteristic equation of the closed-loop system. The tangent linearization technique allows obtaining a local controllability property for the analyzed class of systems. Also, it can reduce the complexity of the global control design, through the use of a cascade connection of two second-order controllers instead of designing a global controller of the fourth-order system. The stabilizing behavior of the delayed controller design is supported by the σ-stability criterion, which provides the controller parameter selection to reach the maximum exponential decay rate on the system response. To illustrate the efficiency of the theoretical results, the proposal is experimentally assessed in two cases of study: a flexible joint system and a pendubot.

Description: Recently, knowledge graph embedding methods have attracted numerous researchers’ interest due to their outstanding effectiveness and robustness in knowledge representation. However, there are still some limitations in the existing methods. On the one hand, translation-based representation models focus on conceiving translation principles to represent knowledge from a global perspective, while they fail to learn various types of relational facts discriminatively. It is prone to make the entity congestion of complex relational facts in the embedding space reducing the precision of representation vectors associating with entities. On the other hand, parallel subgraphs extracted from the original graph are used to learn local relational facts discriminatively. However, it probably causes the relational fact damage of the original knowledge graph to some degree during the subgraph extraction. Thus, previous methods are unable to learn local and global knowledge representation uniformly. To that end, we propose a multiview translation learning model, named MvTransE, which learns relational facts from global-view and local-view perspectives, respectively. Specifically, we first construct multiple parallel subgraphs from an original knowledge graph by considering entity semantic and structural features simultaneously. Then, we embed the original graph and construct subgraphs into the corresponding global and local feature spaces. Finally, we propose a multiview fusion strategy to integrate multiview representations of relational facts. Extensive experiments on four public datasets demonstrate the superiority of our model in knowledge graph representation tasks compared to state-of-the-art methods.

Description: A multimode resource-constrained project scheduling problem (MRCPSP) may have multifeasible solutions, due to its nature of targeting multiobjectives. Given the NP-hard MRCPSP and intricate multiobjective algorithms, finding the optimized result among those solutions seems impossible. This paper adopts data envelopment analysis (DEA) to evaluate a series of solutions of an MRCPSP and to find an appropriate choice in an objective way. Our approach is applied to a typical MRCPSP in practice, and the results validate that DEA is an effective and objective method for MRCPSP solution selection.

Description: Based on the oligopoly game theory and the intellectual property rights protection policy, we investigate the complex dynamical behaviors of a mixed duopoly game with quadratic cost. In the new system, a few parameters are improved by considering intellectual property rights protection and the stability conditions of the Nash equilibrium point are discussed in detail. A set of the two-dimensional bifurcation diagrams is demonstrated by using numerical modeling, and these diagrams show abundant complex dynamical behaviors, such as coexistence of attractors, different bifurcation, and fractal structures. These dynamical properties can present the long-run effects of strengthening intellectual property protection.

Description: Implementing artificial neural networks is commonly achieved via high-level programming languages such as Python and easy-to-use deep learning libraries such as Keras. These software libraries come preloaded with a variety of network architectures, provide autodifferentiation, and support GPUs for fast and efficient computation. As a result, a deep learning practitioner will favor training a neural network model in Python, where these tools are readily available. However, many large-scale scientific computation projects are written in Fortran, making it difficult to integrate with modern deep learning methods. To alleviate this problem, we introduce a software library, the Fortran-Keras Bridge (FKB). This two-way bridge connects environments where deep learning resources are plentiful with those where they are scarce. The paper describes several unique features offered by FKB, such as customizable layers, loss functions, and network ensembles. The paper concludes with a case study that applies FKB to address open questions about the robustness of an experimental approach to global climate simulation, in which subgrid physics are outsourced to deep neural network emulators. In this context, FKB enables a hyperparameter search of one hundred plus candidate models of subgrid cloud and radiation physics, initially implemented in Keras, to be transferred and used in Fortran. Such a process allows the model’s emergent behavior to be assessed, i.e., when fit imperfections are coupled to explicit planetary-scale fluid dynamics. The results reveal a previously unrecognized strong relationship between offline validation error and online performance, in which the choice of the optimizer proves unexpectedly critical. This in turn reveals many new neural network architectures that produce considerable improvements in climate model stability including some with reduced error, for an especially challenging training dataset.

Description: Social networks are a complex system that members communicate, create new connections or destroy existing connections, and further deliver major impacts on each member’s life. Given the spread of the Internet and increased academic pressure, sedentary and prescreen behaviors are very common among adolescents; meanwhile, sports behaviors are gradually decreasing. This situation has had an adverse effect on health. This paper used a questionnaire survey to investigate the influence of social networks on adolescent sports behavior, including the intermediary role of social efficacy and moderating effect of self-presentation. The questionnaire survey was conducted on 568 students from 6 high schools in Shaanxi, Henan, and Shandong Provinces. After this, factor analysis and weighted least squares method were used for the empirical test. Based on theoretical and empirical analysis, this paper found the following: (1) Social networks of adolescents have obvious positive predictive effects on their sports behavior. A single online social network and an offline social network, instrumental network, emotional network, and mixed network have obvious positive predictive effects on adolescent sports behaviors. However, under the influence of multiple types of social networks, an offline social network has a negative predictive effect, while a mixed network has effects that are not as obvious. (2) Social efficacy plays an intermediary role in the relationship between social network and adolescent sports behavior. (3) The moderating effect of self-presentation is not significant.

Description: Forest biomass is an important ecological indicator for the sustainable management of forests. The aim of this study was to estimate forest aboveground biomass (AGB) by integrating SPOT-6 data with field-based measurements using the random forest (RF) algorithm. In total, 52 remote sensing variables, including spectral bands, vegetation indices, topography data, and textures, were extracted from SPOT-6 images to predict the forest AGB of Xuan Lien Nature Reserve, Vietnam. To determine the optimal predictor variables for AGB estimation, 10 different RF models were built. To evaluate these models, 10-fold cross-validation was applied. We found that a combination of spectral and vegetation indices and topography variables offer the highest prediction results (Radj2  = 0.74 and RMSE = 61.24 Mg ha−1). Adding texture features into the predictor variables did not improve the model performance. In addition, the SPOT-6 sensor has the potential to predict forest AGB using the RF algorithm.

Description: Agroecology was born as a competing theory to sciences derived from the Green Revolution like conventional agronomy or modernized animal husbandry. In recent years, several theoretical models or approaches have been developed in order to explain this science. However, any of them can explain its change or difference with its rival theories in a rational manner that allows assessment of its success. As a result, the aim of this study was to propose a rational model of scientific change based on main and auxiliary hypotheses. We found that seven basic principles have been formulated throughout theoretical books and papers as well as several auxiliary hypotheses that can be derived from them. These principles are as follows: (1) characteristic systemic principle of agroecology, (2) principle of biomimicry, (3) principle of biodiversity, (4) principle of specificity of agroecosystems, (5) principle of governance, (6) principle of socioecological resilience, and (7) principle of vulnerability. Also, three principles for food systems approach were retrieved. This model shows agroecology more like an organic theory that moves in different scales than a set of rival theories competing for success. However, a proper articulation and discussion of these basic principles is yet to be done.

Description: Background and Aims. An excessive and prolonged use of fertilizers undermines soils’ quality and, consequently, that of the crops they support, thus reducing the content of organic matter and generating environmental damages and problems to human health. Therefore, the use of biofertilizers such as cyanobacteria becomes a promising alternative. However, it is not always possible to generalize these fertilizers’ applicability, because microorganisms may be impacted by the physical and chemical variations of their environment. We will describe the action mechanisms or the characteristics of cyanobacteria involved in plant growth promotion for different crops in situ through a systematic review of scientific literature. Methods. A comprehensive search for original articles in two different databases, ScienceDirect and Scopus, was performed. We included in our search documents published from 2009 to 2018. After the screening process and the addition of gray literature publications, we obtained 23 articles for theoretical analysis. Results. The studies were distributed mainly in Asia and part of Africa, without any important temporal variation. They also showed a tendency to describe the use of cyanobacteria genera such as Anabaena sp., Nostoc sp., and Calothrix sp., besides mechanisms as N2 fixation, phosphate solubilization, phytohormone production, bioactive compounds excretion, and symbiotic associations, mainly on rice, wheat and corn crops. Conclusions. Cyanobacteria fertilizers used in situ are a widespread strategy, mainly in cereal crops. Their use is predominant in countries where cereal crops make an important contribution to their national economy. The great variety of mechanisms and characteristics of cyanobacteria used to promote plant growth in the field demonstrate the dramatic influence that physical, chemical, and biological variables have in their development.

Description: Height measurement for moving pedestrians is quite significant in many scenarios, such as pedestrian positioning, criminal suspect tracking, and virtual reality. Although some existing height measurement methods can detect the height of the static people, it is hard to measure height accurately for moving pedestrians. Considering the height fluctuations in dynamic situation, this paper proposes a real-time height measurement based on the Time-of-Flight (TOF) camera. Depth images in a continuous sequence are addressed to obtain the real-time height of the pedestrian with moving. Firstly, a normalization equation is presented to convert the depth image into the grey image for a lower time cost and better performance. Secondly, a difference-particle swarm optimization (D-PSO) algorithm is proposed to remove the complex background and reduce the noises. Thirdly, a segmentation algorithm based on the maximally stable extremal regions (MSERs) is introduced to extract the pedestrian head region. Then, a novel multilayer iterative average algorithm (MLIA) is developed for obtaining the height of dynamic pedestrians. Finally, Kalman filtering is used to improve the measurement accuracy by combining the current measurement and the height at the last moment. In addition, the VICON system is adopted as the ground truth to verify the proposed method, and the result shows that our method can accurately measure the real-time height of moving pedestrians.

