Forestry Research Research Articles

Contribution of field schools to extensionism in Mexico

Extensionism in Mexico until 2000 was unidirectional, without taking into account the user of the technology or the processes to be transferred. After the introduction of the Field School Model to Mexico, the way of doing extensionism changed, the National Institute of Forestry, Agricultural and Livestock Research (INIFAP), since that year in the implementation of said model and 20 years later through the FORDECyT Projects, Territorial Development (PRODETER) and then through the technical support strategy (EAT ) inserted at the national level as part of the methodology to carry out an extension where the producers were not users but subjects and beneficiaries of the extension process, that is, based on their problems, they decide what to do in their Family Production Units with the technological options available at your disposal. The results indicate that through Field Schools and “learning-by-doing” there is a greater understanding of the technologies and greater expectations of their adoption, given that they work with producers over 53 years old on average. The objective of this work is to relate how this model has permeated public policies and has been inserted into the taste of producers in three strategies of bringing technologies to producers in the Mexican Republic and its contribution to food self-sufficiency and less dependence on external inputs based on the agroecological transition and more environmentally friendly practices.

BEECH FORESTS OF THE "VYZHNYTSKYI NATIONAL NATURAL PARK": CURRENT SANITARY CONDITION AND PROBLEMS OF PRESERVATION

The beech primeval forests of the Vyzhnytskyi National Natural Park are a unique cultural heritage and play a special role for the Carpathian region and Ukraine as a whole, therefore they are strictly protected in the territories of the nature reserve fund, performing ecological, educational and scientific-cognitive functions. In this regard, monitoring the current state of the beech forests of the Vyzhnytskyi National Natural Park and highlighting the problem of their preservation becomes relevant. In the course of conducting research, classical and modern methods of forestry research were used, as well as specific methods of phytosanitary monitoring and comparative ecology. The massif of primeval beech forests of the Vyzhnytskyi National Natural Park is characterized by a remarkable diversity of fungi. We identified fruiting bodies of wood-destroying fungi on the trunks of beech trees: Fomes fomentarius (L. ex Fr.) Gill., Daedalea quercina L. ex Fr., Phellinus igniarius (L.: Fr.) Quel, Laetiporus sulphureus (Bull.: Fr.) Bond. et Sing., Coriolus versicolor (L.) Quél., Stereum hirsutum (Willd.) Pers., Daldinia concentrica (Bolton) Ces. & De Not., Аrmillariella mellea (Vahl) P.Karst., and Pleurotus ostreatus (Jacq.) P.Kumm. Groups of Coprinus micaceus (Fr.) and Hypholoma capnoides (Fr. ex Fr.) Kumm were noted near rotten beech stumps. We also came across a unique find the invasive red-listed Clathrus archeri (Berk.) Dring. In the course of surveys, fruiting bodies of typical representatives of the marsupial class Xylaria polymorpha (Pers.) Grev., and Xylaria hypoxylon (L.: Fr.) Grev). Representatives of xylophilic ascomycetes were identified on the dead trunk of a European beech Bisporella citrina (Batsch) Korf et S.E. Carp. Symptoms of dieback of central shoots and side branches, dieback of European beech bark, which is directly related to the vital activity of Nectria ditissima Tul., were recorded. & C.Tul. Cumulative manifestations of infectious and non-infectious pathologies were noted. The problems of preserving the beech forests of the Vyzhnytskyi National Natural Park should include: intensive and uncontrolled economic activity; irresponsible behavior of tourists (arson, mechanical damage, littering, poaching, etc.); construction of highways and tourist centers in the immediate vicinity of primeval forests; damage to forest stands due to atmospheric air pollution, climate change; significant spread of pests or pathogens of forest diseases; danger of forest fires; recreational load and livestock grazing. Given the role and importance of the beech forests of the Vyzhnytskyi National Natural Park, a comprehensive study of the forest systems is necessary to preserve these unique resources.

Accurate Calculation of Tree Stem Traits in Forests Using Localized Multi-View Registration

Abstract. In recent years, there has been a high demand in forestry and forest research for the accurate measurement of tree traits from point clouds captured by terrestrial laser scanners. However, the reliability of the calculated values is not sufficient due to the difficulty of accurate registration of each tree over a large area of forest. To solve this problem, we introduce localized multi-view registration for correcting the registration matrix of each tree stem. In addition, we discuss methods for registering the whole point clouds of a forest by using the registration matrices locally calculated for tree stems. Especially, we discuss a method to align tree stem points that do not have sufficient overlapping points required in registration. The proposed method was applied to actual forest point clouds and diameter at breast height (DBH) was compared to the manually measured DBH. Experimental results showed that the proposed method was effective in reducing registration errors and in calculating tree stem traits with high accuracy.