Description: Empirical evidence shows complementarity between maize and soybean as a sustained agricultural system across North and South America as well as Eastern Europe. The potential application to sub-Saharan Africa motivates this literature review. Maize is one of the most important crops on the African subcontinent, accounting for over half of daily caloric intake in some regions. However, continuous cropping of maize has led to extensive degradation of soil and decrease in crop productivity and endangers household food and nutritional security. The cultivation of soybean holds great promise in improving agricultural systems in sub-Saharan Africa. Introducing soy into rotation with maize is a method to diversify diets, better nutritional status, reduce abiotic and biotic stresses, and improve soil fertility, while enhancing crop productivity and generating more income for farmers. However, limited access to extension services and other sources of technical support constrains adoption of the more complex rotation cropping system involving a new crop, soybean. Rotating soybean with maize too challenges farmers as there is not a specific prescription that can guide farmers operating across Africa’s diverse agroecological environments. Finally, soybean is an input-intensive crop requiring significant investment at planting, which may not allow small holders with limited resources and no access to credit.

Description: Since China’s first stock index futures, China Securities Index 300 (CSI300) stock index futures were published in 2010, and China’s stock index futures market is now in a period of rapid development and play a key role in price discovery. During 2014 to 2015, China’s stock index futures market fluctuated abnormally, and the overuse of high-frequency trading (HFT) strategies in the stock index futures market was blamed as the main reason of the abnormal volatility. To lower down market fluctuation, the regulatory institute then announced a series of trade restriction policy to prevent the overuse of HFT behaviour. However, until now, the impact of such trade restriction policy for HFT remains uncertain. To tackle this issue, based on minute-level HFT data from the CSI 300 index futures market, this paper aims to investigate the relationship between HFT and the exogenous liquidity risk and how HFT affects China’s stock index futures market on its liquidity using the liquidity-adjusted value at risk (LVaR) model. The findings indicate that HFT improves the return of the liquidity provider and reduces the exogenous liquidity risk significantly.

Description: Community is the core spatial unit for evaluating sustainable development. However, single data and method seem inadequate for conducting a scientific, effective, and innovative sustainable evaluation of complex community units. In this study, we perform a sustainable-oriented land use scheme using multisource remote sensing, machine learning, and object-based postclassification refinement. Furthermore, we assess the sustainability of the traffic community by data-driven and combined housing, ecosystem services, and landscape configuration. The results indicated that (1) the relationship between housing, ecosystem services, and landscape pattern has obvious synergistic effects, although with dissimilar importance in different sustainability levels. High sustainability level is intensely coordinated with landscape configuration, medium sustainability level is more affected by ecosystem services, and low sustainability level is more related to housing. (2) Community sustainability presents a significant spatial distribution. The communities of high sustainability level are mainly located in both sides of the Pearl River and emerging urban areas, while those of medium sustainability level are distributed sporadically in the study area and those of low sustainability level are concentrated in old towns. (3) Community transformation cannot be accomplished at one step. Along with the continuous optimization of landscape configuration, the priority should be given to housing reconstruction and improvement of ecosystem services further. We provide scientific and effective data-based evidence for urban decision-makers by integrating the advantages of the Earth Observation System and multifactor analysis.

Description: A 42-year sequence (1976–2017) of Scots pine tree diameter measurements using band dendrometers at the Aukštaitija National Park (Lithuania) study site was analysed. We have evaluated the intra- and inter annual growth dynamics of tree’s diameters and their response to meteorological forcing, as well as the long-term annual and monthly growth-rate changes in tree diameter in the study area. On average, the largest tree-diameter growth was found to have taken place during the month of June (35% of the annual increase). After June 24, the diameter growth rate decreased very strongly. The pine growth in May and August was mostly affected by the temperature of the previous month. The precipitation amount was the main driver that determined tree growth in June‒August. Heavy precipitation events had the largest impact on short-term tree-diameter increases. As a consequence of air temperature rise, we have determined the largest positive Scots pine tree diameter growth-rate changes in May and June during the period from 1976 to 2017.

Description: Practically, supply disruption may lead production process to entirely halt (completely disrupted) or the output to differ in the order size (partially disrupted), which makes it more difficult for the retailer to satisfy stochastic market demand. Under the circumstance, the retailer is likely to procure products from two suppliers to effectively alleviate the demand-supply mismatches. Thus, under supply disruption and stochastic demand, this paper develops both backup sourcing and simultaneous sourcing (SS) strategies to analyze the retailer’s performance, where backup sourcing includes wholesale price priority (WPP) and supply reliability priority (SRP). Specifically, (1) under WPP, when the selling price is relatively lower (higher), the retailer is suggested to activate the reliable backup supplier after the realization of supply disruption (demand uncertainty). (2) Under SRP, two scenarios including minor disruption and major disruption can be identified, where the retailer’s order quantity from the reliable (unreliable) supplier under minor disruption scenario is more (less) than that under major. (3) Finally, this paper systematically compares the retailer’s preferences among WPP, SRP, and SS via theoretical results and numerical examples. That is, when the unreliable supplier is more likely to work normally or shortage cost (selling price) is relatively lower, the retailer prefers SPR regarding the unreliable supplier as backup sourcing due to its lower wholesale price and acceptable supply disruption. Otherwise, the retailer is inclined to WPP regarding the reliable supplier as backup sourcing for ensuring all market demand to be satisfied. In addition, unless the emergency prices of two suppliers are extremely higher, backup sourcing strategies could perform better than simultaneous sourcing strategy.

Description: This study investigates a multidepot heterogeneous vehicle routing problem for a variety of hazardous materials with risk analysis, which is a practical problem in the actual industrial field. The objective of the problem is to design a series of routes that minimize the total cost composed of transportation cost, risk cost, and overtime work cost. Comprehensive consideration of factors such as transportation costs, multiple depots, heterogeneous vehicles, risks, and multiple accident scenarios is involved in our study. The problem is defined as a mixed integer programming model. A bidirectional tuning heuristic algorithm and particle swarm optimization algorithm are developed to solve the problem of different scales of instances. Computational results are competitive such that our algorithm can obtain effective results in small-scale instances and show great efficiency in large-scale instances with 70 customers, 30 vehicles, and 3 types of hazardous materials.

Description: Single image super-resolution (SISR) is a traditional image restoration problem. Given an image with low resolution (LR), the task of SISR is to find the homologous high-resolution (HR) image. As an ill-posed problem, there are works for SISR problem from different points of view. Recently, deep learning has shown its amazing performance in different image processing tasks. There are works for image super-resolution based on convolutional neural network (CNN). In this paper, we propose an adaptive residual channel attention network for image super-resolution. We first analyze the limitation of residual connection structure and propose an adaptive design for suitable feature fusion. Besides the adaptive connection, channel attention is proposed to adjust the importance distribution among different channels. A novel adaptive residual channel attention block (ARCB) is proposed in this paper with channel attention and adaptive connection. Then, a simple but effective upscale block design is proposed for different scales. We build our adaptive residual channel attention network (ARCN) with proposed ARCBs and upscale block. Experimental results show that our network could not only achieve better PSNR/SSIM performances on several testing benchmarks but also recover structural textures more effectively.

Description: The extract of Nicotiana tabacum L. var Virginia origin of Ponorogo (EHRE-Nt) was applied under field conditions against the coffee borer beetle Hypothenemus hampei (CBB). Three extract formulations containing 150, 300, and 450 ml of EHRE-Nt in 100 liters of water were prepared and sprayed on 0.5 hectares each. A nontreatment was applied as a control on 0.5 hectares of plantation. The intensity of the CBB attacks was observed for six weeks on a Robusta coffee plantation in the Kalibening area, South Semarang, Central Java, Indonesia. An extract formulation containing 450 ml of EHRE-Nt resulted in the lowest intensity of CBB attacks from weeks one to six (1.6% to 2.2%). The attacks of the control field were 11.3% to 13.5%. The highest efficacy level of 85.4% was obtained with the 450 ml EHRE-Nt formulation. These results demonstrate that EHRE-Nt has potential as a bioinsecticide for coffee berries from CBB attacks.

Description: With the gestation and development of new technologies, new products, new formats, and new models, venture capital investment, as one of the most important forms of open innovation in large companies, plays an increasingly important role in the innovation of mature large companies and entrepreneurial enterprises. To deal with the complex and dynamic environment, the niche of Corporate Venture Capital (CVC) ecological community is investigated from the perspective of the innovation ecosystem. By analyzing the innovation of CVC ecological community with the use of the logistic expansion model, this paper analyzes the stability of evolution game through the replicator dynamic equation and discusses ten parameters of niche state. In the end, we conclude that there are four optimization strategies in the coevolution of major corporations and entrepreneurial firms, namely, niche separation, niche expansion, niche K-R, and niche alliance.

Description: Multiobject detection tasks in complex scenes have become an important research topic, which is the basis of other computer vision tasks. Considering the defects of the traditional single shot multibox detector (SSD) algorithm, such as poor small object detection effect, reliance on manual setting for default box generation, and insufficient semantic information of the low detection layer, the detection effect in complex scenes was not ideal. Aiming at the shortcomings of the SSD algorithm, an improved algorithm based on the adaptive default box mechanism (ADB) is proposed. The algorithm introduces the adaptive default box mechanism, which can improve the imbalance of positive and negative samples and avoid manually set default box super parameters. Experimental results show that, compared with the traditional SSD algorithm, the improved algorithm has a better detection effect and higher accuracy in complex scenes.

Description: The nonlinear resonant responses, mode interactions, and multitime periodic and chaotic oscillations of the cantilevered pipe conveying pulsating fluid are studied under the harmonic external force in this research. According to the nonlinear dynamic model of the cantilevered beam derived using Hamilton’s principle under the uniformly distributed external harmonic excitation, we combine Galerkin technique and the method of multiple scales together to obtain the average equation of the cantilevered pipe conveying pulsating fluid under 1 : 3 internal resonance and principal parametric resonance. Based on the average equation in the polar form, several amplitude-frequency response curves are obtained corresponding to the certain parameters. It is found that there exist the hardening-spring type behaviors and jumping phenomena in the cantilevered pipe conveying pulsating fluid. The nonlinear oscillations of the cantilevered pipe conveying pulsating fluid can be excited more easily with the increase of the flow velocity, external excitation, and coupling degree of two order modes. Numerical simulations are performed to study the chaos of the cantilevered pipe conveying pulsating fluid with the external harmonic excitation. The simulation results exhibit the existence of the period, multiperiod, and chaotic responses with the variations of the fluid velocity or excitation. It is found that, in the cantilevered pipe conveying pulsating fluid, there are the multitime nonlinear vibrations around the left-mode and the right-mode positions, respectively. We also observe that there exist alternately the periodic and chaotic vibrations of the cantilevered pipe conveying pulsating fluid in the certain range.

Description: Ventilator is important equipment for mines as it safeguards the lives under the shaft and ensures other equipment’s proper functioning by providing fresh air. Therefore, how to effectively control the ventilator system becomes more significant. In order to acquire the commonly used model and control strategy for ventilator systems, a new universal ventilator model is established based on the blast capacity differential pressure in the ventilating duct and the ventilator motor model. Then, an adaptive Chebyshev neural network (ACNN) controller is proposed to effectively control the ventilator system where the unknown load torque and the unknown disturbance caused by the complex environment under the shaft are approximated by the Chebyshev neural network (CNN). Afterwards, an appropriate Lyapunov function candidate is designed to guarantee the stability of the proposed controller and the closed-loop ventilator system. Finally, the ACNN controller has been demonstrated to be effective in terms of validity and precision for the new proposed ventilator model through the simulations.

Description: An experiment was conducted to examine the performance of pearl millet under different nitrogen (N) fertilizer rates in two locations in the semiarid zone of Nigeria. The objective was to evaluate the effects of different N rates on pearl millet yields, water- and nitrogen-use efficiency, and profitability. Grain yield increased by 23, 26, 32, 32, and 27% and by 38, 41, 54, 58, and 56% compared to unfertilized plots when applying 20, 40, 60, 80, and 100 kg Nha−1 in Minjibir and Gambawa, respectively. Similarly, stalk yield increased by 4, 3, 9, 9, and 9% and by 16, 24, 36, 40, and 37% compared to unfertilized plot when applying 20, 40, 60, 80, and 100 kg Nha−1 in Minjibir and Gambawa, respectively. The variations in GY that could be explained by TWU and NUE were 28% and 26% in Minjibir and 46% and 41%, respectively, in Gambawa. There was a strong and positive correlation (R = 0.81 and R = 0.95) between WUE and GY across N-fertilizer rates and pearl millet varieties in both locations. An increase in N-fertilizer levels increased WUE, confirming the optimal application of 60 kg Nha−1 in Minjibir and of 80 kg Nha−1 in Gambawa. Similarly, the highest net economic return (NER) of US$610 ha−1 was obtained at 60 kg Nha−1 in Minjibir and the highest NER of US$223 ha−1 was obtained at an application rate of 80 kg Nha−1 in Gambawa. Break-even yield was above 1000 kg ha−1, signifying that average farmer with a mean yield of less than 1000 kg ha−1 produces millet at a loss.

Description: Factors that limit the range expansion of introduced species can offer insights into the basic ecology of these species and inform conservation of associated endemic species. North American red squirrels (Tamiasciurus hudsonicus (Erxleben, 1777)) were recently introduced to the island of Newfoundland, Canada, where they have been implicated in the decline of two endemic bird subspecies. During the summers of 2016 (following conifer masting) and 2017 (following nonmasting), we conducted surveys with 1960 point counts and playback to assess red squirrel distribution and habitat use across a 257 km2 montane landscape in western Newfoundland. We used generalized additive models with stepwise model selection to assess the relationship between land cover and red squirrel occurrence each summer. Red squirrels were most common at low elevations and were not detected at elevations above ∼500 m. Their occurrence was negatively associated with the presence of water, coniferous scrub, and 10- to 30-year-old fir–spruce but positively associated with the presence of 30- to 70-year-old fir–spruce and 〉70-year-old fir. Red squirrel presence was related to more land cover variables in 2016, after a masting year. The absence of red squirrels from forests at higher elevations apparently resulted from lack of suitable habitat rather than incomplete range expansion. Climate- or silviculture-induced changes in vegetation may alter mid- and upper-elevation habitat suitability.

Description: Nonlinear evolution equations widely describe phenomena in various fields of science, such as plasma, nuclear physics, chemical reactions, optics, shallow water waves, fluid dynamics, signal processing, and image processing. In the present work, the derivation and analysis of Lie symmetries are presented for the time-fractional Benjamin–Bona–Mahony equation (FBBM) with the Riemann–Liouville derivatives. The time FBBM equation is reduced to a nonlinear fractional ordinary differential equation (NLFODE) using its Lie symmetries. These symmetries are derivations using the prolongation theorem. Applying the subequation method, we then use the integrating factor property to solve the NLFODE to obtain a few travelling wave solutions to the time FBBM.

Description: The Cloud Computing paradigm is focused on the provisioning of reliable and scalable virtual infrastructures that deliver execution and storage services. This paradigm is particularly suitable to solve resource-greedy scientific computing applications such as parameter sweep experiments (PSEs). Through the implementation of autoscalers, the virtual infrastructure can be scaled up and down by acquiring or terminating instances of virtual machines (VMs) at the time that application tasks are being scheduled. In this paper, we extend an existing study centered in a state-of-the-art autoscaler called multiobjective evolutionary autoscaler (MOEA). MOEA uses a multiobjective optimization algorithm to determine the set of possible virtual infrastructure settings. In this context, the performance of MOEA is greatly influenced by the underlying optimization algorithm used and its tuning. Therefore, we analyze two well-known multiobjective evolutionary algorithms (NSGA-II and NSGA-III) and how they impact on the performance of the MOEA autoscaler. Simulated experiments with three real-world PSEs show that MOEA gets significantly improved when using NSGA-III instead of NSGA-II due to the former provides a better exploitation versus exploration trade-off.

Description: There is a large amount of information and maintenance data in the aviation industry that could be used to obtain meaningful results in forecasting future actions. This study aims to introduce machine learning models based on feature selection and data elimination to predict failures of aircraft systems. Maintenance and failure data for aircraft equipment across a period of two years were collected, and nine input and one output variables were meticulously identified. A hybrid data preparation model is proposed to improve the success of failure count prediction in two stages. In the first stage, ReliefF, a feature selection method for attribute evaluation, is used to find the most effective and ineffective parameters. In the second stage, a K-means algorithm is modified to eliminate noisy or inconsistent data. Performance of the hybrid data preparation model on the maintenance dataset of the equipment is evaluated by Multilayer Perceptron (MLP) as Artificial Neural network (ANN), Support Vector Regression (SVR), and Linear Regression (LR) as machine learning algorithms. Moreover, performance criteria such as the Correlation Coefficient (CC), Mean Absolute Error (MAE), and Root Mean Square Error (RMSE) are used to evaluate the models. The results indicate that the hybrid data preparation model is successful in predicting the failure count of the equipment.

Description: The optical images collected by remotely operated vehicles (ROV) contain a lot of information about underwater (such as distributions of underwater creatures and minerals), which plays an important role in ocean exploration. However, due to the absorption and scattering characteristics of the water medium, some of the images suffer from serious color distortion. These distorted color images usually need to be enhanced so that we can analyze them further. However, at present, no image enhancement algorithm performs well in any scene. Therefore, in order to monitor image quality in the display module of ROV, a no-reference image quality predictor (NIPQ) is proposed in this paper. A unique property that differentiates the proposed NIPQ metric from existing works is the consideration of the viewing behavior of the human visual system and imaging characteristics of the underwater image in different water types. The experimental results based on the underwater optical image quality database (UOQ) show that the proposed metric can provide an accurate prediction for the quality of the enhanced image.

Description: Identification of community structures and the underlying semantic characteristics of communities are essential tasks in complex network analysis. However, most methods proposed so far are typically only applicable to assortative community structures, that is, more links within communities and fewer links between different communities, which ignore the rich diversity of community regularities in real networks. In addition, the node attributes that provide rich semantics information of communities and networks can facilitate in-depth community detection of structural information. In this paper, we propose a novel unified Bayesian generative model to detect generalized communities and provide semantic descriptions simultaneously by combining network topology and node attributes. The proposed model is composed of two closely correlated parts by a transition matrix; we first apply the concept of a mixture model to describe network regularities and then adjust the classic Latent Dirichlet Allocation (LDA) topic model to identify community semantically. Thus, the model can detect broad types of network structure regularities, including assortative structures, disassortative structures, and mixture structures and provide multiple semantic descriptions for the communities. To optimize the objective function of the model, we use an effective Gibbs sampling algorithm. Experiments on a number of synthetic and real networks show that our model has superior performance compared with some baselines on community detection.

Description: This work investigates a decentralized state feedback scheme of neural network control for an interconnected system. The completely unknown associated terms are estimated directly by the neural structure. A modified approach is proposed to deal with the state feedback format. By combining the Lyapunov function and backstepping technology together, an adaptive decentralized controller is established, and we can construct the boundedness of all signals in the closed-loop structure through the controller, which can drive the formation of a given reference signal. In the end, the effectiveness of the presented strategy is referred to a simulation example.

Description: A novel four-dimensional energy, economic, and environmental (3E) under energy reduction constraints chaotic system is proposed. The acquisition of environmental quality data is the key to this paper. During the course of the study, we used Bayesian estimation algorithm to calibrate the environmental quality. Based on the official data, the Levenberg–Marquardt backpropagation neural network method was optimized by genetic algorithm to effectively identify the parameters in the 3E system. The research results show that although increasing energy reduction inputs can improve environmental quality, the effect on energy intensity and overall stability of the system is not obvious. When polluting input in the ecological environment system affects its maximum capacity, the environmental system collapses (i.e., the ecological system can no longer purify the environment through the self-circulation process and will eventually die out). Therefore, it is necessary to correctly grasp the ecological environment protection and the relationship between economic developments and explore synergies to promote ecological priorities and green development new ideas.