The utilization of wood samples from xylarium in historical wooden statues: improving the separation accuracy non-destructive measurement for using several algorithms

There are numerous wooden historical artifacts in Kyoto and other parts of Japan, including Buddhist statues or Shinto deities. The identification of wood species in these historical artifact is desirable for both repair and maintenance purposes. The most common method of identifying wood species involves examining samples taken from the artifacts. However, intentional sampling from old cultural artifacts is prohibited in Japan. As a result, we attempted to determine the wood species of old statues non-destructively using near-infrared spectroscopy (NIRS). In this article, we developed the softwood and hardwood separation model using NIRS to compare the prediction accuracy for few algorithms. The model was created based on wood samples stored in the xylarium of the Forestry and Forest Products Research Institute (TWTw). We then applied this model to old Buddhist statues in order to classify them as either softwood or hardwood. These Buddhist statues were housed in Nazenji temple and are believed to have been carved during the Heian period (8th–12th century). For the near-infrared (NIR) measurements, we collected diffuse reflectance spectra from TWTw sample and Buddhist statues using same spectrometer. Initially, we used the soft independent modeling of class analogy method (SIMCA), partial least squares discriminant analysis (PLS_DA), and support vector machine to analyze the NIR spectra obtained from the TWTw wood samples. Subsequently, we applied the NIR spectra obtained from several Buddhist statues in Nazenji temple to the aforementioned separation model and determined whether spectra data were classified as the softwood or hardwood. Finally, wood specimens detached naturally from the Buddhist statues over time were observed under microscopic analysis to identify the wood species. As comparing the prediction accuracy of few algorithms, SIMCA had a poor result, but PLS_DA had a good result. PLS_DA had better discrimination because it performed calculations to improve regression from both explanatory variables and objective variables.

Integrated Pest Management Decision Support System (IPM-DSS) a tool to support management of tree diseases in Kenya

Tree diseases have been noted as one of the major causes of abnormalities and malformations on perennial plants. Tree disease research in Kenya has resulted in a list of diseases identified to cause significant losses on forest plantations. The need for management of such diseases have been on the increase. The Decision Support System (DSS) was envisioned to help stakeholders make decisions to manage tree diseases on farm and in tree plantations. Information was collected across Kenya on diseases affecting seed, seedlings, plantations, natural forests and post-harvest products in sawmills. The data was entered into excel sheets and organized for database administration on MySQL software. Over 20 major fungal species were identified and their biology, distribution and management determined. This information was further fed into a query system to allow different groups of stakeholders to access the information for diagnosis and control of tree diseases. Results showed that major tree diseases in Kenya were caused by fungi belonging to the families; Botryosphaeriaceae, Nectriaceae, and Amphisphaeriaceae. The data and information availed through this query system is being used in trend analysis for proactive control and management of tree diseases in Kenya. It will also be used for farmer advisory services through closest match selection of symptom appearance based on the tree species. The query system is an innovation that will also be used for Citizen Science Data Capture to aid Kenya Forestry Research Institute in detecting emerging diseases in real-time for phytosanitary measures. The identification of commonly occurring pathogens in commercial forestry species in the country has led to research towards their control and tree improvement for resistance to tree diseases. Future plantation establishment should be based on resistant species and high-quality germplasm for maximum survival and improved yields. Key words: Advisory services, Botryosphaeriaceae, citizen science, Decision Support System, Integrated Pest Management, tree diseases.

Optimizing crown density and volume estimation across two coniferous forest types in southern China via Boruta and Cubist methods

Abstract Quantifying forest stand parameters is crucial in forestry research and environmental monitoring because it provides important factors for analyzing forest structure and comprehending forest resources. And the estimation of crown density and volume has always been a prominent topic in forestry remote sensing. Based on GF-2 remote sensing data, sample plot survey data and forest resource survey data, this study used the Chinese fir (Cunninghamia lanceolata (Lamb.) Hook.) and Pinus massoniana Lamb. as research objects to tackle the key challenges in the use of remote sensing technology. The Boruta feature selection technique, together with multiple stepwise and Cubist regression models, was used to estimate crown density and volume in portions of the research area’s stands, introducing novel technological methods for estimating stand parameters. The results show that: (i) the Boruta algorithm is effective at selecting the feature set with the strongest correlation with the dependent variable, which solves the problem of data and the loss of original feature data after dimensionality reduction; (ii) using the Cubist method to build the model yields better results than using multiple stepwise regression. The Cubist regression model’s coefficient of determination (R2) is all more than 0.67 in the Chinese fir plots and 0.63 in the P. massoniana plots. As a result, combining the two methods can increase the estimation accuracy of stand parameters, providing a theoretical foundation and technical support for future studies.