Description: Ditch network maintenance promotes forest growth in drained peatland forests but increases nutrient and sediment loads, which are detrimental to water quality. Society needs to balance the harvest revenue from improved forest growth against deteriorating water quality. We examine socially optimal even-aged forest management in drained peatlands when harvesting and ditch network maintenance cause nutrient and sediment loading. The means to reduce loading include establishing overland flow fields and abstaining from ditch network maintenance. We characterize this choice analytically in a rotation framework and examine, in a numerical model, the key factors affecting the choice of forest management and water protection measures. We choose a drained peatland forest site located in northeastern Finland in the vicinity of ecologically vulnerable forest headwater streams. On the given drained forest site, we find a set of parameters under which implementing ditch network maintenance is privately but not socially optimal.

Description: Shadow fractions can be overestimated because of topographic shadows, which can occupy a significant area on aerial photographs of mountainous terrain. In this study, we first used high-dynamic-range (HDR) image analysis techniques to extract the original canopy shadow from the topographic shadows on aerial photographs. Subsequently, we applied the shadow fraction method to estimate selected forest attributes (stand height, basal area, and stem volume). In this paper, we discuss the effects of tree shadow fraction normalization, auxiliary spectral information, and forest type on forest attribute estimation. HDR image analysis successfully extracted canopy shadow information from topographic shadows. The tree shadow fraction normalization method had no obvious effect. The shadow fraction enhanced spectral information to estimate stand attributes. Using shadow fractions resulted in better estimates of stand height for mixed-hardwood forest ([Formula: see text] = 0.45), basal area for mixed-hardwood forest ([Formula: see text] = 0.50), and stem volume for conifer–hardwood forest ([Formula: see text] = 0.43). This difference in estimated results is related to the shade patterns produced by stand structures in the different forest types.

Description: Forest supply chain planning must deal with many natural disturbance uncertainties such as fires, insects, and windthrow. One important consideration is wood infestation by invasive insects, as it causes environmental and economic harm. An example of invasive insects in Eastern Canada is the spruce budworm (Choristoneura fumiferana (Clemens)), which is the most destructive insect in North America’s conifer stands. In 2017, more than 5 million ha of forest were defoliated by spruce budworm in Quebec. Repeated defoliation causes tree mortality, reduction of growth rates, and reduced lumber quality. Consequently, different wood qualities with greatly varied values are found in the forest. Changes in the outbreak intensity impact wood values throughout the forest. One of the common actions to mitigate the economic and environmental damages is salvage harvesting. However, because of the large uncertainties and lack of detailed information, it is a difficult problem to model. We propose a multistage stochastic mixed-integer programming model for harvest scheduling under various outbreak intensities. The objective is to maximize revenues of wood value minus logistic costs while satisfying demand for wood in the industry. The results show that when there is an outbreak throughout the forest, the priority for salvage harvesting is to focus on forest areas with the lowest level of infestation.

Description: Simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) genotypes on the same plant samples of Chrysolepis chrysophylla (Douglas ex Hook.) Hjelmq. (Fagaceae; golden chinquapin) from 22 sites were used to determine genetic diversity and population structure. One site of C. sempervirens (Kellogg) Hjelmq. allowed interspecific vs. intraspecific comparisons. SSRs and SNPs yielded many similar results. Among-site variation contributed 13% to 17% of the genetic variation and Fst estimates of 0.14 to 0.17 were in the range expected among Fagaceae species rather than among populations within a species. The northern sites tended to group separately on the first two axes of multivariate scatterplots from southern sites. Sites in two geographically isolated areas were divergent: (i) the Hood Canal, Washington population was relatively more genetically distant from other golden chinquapin sites than was our C. sempervirens site; (ii) three coastal southern California sites were moderately diverged. The Hood Canal site had a negative inbreeding coefficient, fewer alleles, lower heterozygosity, and differed from the Skamania County, Washington site as well as all other sites. Hood Canal trees are distinguished by disjunct geography and by these molecular results. This suggests that the golden chinquapin near Hood Canal be treated as a management unit, and potential conservation actions are discussed.

Description: The gravity model was used in this paper to clarify the influencing factors of the export value of non-timber forest products (NTFPs) for Vietnam from 2003 to 2017. The estimates of this model indicate the importance of the size of economies, distance, common borders, exchange rates, average forest area, natural forest closing (NFC) policy of the Vietnamese government, sanitary and phytosanitary measures (SPS), and the interaction of SPS and importers’ GDP (SPS-GDP) as determinants of NTFP export of Vietnam. The main result of this study is the distinct and contradictory effect of NFC policy and SPS measures. While, the NFC policy increase the value of Vietnam's NTFP exports, SPS measures significantly decrease the exportation. Using the SPS-GDP interaction variable yields a noticeable result: the negative impact of SPS on NTFP trade decreases with increasing income of NTFP importers. Furthermore, the NFC needs to continue to implement policies to increase investments in the NTFPs trade, increase the quality of NTFP products from planting, harvesting, to processing, to meet the requirements of future importers. The findings offer several implications both in theory and in practice for trade policies, economic development theory based on Vietnam's forest resources.

Description: Forest management, characterized in many northern countries by the predominance of clear cutting and growing even-aged and -sized trees, has simplified the structure of boreal forests. Consequences include alterations in cultural ecosystem services such as forest attractiveness, i.e., combined aesthetic and recreational values. Continuous-cover forestry might mitigate these effects through the use of selection and gap cutting, but these methods have been little studied, particularly from the attractiveness viewpoint. We used photo surveys to assess Finnish citizens’ perceptions of attractiveness of in-stand scenery of Scots pine (Pinus sylvestris L.) forests logged using different methods. (i) The attractiveness scores, given by respondents, declined steadily from unharvested forest through continuous-cover methods to seed-tree and clear-cut methods. (ii) Respondents with a negative attitude to forest management gave lower scores than respondents with a positive attitude, but the declining slopes of attractiveness against logging intensity were similar. (iii) In unharvested and less intensively managed stands, summer photos received higher scores than corresponding winter photos. (iv) Background variables (gender, education, living environment, memberships in recreational or nature NGOs, forestry profession, and forest ownership) had negligible effects on the scores. We recommend the use of continuous-cover logging methods in settlement and recreational areas.

Description: The world’s forests are highly fragmented by linear disturbances, and many forests have failed to recover decades after abandonment. Lack of recovery is common in unproductive forests, such as treed peatlands, because of conditions that limit tree growth, including simplification of microtopography (loss of microsites). The persistence of these features affects biodiversity, but of particular concern in Canada is the detrimental effects on threatened woodland caribou. Although natural regeneration of trees in peatlands occurs in some places, it is not an effective recovery strategy for restoring the habitat of woodland caribou. This has led to restoration activities with costs exceeding CAD$12 500/km. However, current restoration does not consider wildfires, which can destroy planted trees but also initiate early seral conditions that favor natural regeneration. Here we compared tree regeneration on seismic lines and adjacent forest controls for burnt (75 sites) and unburnt (68 sites) treed peatlands in northeast Alberta, Canada. Tree regeneration (stems with a DBH 〈 1 cm/ha) varied from 28 500 in burnt lines, 11 440 in unburnt lines, and 18 210 in burnt forest, to 9520 in unburnt forest. Wildfires promoted denser regeneration in sites with a greater proportion of serotinous species and water table depth. Microtopography and terrain wetness explained regeneration on burnt lines, but not unburnt lines. In burnt and unburnt lines, sunlight, microtopography, and depth of water table most affected tree regeneration patterns.

Description: Because of the very high complexity of modern optimization models based on single trees, uncertainties are often disregarded. In this study, we present a modelling approach that allows partial harvesting but is still simple enough to consider risk. Our modelling approach investigates whether the inclusion of timber price uncertainty influences the harvesting schedule. The model considers positive growth response to the density reduction that follows harvesting. Testing the impact of uncertainty, we define the discounted net revenues of each harvest operation as random variables. We compare harvest scheduling both with and without the inclusion of uncertainty. We first model growth response based on a partial-harvest schedule, without integrating uncertainty from timber price fluctuations. The results show that harvesting tree cohorts at different times is financially optimal. We run the same model again, including the risk of timber price fluctuations. The inclusion of risk leads to slightly greater differences in recommended harvest timings. Because of the small difference observed, we conclude that it is unlikely that risk arising from fluctuating timber prices would strongly affect the results for more complex forest economic models concerning the optimal harvest schedules.

Description: Once dominant across the United States (US) Southeastern Coastal Plain, the longleaf pine (Pinus palustris Mill.) ecosystem covers a fraction of its historic geographic range. Restoration efforts have largely occurred on public lands, while most private forests feature alternative pine species. A better understanding of public interest in ecological restoration is critical to sustained efforts and successes. This research examines both forest landowner and general public interest in longleaf pine restoration. Results contribute to research on the social dimensions of ecological restoration, much of which has focused on small-scale projects rather than landscape-scale initiatives. In addition, this study addresses the lack of knowledge regarding factors driving attitudes towards ecological restoration other than demographic and psychometric variables. We employed a telephone survey of 2700 participants across eight states in the southeastern US in the historical range of longleaf pine. A majority of respondents supported restoration as a general goal and were supportive of the use of prescribed fire as a restoration practice. Place attachment, knowledge about longleaf pine, and age were among the significant predictors of restoration support. Findings have implications for future research focusing on sociocultural influences of restoration projects, as well as expanded public support for restoration of fire-maintained ecosystems.

Description: Coarse woody debris (CWD) in the form of logs, downed wood, stumps and large tree limbs is an important structural habitat feature for many small mammal species, including the American marten (Martes americana). At a long-term experimental trial in northern temperate hemlock-cedar forests of British Columbia, Canada, we analysed the impact of varying amounts of overstory basal area retention: 0% (clearcut), 40%, 70%, and 100% (unharvested) on CWD volume, decay class, and inputs from windthrow over 27 years. We used CWD attributes (diameter, length, decay class, and height above the ground) known to be favourable for martens to create an index for assessing the impact of harvesting intensity on CWD habitat features. Stands with 70% retention had CWD attributes that resulted in CWD habitat features similar to unharvested stands. Clearcuts contained pieces that were smaller, more decayed, and closer to the ground, which contributed to a habitat that was less valuable, compared with stands that had higher retention. Over the 27-year period, windthrown trees were the majority of CWD inputs, and volume change was positively related to percent retention. Our results highlight that forest management influences CWD size and input dynamics over multiple decades, and the need for consideration of these impacts when undertaking long-term multiple-use forestry planning.