Essential oils of lavandin (Lavandula x intermedia Emeric ex Loisel.) of Spain: A case study on clones ´Grosso´ and ´Super´

Lavandin (Lavandula x intermedia Emeric ex Loisel.) is a sterile natural hybrid obtained from the crossing of lavender (L. angustifolia Mill.) and spike lavender (L. latifolia Medik.), and its cultivation has gained great importance in Spain. This work is aimed to study the chemical composition of essential oils (EOs) of lavandin from clones ´Grosso´ and ´Super´ cultivated in Spain. For this purpose, 215 EOs, obtained by steam distillation between 2016 and 2022 in agricultural farms located in 13 provinces of Spain, were analyzed by gas chromatography (GC) in three public R&D centers: the Regional Institute for Agrifood and Forestry Research and Development of Castilla-La Mancha (IRIAF), the Agrarian Technological Institute of Castilla y León (ITACyL) and the Agrifood Research and Technology Center of Aragon (CITA). The chemical composition of the EO of lavandin showed great inter- and intra-varietal variability, with the main compounds being linalool, linalyl acetate, camphor and 1,8-cineole. The results showed that the contents of camphor and 1,8-cineole were higher in ´Grosso´ (7.2% vs 5.0% and 5.7% vs 3.8%, respectively), while those of linalool and linalyl acetate were higher in ´Super´ (35.8% vs 34.2% and 33.7% vs 27.2%). Among minor compounds, the lavandin 'Super' exhibited a higher content of β-Z-ocimene and β-E-ocimene, and a lower content of terpinen-4-ol compared to 'Grosso´. Additionally, eleven compounds of lavandin 'Grosso' were compared within the ranges established by ISO 8902:2009 standard, revealing that only 18% of the samples complied with it for all of these compounds. In this sense, the contents of α-terpineol, linalool and lavandulyl acetate were above the upper limit of the standard in respectively 49%, 23% and 21% of the samples. On the contrary, 36% of the samples for β-Z-ocimene and 32% for linalyl acetate were below the range of this regulation. Unfortunately, these discrepancies with the ISO regulation exclude numerous EOs from the market despite their value in different sectors like perfumery, cosmetics, aromatherapy, phytosanitary or pharmacy. This work could serve as a guidance and/or reference study of Spanish essential oil of ´Grosso´ and ´Super´ clones for stakeholders involved in the lavandin EO market.

A dataset for fine-grained seed recognition

The research of plant seeds has always been a focus of agricultural and forestry research, and seed identification is an indispensable part of it. With the continuous application of artificial intelligence technology in the field of agriculture, seed identification through computer vision can effectively promote the development of agricultural and forestry wisdom. Data is the foundation of computer vision, but there is a lack of suitable datasets in the agricultural field. In this paper, a seed dataset named LZUPSD is established. A device based on mobile phones and macro lenses was established to acquire images. The dataset contains 4496 images of 88 different seeds. This dataset can not only be used as data for training deep learning models in the computer field, but also provide important data support for agricultural and forestry research. As an important resource in this field, this dataset plays a positive role in modernizing agriculture and forestry.

Aktivity v oblasti výzkumu a vývoje u podniků v lesním hospodářství v České republice

Research, development and innovation are generally formulated as priority attributes of economic growth, competitiveness and, therefore, improvement of living standards and social conditions all over the world. According to the Czech Statistical Office, the main source of funding for research, development and innovation in the Czech Republic are domestic and foreign enterprises. The emergence and history of forestry research in the Czech Republic has a remarkable and deep tradition, enhanced by the longevity of natural and production processes in forestry, not least because of the accentuated social importance of forest and forestry functions. The paper focuses on the research and development activities of selected forestry companies in the Czech Republic. The analysis included the state enterprise Lesy České republiky (Forests of the Czech Republic, s.e.), enterprises in the position of so-called contractual partners (in the outsourcing business model) and companies carrying out management activities in municipal forests. The basic methodological approach was the analysis of publicly available information on research and development reported by the enterprises concerned as so-called non-financial information in their annual reports for the years 2014–2020, on the basis of Act No. 563/1991 Coll., on accounting.