Description: Fire is an important disturbance agent in the boreal forests of China. The aggressive fire suppression policy of China since 1988 has resulted in a large financial investment in support of fire brigade capabilities and the maintenance of fire management infrastructure. We developed a spatially explicit burn probability (BP) model to evaluate the effectiveness of improved fire management in Daxing’anling, China. The BP model can emulate the burn probability of the forest landscape by simulating daily wildfire occurrences, spread, and suppression for simulated years. Two scenarios were used for fire simulations in this study. The base scenario used the infrastructure data and parameters of fire suppression capability from the 1968–1987 period, and the intensive scenario used the data and parameters from the 1988–2012 period. The simulated annual burned areas for 1968–2012 showed a fluctuating trend similar to the historical fire records. Compared with the base scenario, the burn probability decreased by 73.6% under the intensive scenario, which suggests that improved fire management could significantly reduce the burn probability. This study shows that the BP model can model the effects of fire management activities on the forest landscape level and evaluate the effectiveness of fire management strategies or management measures.

Description: The impact of climate change on tree stability is often associated with a higher risk of windthrow due to higher frequency and greater magnitude of extreme climatic conditions. Higher lateral loads due to an increase in maximum wind and rainfall reduce tree anchorage because of a decrease in soil matric suction and consequently the overall strength in the system of trunk, root, and soil. This study compared the mechanical response of trees with different root architectures using static loading tests conducted in the field and numerical analysis of laser-scanned root systems. For this case, mature trees of Khaya senegalensis (Desr.) A. Juss., Samanea saman (Jacq.) Merr., and Syzygium grande (Wight) Wight ex Walp. were tested and analyzed. The root system models consisted of root system architectures obtained using 3-D laser scanning. A parametric analysis was conducted by varying the modulus of elasticity of the soil (Es) from 2.5 to 25 MPa, and the results were compared with those of the static loading tests to obtain the overall mechanical responses of the root–soil systems. The results showed important dependencies of the mechanical responses of the root–soil system on the root architecture in withstanding the lateral load. The numerical models also allowed estimation of the effective leeward and windward anchorage zones with different soil elastic moduli and rooting architectures to define the extent of the tree root protection zones.

Description: Habitat loss is one of the main consequences of landscape transformation by humans. Monitoring biodiversity changes in areas under different management strategies is fundamental for species conservation. Our study is the first to assess the role of forest disturbance history on spider (Araneae) biodiversity in the westernmost portion of the Atlantic Forest. We analyzed taxonomic and functional aspects of spider assemblages in understories in a large forest fragment in southwestern Brazil. Spiders were sampled in five 30 m × 5 m plots over three seasons in three areas with different management histories: clear-cutting, selective logging, or native plots. We also characterized tree basal area, tree density, and canopy openness. The clear-cut plots showed more canopy openness and low habitat heterogeneity due to the high density of one pioneer native tree species. Forest structure in selective logging and native plots was similar. Spider richness, abundance, and functional richness were affected only by the season. Species composition also differed among the areas depending on the season. The abundance of web-building species was mainly associated with clear-cut areas in winter and spring. These results highlight the importance of natural regeneration in the Atlantic Forest after disturbance for the conservation of regional spider biodiversity.

Description: In Europe, mixed mountain forests, primarily comprised of Norway spruce (Picea abies (L.) Karst.), silver fir (Abies alba Mill.), and European beech (Fagus sylvatica L.), cover about 10 × 106 ha at elevations between ∼600 and 1600 m a.s.l. These forests provide invaluable ecosystem services. However, the growth of these forests and the competition among their main species are expected to be strongly affected by climate warming. In this study, we analyzed the growth development of spruce, fir, and beech in moist mixed mountain forests in Europe over the last 300 years. Based on tree-ring analyses on long-term observational plots, we found for all three species (i) a nondecelerating, linear diameter growth trend spanning more than 300 years; (ii) increased growth levels and trends, the latter being particularly pronounced for fir and beech; and (iii) an elevation-dependent change of fir and beech growth. Whereas in the past, the growth was highest at lower elevations, today’s growth is superior at higher elevations. This spatiotemporal pattern indicates significant changes in the growth and interspecific competition at the expense of spruce in mixed mountain forests. We discuss possible causes, consequences, and silvicultural implications of these distinct growth changes in mixed mountain forests.

Description: To assess the impacts of uncertainty and environmental objectives on the configuration of timber supply networks, we develop a generic multi-period, mixed-integer fuzzy linear programming model with demand uncertainty and two objectives of minimizing total transportation cost and greenhouse gas (GHG) emissions. We then use the triangular fuzzy number method to define the uncertain demands and convert the model into its equivalent auxiliary crisp counterpart. To derive Pareto solutions more efficiently, we propose the nondominated sorting genetic algorithm (NSGA-II) to solve the model. Finally, we apply the model framework and solution method to a real-world case of regional timber supply in Fujian, China, to demonstrate their applicability. The simulation results of the model show that trade-offs exist between total cost and GHG emissions and that the proper selection of the number and locations of distribution centers can help reduce both the cost and GHG emissions. Demand uncertainty and supply fluctuations across different time periods can increase the cost and GHG emissions. Our empirical results provide useful insights into the design and management of regional timber supply networks, and our generic model is applicable to the analysis of regional supply networks of other products or materials besides timber.

Description: Recent interest in continuous cover forest management of longleaf pine (Pinus palustris Mill.) ecosystems raises questions of long-term sustainability because of uncertainty in rates of canopy recruitment of longleaf pine trees. We destructively sampled 130 naturally regenerated, midstory longleaf pines across an 11 300 ha, second-growth longleaf pine landscape in southwestern Georgia, United States, to reconstruct individual tree height growth patterns. We tested effects of stand density (using a competition index) and site quality (based on two site classifications: mesic and xeric) on height growth and demographics of midstory trees. We also compared height growth of paired midstory and overstory trees to infer stand regeneration and recruitment dynamics. In low-density stands, midstory trees were younger and grew at greater rates than trees within high-density stands. Midstory trees in low-density stands were mostly from a younger regeneration cohort than their paired overstory trees, whereas midstory–overstory pairs in high-density stands were mostly of the same cohort. Our results highlight the importance of releasing midstory longleaf pine trees from local competition for sustained height growth in partial-harvesting management systems. They also demonstrate patterns of long-term persistence in high-density stands, indicating flexibility in the canopy recruitment process of this shade-intolerant tree species.

Description: Fire refugia — locations that burn less severely or less frequently than surrounding areas — support late-successional and old-growth forest structure and function. This study investigates the influence of topography and fuels on the probability of forest fire refugia under varying fire weather conditions. We focused on recent large fires in Oregon and Washington, United States (n = 39 fires 〉 400 ha, 2004–2014). Our objectives were to (1) map fire refugia as a component of the burn severity gradient, (2) quantify the predictability of fire refugia as a function of prefire fuels and topography under moderate and high fire weather conditions, and (3) map the conditional probability of fire refugia to illustrate their spatial patterns in old-growth forests. Fire refugia exhibited higher predictability under relatively moderate fire weather conditions. Prefire live fuels were strong predictors of fire refugia, with higher refugia probability in forests with higher prefire biomass. In addition, fire refugia probability was higher in topographic settings with relatively northern aspects, steep catchment slopes, and concave topographic positions. Conditional probability maps revealed consistently higher fire refugia probability under moderate versus high fire weather scenarios. Results from this study inform conservation planning by determining late-successional forests most likely to persist as fire refugia despite increasing regional fire activity.

Description: The sampling intensity of a national forest inventory is usually low. Forest dynamics models can be used to update plots from past inventory campaigns to enhance the precision of the estimate on smaller areas. By doing this, however, the inference relies not only on the sampling design, but also on the model. In this study, the contribution of model predictions to the variance of enhanced small-area estimates was assessed through a case study. The French national forest inventory provided different annual campaigns for a particular region and department of France. Three past campaigns were updated using a forest dynamics model, and estimates of the standing volumes were obtained through two methods: a modified multiple imputation and the Bayesian method. The update greatly increased the precision of the estimate, and the gain was similar between the two methods. The sampling-related variance represented the largest share of the total variance in all cases. This study suggests that plot updating provides more precise estimates as long as (i) the forest dynamics model exhibits no systematic lack of fit and was fitted to a large data set and (ii) the sampling-related variance clearly outweighs the model-related variance.

Description: This study was carried out in the northern region of Burkina Faso under Sahelian climatic conditions. The area was particularly affected by the 1970s–1980s droughts that led to the degradation of land and vegetation. Since the early 1990s, a gradual return of rainfall has been observed throughout the Sahel region. In this new environmental context, understanding the development of woody plants is important for effective conservation and management. We analyzed the dynamics of woody plant cover over the 30 years following the end of the 1970s–1980s droughts by using Landsat images from 1986, 1999, and 2015 with 30 m spatial resolution and taking into account changes in rainfall and land use. The change in the enhanced vegetation index 1 (EVI1) at the beginning of the dry season was used as a proxy for the change in photosynthetic activity of woody plants. Results showed an improvement in EVI1 on 98% of the study area, with a mean increase of 0.20 from 1986 to 2015. This improvement was accompanied by an increase in agroforestry and was weakly correlated with rainfall. The improvement in EVI1 was unstable, however, with a decline from 1999 to 2015 in the areas undergoing regreening.

Description: The effect of the radial force applied by a ring debarker tip to frozen balsam fir (Abies balsamea (L.) Mill.) logs, obtained at three positions on the stem, was studied. A one-armed ring debarker prototype was built, which controlled the radial force, the rake angle, and cutting and feed speeds. Balsam fir logs at −19 °C were debarked at three levels of radial force. The rake angle, tip overlap, tip edge radius, and cutting and feed speeds were kept constant. Debarking quality was evaluated by two criteria: the proportion of bark remaining on log surfaces and the amount of wood fibres in bark residues. Log characteristics (dimensions, eccentricity, bark thickness, and knot features), bark–wood shear strength, and the basic densities of sapwood and bark were also measured. Results showed that the radial force had a significant effect on debarking quality. The proportion of bark remaining on log surfaces increased while the amount of wood fibres in bark residues decreased as radial force decreased. A radial force of 18.5 N·mm−1 is suggested for an optimal debarking quality. In contrast, log position on the stem did not affect the debarking quality indicators. Results also showed that the proportion of bark remaining on log surfaces increases as bark–wood shear strength and the proportion of knot surface increase, while the amount of wood fibres in bark residues increases as bark–wood shear strength decreases and logs are more eccentric. The results give useful information to improve the debarking process within the studied range of log diameters and debarking parameters.

Description: In this study, the performance of a selected microbial consortium (Scutellospora calospora + Azotobacter chroococcum + Bacillus coagulans + Trichoderma harzianum) on Acacia auriculiformis A. Cunn. ex Benth. was evaluated through large-scale nursery trials at three locations in the Mandya district of Karnataka state, India. At each location, 500 inoculated and 500 uninoculated seedlings were cultivated. The increase in plant dry biomass of inoculated plants was 31% (mean of three locations) compared with uninoculated plants. The seedlings inoculated with microbial consortium under large-scale nursery trials were planted in wasteland at three locations, and their growth was monitored for nearly 6 years. At the end of the study, field growth of inoculated trees, measured as the biovolume index, was 52% higher than that of uninoculated trees. This study shows that the selected microbial consortium enhances nursery quality and midterm field growth of Acacia auriculiformis plantations on dry wasteland.

Description: Shade-tolerant mesophytic tree species tend to dominate the understories of present-day oak–hickory and mixed-hardwood forests in the eastern United States. We quantified the sapling density associations with abiotic and biotic variables for three important mesophytic species: red maple (Acer rubrum L.), sugar maple (Acer saccharum Marsh.), and American beech (Fagus grandifolia Ehrh.) in southeastern Ohio. In this study, we sampled 165 permanent plots in oak-dominated, topographically diverse, mature (〉90 years old), second-growth forests following a time span of 21–25 years (1993–1995 and 2016–2018) between samples on the Athens and Marietta units of the Wayne National Forest. Our models showed that sugar maple was strongly associated with high pH soils and red maple was strongly associated with low pH soils. Additionally, red maple was associated with upper slope positions and older stands, while American beech was associated with lower slopes, northeasterly aspects, and northeast-facing upper slopes. Basal area of competing species, solum depth, and management unit were not significantly related to sapling density for our focal species. American beech sapling density doubled between the two sampling periods, while densities of both maple species declined by half. Our results will help scientists and managers by providing insight into potential future composition of currently oak-dominated forests in areas without active management intervention.

Description: There has been limited study of songbird communities in different habitats of the lowland boreal forests of southern Yukon, including the mature forest valued for timber harvest. Our goal was to describe the songbird community during the breeding season in a mature (≥80 years since wildfire) forest dominated by white spruce (Picea glauca (Moench) Voss) adjacent to streams (n = 23) and wetlands (n = 15) compared with a nearby upland forest. Based on point count surveys, songbird communities were unique in the mature forest in the riparian forest edge position, including greater species richness and four significant riparian indicator species. Songbird communities were also unique in the forest adjacent to streams versus wetlands. We mapped species observations along 300 m transects from riparian to upland forests and identified nine species with greater abundance closer to the riparian forest edge. Many of these species are typically associated with riparian and wetland habitats for breeding. Most of the variability in the songbird community was explained by study site, likely related to high variability in forest type and amount of wetland and open water but also to unmeasured habitat characteristics. Our results increase the knowledge of songbird communities in this unique boreal region and suggest that riparian reserve zones in forest management may be useful for protecting songbird habitat.

Description: Softwood logs comprise a large portion of forest product exports from the United States. Most of these exports have occurred between the Pacific Northwest region of the United States and several Asian countries. In this study, the extent and degree of market integration of softwood log exports from 1996 to 2018 are examined by co-integration analyses and permanent–transitory decomposition. Softwood log exports to Japan and South Korea appear to be in the same economic market and show a high degree of integration, while trade between the United States and China has evolved more independently. A detailed analysis is conducted on five prices related to Japan and South Korea with full-time coverage, and one common integrating factor is found and estimated. The price of export from the Columbia-Snake Customs District to Japan is identified as the driving force. Price responses to market shocks usually occur within four months. These findings have implications for government agencies and participants in the market of softwood log trade.

Description: In southeast Alaska, United States, multiple-use forest management objectives include both timber production and wildlife habitat. Following stand-replacing disturbances such as clear-cutting, Sitka spruce (Picea sitchensis (Bong.) Carrière) and western hemlock (Tsuga heterophylla (Raf.) Sarg.) naturally regenerate and competitively dominate resources, excluding understory biomass and biodiversity. Thinning may mitigate the effects of canopy closure and permit understory development, but evidence of the effect on understories 8–10 years after thinning is lacking. We report results 4–5 and 8–10 years after thinning experiments on the Tongass National Forest to demonstrate the effects of precommercial thinning (thinned versus control), stand age (15–25, 25–35, and 35–50 years), and weather on understory dynamics and Sitka black-tailed deer (Odocoileus hemionus sitkensis Merriam, 1898) forage availability. Stand density negatively affected understory biomass, whereas temperature and precipitation positively interacted to increase biomass. Thinning had an enduring effect on understories, with biomass at least twice as great in thinned versus unthinned stands through year 10. We identified compositional differences from thinning as stand age class increased. Deer forage responded similarly to biomass, but thinning-induced differences faded with increased winter snowfall scenarios, especially in older stands. This study aids the understanding of stand overstory and understory development following silvicultural treatments in the coastal temperate rain forest of Alaska and suggests management implications and applications for balancing objectives throughout the forest type.

Description: The objective of our research is to extend current conservation applications of modern portfolio theory (MPT) to develop a framework for the cost-efficient budget distribution for a forest carbon payment program that optimizes risk–reward trade-offs in the presence of economic growth uncertainty over time. We consider correlation across space and time of the fluctuating opportunity costs of restoring forestland under changing future economic conditions using a case study of eight states in the central and southern Appalachian region of the United States. The findings suggest that optimal budget allocation decisions that ignore the covariance component of the spatial variance–covariance structure of forest carbon returns fail to minimize the true risk of conservation investment for any level of expected return. The importance of incorporating the spatial covariance in targeting conservation payments is made explicit through alternative approaches using multi-objective (mean–variance) optimization and an ex post analysis with and without the covariance component of the spatial variance–covariance structure of forest carbon return on investment (ROI). A comparison of these approaches against our MPT-based approach revealed misleading risk–return expectations if the ROI covariance is ignored in the spatial targeting of forest carbon payments under uncertainty.

Description: Wood density, an important parameter for evaluating forest biomass productivity and wood product quality control, is influenced by a complex combination of variables of forest plantations, including environmental conditions and the management practices adopted. In this paper, we demonstrate that three site variables (annual rainfall, temperature, and soil texture) and 10 plantation variables (e.g., age and genetic material) are associated with basic wood density (evaluated in two situations: with and without bark) in 936 trees of different species of Eucalyptus L’Hér across five distinct edaphoclimatic regions in Brazil. A canonical correlation analysis was used to identify the most contributory variables affecting wood density. The variables globally associated with high basic wood densities were, in order of importance, the genetic material and area per tree (both under direct control of plantation managers), as well as mean annual temperature and soil texture of the site. These results confirmed the advantage of using clonal material (instead of seedling origin material) planted in larger spacings in sites with higher mean annual temperatures and clayey soils to obtain higher basic wood densities. Conversely, low basic wood densities were associated with high-productivity sites, higher rainfall, and plantations with a higher basal area per stem in second rotation.

Description: Trends in land cover and the demand for ecosystem services suggest that plantation forests will be expected to provide a larger quantity and diversity of ecosystem services. We identified three measures indicative of diverse ecosystem services (aboveground biomass, understory biodiversity, and crown length) and compared their relationships to tree species composition in intensively managed forest plantations of the Coast Range mountains of the Pacific Northwest, United States. This study was conducted in stands of western hemlock (Tsuga heterophylla (Raf.) Sarg.), Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco), and red alder (Alnus rubra Bong.), as well as in mixtures of the three species that were 35–39 years old. In this operational setting, we did not observe the positive relationship between species diversity and productivity observed in other studies, which we attributed to management practices that minimize interspecific interaction during most of the rotation. Crown length and understory species diversity were greater in mixtures of tree species than in (monospecific) monocultures. When multiple ecosystem components were considered simultaneously, mixtures of tree species outperformed monocultures. The observed relationships of the three responses to tree species composition and diversity are likely explained by differences in tree phenology, shade tolerance, disease susceptibility, and management interventions. Based on the results, management that is solely fixated on wood production homogeneously throughout the plantation may miss opportunities to provide other ecosystem services.

Description: We compared early seral development between stands subject to single and repeated high-severity wildfire in low-elevation, mixed conifer – hardwood forests in the Klamath Mountains, California, USA. We used a before–after, control–impact (BACI) approach to assess changes in the density of conifer regeneration and the cover of multiple components of vegetation structure (conifers, hardwoods, shrubs, forbs, and graminoids) and compare pathways of seral development between plots that burned once and plots that burned twice. Fifty-three field plots were established 6 years following a high-severity fire in 2004. Nineteen of these plots experienced a second high-severity wildfire 11 years later (2015), and all plots were remeasured in 2016–2017. Conifer regeneration was abundant following the first fire but was greatly reduced by the second fire. Plots that did not reburn increased in conifer, hardwood, and shrub cover, whereas plots that reburned increased in forb cover and decreased in shrub, hardwood, and conifer cover. Despite conifer loss, we found little evidence of shifts to nonforested states following repeated fire due to resilience of resprouting hardwoods. Our results indicate that repeated high-severity fire has the potential to protract early seral development and catalyze transitions from mixed conifer – hardwood forest to hardwood-dominated early seral conditions.

Description: Imaging spectroscopy is currently the best approach for continuously mapping forest canopy traits, which is important for ecosystem and biodiversity assessments. Ideally, models are trained with trait data from fully sunlit leaves from the top of the canopy. However, sampling leaves at the top of the canopy is often difficult, and sunlit foliage from the crown periphery is collected instead, assuming minimal within-crown trait variation among sunlit leaves. We tested the degree to which crown position affects foliar traits and spectra using mixed-effects models comparing sun leaves from the crown centre of mature sugar maple (Acer saccharum Marsh.) trees collected with DeLeaves, a novel twig-sampling unmanned aerial system device, with sun leaves from the crown periphery collected with a pole pruner. Sun leaves from the crown centre differed from sun leaves from the crown periphery in absorption, reflectance, transmittance, and a series of foliar traits, including leaf thickness, leaf mass, and leaf nitrogen content per unit area, demonstrating differences in resource allocation depending on sun exposure. Our study highlights the importance of accurately matching the location of foliar samples and spectral data and of sampling across gradients of intra-individual variation for the accurate prediction of foliar trait distributions across and within canopies using imaging spectroscopy.

Description: Pterocarya fraxinifolia (Poir.) Spach (Juglandaceae) is a model relict tree species native to South Caucasus and is a typical element of threatened riparian forests. Intensive land transformations, which are common in Transcaucasia, have resulted in loss of natural habitat and population decline of the species. One of the methods of ex situ conservation is seed banking. Cryopreservation in liquid nitrogen (−196 °C) is of particular interest, as it allows safe preservation of valuable plant genetic resources. However, the feasibility of seed cryopreservation is related to the desiccation tolerance and intrinsic composition of the seeds. In this study, we examined the physiological traits of Pterocarya fraxinifolia seeds, for which desiccation tolerance is unknown or controversial, and their feasibility for cryopreservation. Additionally, we tested stratification methods for dormancy assessment. Results showed that seeds survived desiccation to a moisture content of 2.8% with a germination rate of 64%. Stratification at a temperature of 3 °C for 8 weeks proved to be both fast and effective. Seed moisture content ranging from 2.8% to 18.1% was determined to be safe for cryopreservation. There was no difference in seedling emergence in seeds stored for 1 year regardless of the storage temperature (−3, −18, or −196 °C). Based on our results, Pterocarya fraxinifolia seeds can be classified as orthodox. This study demonstrates for the first time the feasibility of cryopreserving Pterocarya fraxinifolia seeds.

Description: Blue stain is a type of discoloration that considerably lowers the aesthetic qualities of wood. During harvesting, fungal inoculum finds its way into the wood through places of cutting, delimbing, and damage to the tree stem. The development of peripheral blue stain in the logs of Scots pine (Pinus sylvestris L.) due to damage by a harvester head was investigated, using logs felled and delimbed with a chainsaw as reference. The development of blue stain was related to the age class of the stand, the date of felling, and the microclimatic conditions of the wood storage place. The mean surface area of blue stain in logs produced with the harvester was almost 35 cm2, approximately 30% larger than that of the reference logs. In stands of the fourth age class (diameter at breast height 32 cm), the surface of blue stain was more than two times larger than that of stands of the third age class (diameter at breast height 24 cm). The mean area of blue stain in wood stored after spring felling (19.3 cm2) was about 50% of that after summer felling (38.2 cm2). In particular, the development of blue stain in logs obtained with a harvester was visible between weeks 6 and 9 after spring felling and between weeks 3 and 6 after summer felling. For both felling dates, the range of blue stain depended less on air temperature around the wood stack and depended more on the duration of storage.

Description: Tree height is one of the most important variables for quantitative assessment of forest stocks but is difficult to directly measure. However, such allometric relationships of trees can vary between geographical regions, mainly due to climatic, edaphic, and floristic gradients. Based on the hypothesis that different forest types influence the generic modeling of tree height–diameter relationships on geographical scales, this study aimed to 1) fit equations to estimate tree height in Atlantic Forest types in the state of Rio de Janeiro, Brazil; 2) compare efficiency and precision between generic and specific equations for forest types; and 3) test the effect of different forest types and species on the height–diameter relationship. Four allometric models were tested for all forests (generic) and three main forest types (specific). Effects of tree size, forest types and species on tree height estimation were analyzed using multiple linear models and mixed effect linear models. A significant effect of forest type and species on tree height was seen, showing the need to apply local specific equations to minimize the effects that are not captured by generic equations. Differences in tree allometry between forest types were associated with temperature, rainfall, soil and forest structure. These results confirm the effect of the local environment on the height–diameter relationship of trees as found for large scales in tropical forests.

Description: Herbivores impact soil biogeochemical processes, often increasing nutrient cycling rates under high nutrient availability and decreasing nutrient cycling rates under low nutrient availability. These patterns are far from universal, and interactions between habitat fertility and herbivore effects are under continuing investigation. By sampling inside and outside a network of deer exclosures, we determined deer browsing effects on temperate forest soil nitrogen (N) and carbon (C) cycling along a gradient of soil and litter C–N ratios across our network of sites. Deer browsing increased net N mineralization rates in high nutrient environments and decreased N mineralization rates in low nutrient environments, whereas browsing decreased CO2 respiration rates in high nutrient environments and increased CO2 respiration rates in low nutrient environments. Differences in deer browsing effects on soil processes could be explained by plant responses to herbivory across gradients of resource availability. To our knowledge, our study is one of the first to show that deer browsing can have significant effects on net N mineralization and C respiration in temperate forest soils and that the direction and magnitude of deer browsing effects on soil N and C cycling vary across fertility gradients.

Description: We consider the problem of tactical forest management over a 5-year horizon with yearly periods. The main decisions made consider which harvest areas to cut in each period, the flow of timber from an area to each wood-processing mill to satisfy its annual demand, and which roads to build to access a harvest area not connected to the existing road network. The goal is to minimize the total transportation and road-building costs subject to budget limitations. To explore the benefits of economies of scale (EOS) in road construction, we incorporated this notion in the proposed model. Then, the efficiency of the obtained solution is compared with the model without EOS. The proposed model is a mixed-integer linear program, including several timber assortments and multiple periods. We validated the model for a realistic case in the context of the province of Quebec. The results demonstrate that consideration of EOS significantly reduces the total cost by about 5.3%. In the EOS solution, the road segments that are built every year are very concentrated in specific parts of the region, allowing a road-building company to take advantage of EOS. Moreover, this solution provides a much more efficient timber transportation plan.

Description: Postfire salvage logging is used to reduce economic losses; however, burned trees are rapidly colonized by wood-boring insects, which reduce the merchantable value of the wood. This study aims to predict wood borer (Monochamus Megerle in Dejean, 1821) attacks after wildfire as a function of rapidly available variables such as tree basal area, stem diameter, and burn severity using the differenced normalized burn ratio (dNBR). In 2011, we sampled 60 black spruce (Picea mariana (Mill.) Britton, Sterns & Poggenb.) or jack pine (Pinus banksiana Lamb.) plots in five burns from 2010 in the Haute-Mauricie region of Quebec, Canada. A 50 cm bole section was debarked on seven trees in each plot to estimate wood borer attack density. Wood borer attacks were more abundant in black spruce than in jack pine. As a continuous variable, dNBR unveiled a quadratic effect of burn severity on attack density in black spruce, which was higher at moderate burn severity. In jack pine, the highest levels of attack density were found at high burn severity. Models produced in this article will help forest managers to better prioritize areas for salvage logging and thus reduce economic losses due to wood borer activity.

Description: Les forêts protégées ivoiriennes fournissent des services écosystémiques aux gestionnaires ainsi qu’aux populations riveraines. Cependant, leur gestion connaît de nombreuses difficultés du fait de leur infiltration illégale pour l’agriculture. Ces différentes conversions des classes d’occupation du sol ont modifié les différents services d’approvisionnement des forêts domaniales en général et des forêts classées en particulier. Cette étude a pour objectif d’évaluer les services d’approvisionnement fournis par les plantes de la forêt classée du Haut-Sassandra (FCHS) dans le Centre-Ouest ivoirien, en comparant les bénéfices issus de la FCHS en 2019 à ceux tirés de cet espace en 2000. Les dynamiques spatiotemporelles des formations végétales ont été analysées et ont mis en exergue la progression des exploitations cacaoyères (951,51 % de progression) au détriment des forêts (92,08 % de régression) entre 2000 et 2019. Les enquêtes socioéconomiques ont révélé que cette augmentation des surfaces cacaoyères a entrainé des pertes de 98,11, 93,18 et 78,67 % d’espèces respectivement utilisées pour l’artisanat, la construction et la pharmacopée traditionnelle et une augmentation des services d’alimentation liés aux espèces agricoles. Cependant, ces bénéfices ne profitent pas à l’ensemble des communautés présentes dans la zone d’étude.

Description: Attributes of deadwood in forests, including quantity, landscape position, and state of decay, influence numerous ecosystem processes such as wildfire behavior, tree regeneration, and nutrient cycling. Attributes of deadwood that vary over subdiurnal time steps, including moisture, have not been routinely measured despite the profound effects they have on ecosystem processes. To improve our understanding of forest deadwood subdiurnal moisture dynamics, we installed an intensive time-domain reflectometry (TDR) sensor network in a log and surrounding soil within a northern hardwood forest in New England, United States. Intensive monitoring during a partial growing season indicated that deadwood moisture was dynamic but similar to that of surrounding soils at 15-min intervals, especially during wetting and drying events. Field results and bench analysis of the sample log revealed numerous challenges when attempting to monitor deadwood moisture with TDR such as heterogeneous and (or) advanced decay confounding TDR moisture measurements in logs. An efficient, high-frequency TDR sensor network was demonstrated to record deadwood and soil moisture fluctuations, which provides an opportunity to refine our understanding of deadwood dynamics in the context of global change such as changing precipitation regimes.

Description: Weibull distributions have been widely used to describe tree stem diameter distributions. However, there is a scarcity of studies that suggest the best Weibull formulation. The parameters of the Weibull distribution are usually predicted by either the parameter prediction method (PPM) or the parameter recovery method (PRM), although other methods have been proposed. Thus, this study aimed to evaluate the performance of eight Weibull formulations and compare methods of parameter prediction to describe diameter distributions of clonal eucalypt stands in Brazil. Data originated from remeasurements of 56 plots at ages 3, 5, and 6 years. Weibull distributions were fitted using the maximum likelihood method and evaluated in a goodness-of-fit indicators ranking. The right-truncated two-parameter formulation showed the best results and was used to evaluate the methods of parameter prediction. Stand attributes showed a strong relationship with shape and scale parameters. Regression models were developed and resulted in accurate estimates using PPM. PRM used a growth and yield system to estimate the stand attributes, followed by the moment-based method. The modified cumulative distribution function regression (CDFR) approach was also evaluated, and it presented the poorest results. Although the PPM showed excellent results, PRM is recommended in older stands with inventory because it implicitly promotes compatibility among stand attributes.

Description: The size structure of tree populations making up a forest stand provides a scientific basis for evaluating the forest resources and scheduling future silviculture treatments. We evaluated the efficiency of the skewed Student’s t (ST) model to predict the distributions of various complex diameter at breast height (DBH) data. The ST model was compared with finite mixtures of selected functions (gamma, log-normal, and Weibull). Additionally, two scenarios were employed to determine the number of components: (1) the use of the Bayesian information criterion and (2) visual analysis of the histogram of the DBH relative frequencies. The ST model demonstrated the highest degree of flexibility for fitting the DBH distributions. It outperformed other competitors in modeling the DBH variables in terms of all implemented scenarios. It possesses a high degree of flexibility. This model should be used to fit the DBH distributions of multigeneration forest patches with diverse size structures.

Description: Widespread, rapid aspen (Populus tremuloides Michx.) mortality since the beginning of the 21st century, sometimes called sudden aspen decline (SAD), has been documented in many locations across North America, but it has been particularly pronounced in the southwestern United States. We investigated the relationship among aspen growth, mortality, and climate across three forest types in northern Arizona using cross-dated tree-ring samples from 126 live and 132 dead aspens. Aspen growth was negatively correlated with warm temperatures and positively associated with higher precipitation. Using survival analysis techniques to investigate the links between aspen mortality, tree traits, and climatic conditions, we found that tree traits played a larger role in mortality risk than climate factors. Trees with larger diameters, older trees, and trees with faster growth rates over the past 50 years had a reduced risk of mortality. Management actions aimed at maintaining the most vigorous, fastest growing aspen in the region could help mitigate the impacts of a warmer, drier future.

Description: Ice storms cause widespread damage to forests in many temperate regions, leaving behind many live trees with severe crown damage. Following a severe ice storm in 2014 that damaged forests across Slovenia, we examined how tree-level attributes influenced survival and crown rebuilding three growing seasons after the storm. Field sampling was carried out in four mature stands dominated by native broadleaf species. Of the 763 sampled trees, the annual mortality rate following the storm was 2.2%, and nearly all trees that died experienced 〉75% crown removal. Oak (Quercus petraea (Matt.) Liebl.) and chestnut (Castanea sativa Mill.) had higher rates of mortality than beech (Fagus sylvatica L.) and maple (Acer pseudoplatanus L.). Mixed models revealed that survival significantly increased with tree diameter and decreased with increasing crown damage. Although we observed sprouting across all the dominant species, maple, oak, and chestnut showed a more vigorous response than beech, and maple had the fastest sprout growth. Model results showed that sprout density and length increased with level of crown damage. The results indicate that these broadleaf forests are resilient to severe ice damage. Consequently, hasty salvage cutting of trees with canopy damage should be avoided, as many individuals with 〉75% crown damage are likely to survive and recover.

Description: The use of thermally modified timber (TMT) in outdoor applications is well established, but its performance against the stresses of outdoor conditions is not comprehensively understood. This study investigates the changes in density, surface chemical composition, color, equilibrium moisture content (EMC), checking, hardness, and cupping of thermally modified boards of Scots pine (Pinus sylvestris L.), Norway spruce (Picea abies (L.) H. Karst.), and European ash (Fraxinus excelsior L.) during a two-year weather exposure test in Eastern Finland. Unmodified pine, spruce, and ash and copper salt impregnated pine boards were used as controls. The results show that a two-year weather exposure period causes degradation of hydrophobic lignin, and the leaching of the degraded compounds changed the color, increased the EMC, and decreased the hardness of specimens. Although the EMC of TMT specimens was lower compared with unmodified and impregnated ones during weathering, the changes were more obvious in TMT than in the controls. More checks occurred in the TMT specimens than in unmodified ones after the exposure. On the other hand, the TMT specimens had a lower degree of cupping. These findings also indicate that an increase in modification temperature induces more checks but improves the durability of all studied species by reducing the chemical degradation, color change, cupping, and hygroscopicity during weather exposure.

Description: Warming global temperatures are expected to strongly influence plant communities, yet there is limited knowledge of how these changes will interact with stressors such as the invasion of exotic earthworms. We conducted a small-scale microcosm experiment to assess the individual and interactive effects of warming and exotic anecic earthworms (Lumbricus terrestris L.) on the growth of sugar maple (Acer saccharum Marsh.) seedlings. After 50 days, the elevated-temperature chamber created warmer and drier soil conditions and increased several measures of plant growth, including stem width, ratio of stem width to stem height, stem biomass, and fine-root biomass. Earthworms did not have any clear impacts on plant growth on their own nor in interactions with the temperature chambers. However, earthworms both reduced surface leaf litter cover and exposed soils, which could exacerbate evaporative losses and moisture stress in field soils resulting from a warming climate under different growing conditions. Future studies should consider the long-term effects of earthworm–temperature interactions on sugar maple growth, as well as diurnal and seasonal changes in temperature.

Description: Using data from the National Council of Real Estate Investment Fiduciaries (NCREIF), we examine market integration of commercial real estate and timberland–farmland assets via the Fama–MacBeth two-step approach under the intertemporal capital asset pricing framework. In addition, we study the information transition dynamics between those markets via the vector error correction model (VECM). We find evidence of market segregation and one-way information flow from the timberland–farmland market to the commercial real estate market. We conclude that commercial real estate and timberland–farmland assets are driven by different market fundamentals and that lagged timberland–farmland returns can help predict current commercial real estate returns. The only exception is during market downturns when commercial real estate and timberland–farmland markets are somewhat integrated and driven by some factors that are not specified in this study.

Description: The main purpose of this study was to study spatial and competition effects on estimates of genetic parameters, as well as on selection options for growth traits, including height (H), diameter at breast height (DBH), and volume (V), in a progeny test of Japanese larch at age 20. We compared performances among the individual tree additive genetic base model (B) with design factors only, the spatial effect model (AR1), competition model (C), and combined spatial and competition model (CS). Spatial heterogeneity had significant effects on growth traits; plot variance decreased by more than 80% in the AR1 model relative to base model. Competition had significant effects on DBH and V, but a smaller effect on H. In the C model, direct additive genetic variances for DBH and V increased by 205% and 93%, respectively, whereas residual variances decreased by 8% and 6%. In the CS model, the correlations between direct and competitive genetic effects were 0.83, −0.97 and −0.98 for H, DBH and V. Competition significantly affected the forward selection. The proportions of selected elite trees were only 39% and 25% common between the B and CS models for DBH and V when selection intensity was 5%. For breeding selection, depending on thinning regimes planned, trees of high additive breeding values, but low competitive breeding values are preferable for plantation.

Description: Tree and stand volume estimates are relevant for forest inventories, forest sales, and carbon stock evaluations. Forest practice commonly uses generalized stem-wood volume functions; however, such generalized approaches neglect the stem form in detail. Hence, trees of a given species with the same diameter at breast height (d1.3) and height (h) are always assumed to have the same form factor and thus the same volume. This case study focused on stem form variation of Norway spruce (Picea abies (L.) Karst.) due to competition effects. Using terrestrial laser scanning (TLS), we measured the stem shape of 868 trees from a long-term spacing and thinning experiment in Germany. The plots covered a broad density range. We analysed the effect of competition and compared the TLS-determined stem volume estimates with those determined conventionally. TLS-based volume estimations showed that the lower the competition was, the lower the tree volume was with a given d1.3 and h. Commonly used functions underestimated the volume stock overall by 4.2%, disregarding any levels. At plot level, underestimation varied from 0.7% to 7.0%. At tree level, the volume was under- and over-estimated by −10% to +10%, respectively. The more precise the examination was, the more suitable the application of TLS was for enhancing volume estimation.

Description: Models for prediction of site index (SI) typically include only abiotic causal variables (e.g., soil) and lack biotic response variables (e.g., vegetation), which could exhibit greater sensitivity to important environmental factors affecting tree height growth. Our study objective was to evaluate Whittaker’s moisture condition index (MCI) (R.H. Whittaker. 1956. Ecol. Monogr. 26: 1–80) as a potential biotic variable for inclusion with conventional abiotic variables in oak (Quercus L.) SI prediction models. The MCI is the sum of relative abundances of inventoried plot tree species weighted by their moisture affinity classification. We compared regression parameters of conventional base models including only abiotic variables with exploratory models configured with abiotic variables and MCI for explaining variation of SI. The best abiotic model included only aspect. When MCI was included in the abiotic model, aspect became insignificant, resulting in a single-variable biotic model that accounted for increased SI variation. The MCI biotic model remained significant when tested with independent data from a distant location. The MCI is easily calculated using plot inventory data, and with further evaluation, it may be confirmed as a useful biotic variable in combination with abiotic soil and topographic variables for prediction of oak SI.