ANALYSIS FOR MULTIPLE RESPONSES IN A COMPLETELY RANDOMIZED EXPERIMENTAL DESIGN

Multiple responses are often generated in agricultural and forestry research. For example, the moisture content, fatty acids, carbohydrates, size, diameter, length, shape and hardness, among other characteristics are measured to cottonseed. Of course, multiple responses are observed in many other areas of research. Multivariate analysis of variance (MANOVA) can be useful for multiple response analysis when differences in treatment effects are to be determined. However, the performance of current post hoc tests in this context is not satisfactory due to the limitations of the available methods, or because they are difficult to use for non-statistician researchers. Furthermore, this methodology requires the assumptions of multivariate normality and homogeneity of variance and covariance matrices, assumptions that are difficult to verify if the sample size is small. This research proposes an alternative analysis to test the hypothesis of equality of effects between treatments and post hoc tests in the case of multiple responses. An asymptotic result is demonstrated for the random variable generated in the proposal for the case of uncorrelated normal variables and the case for correlated normal random variables is left open. A simulation study shows that the performance of the proposal with small samples is satisfactory in terms of power and that it has advantages compared to MANOVA. Furthermore, the methodological approach allows for post hoc testing in the case of multiple responses in the completely randomized experimental design.

Evaluating the Point Cloud of Individual Trees Generated from Images Based on Neural Radiance Fields (NeRF) Method

Three-dimensional (3D) reconstruction of trees has always been a key task in precision forestry management and research. Due to the complex branch morphological structure of trees themselves and the occlusions from tree stems, branches and foliage, it is difficult to recreate a complete three-dimensional tree model from a two-dimensional image by conventional photogrammetric methods. In this study, based on tree images collected by various cameras in different ways, the Neural Radiance Fields (NeRF) method was used for individual tree dense reconstruction and the exported point cloud models are compared with point clouds derived from photogrammetric reconstruction and laser scanning methods. The results show that the NeRF method performs well in individual tree 3D reconstruction, as it has a higher successful reconstruction rate, better reconstruction in the canopy area and requires less images as input. Compared with the photogrammetric dense reconstruction method, NeRF has significant advantages in reconstruction efficiency and is adaptable to complex scenes, but the generated point cloud tend to be noisy and of low resolution. The accuracy of tree structural parameters (tree height and diameter at breast height) extracted from the photogrammetric point cloud is still higher than those derived from the NeRF point cloud. The results of this study illustrate the great potential of the NeRF method for individual tree reconstruction, and it provides new ideas and research directions for 3D reconstruction and visualization of complex forest scenes.

Sensitivity of long-term productivity estimations in mixed forests to uncertain parameters related to fine roots

Forest growth models are increasingly being used in forestry and ecology research as predictive tools to help developing practical guidelines and to improve understanding of the drivers of forest ecosystem functioning. Models are usually calibrated using parameters directly obtained or estimated from empirical field observation, and hence are subject to uncertainty. Thus, output accuracy depends on input parameters precision and on how influential is each parameter on model behaviour. Hence, it is important to analyse parameter-related uncertainty and its effects on model outputs. This can be done by performing sensitivity analyses, which allow to explore the influence of one or several calibration parameters on model outputs. As studies on tree root parameters are particularly scarce, the aim of the present work was to evaluate the influence of parameters related to fine roots on estimations of long-term forest growth patterns in pure and mixed forests, using FORECAST (a hybrid forest growth model) as a virtual lab. The fine root parameters assessed were biomass, turnover rate, and nitrogen content. The analysis was performed by simulating monospecific stands of two contrasting species (Pinus sylvestris L. and Fagus sylvatica L.), and mixed stands formed by both species. In all cases, FORECAST showed good capability to contain uncertainty propagation during the first and middle stages of stand development (<40 years). After that moment, model output uncertainty steadily increased, but it reached different maximum uncertainty levels depending on stand type. Simulations of the less nutrient demanding P. sylvestris manifested very little sensitivity when growing in monospecific stands. However, F. sylvatica monospecific stands showed intermediate sensitivity, but significant species interactions occurred in mixed stands that determined the biggest impact detected of uncertainty related to fine root parameters over model outputs. All things considered, FORECAST displayed an interesting capability to capture some of the interspecific interactions that are key in mixed forests functioning. Our results suggest an acceptable model performance under uncertain parameterization but also caution against expecting accurate quantitative estimations of forest growth, especially when considering long-term scenarios in complex mixed stands.

Enhanced Seedling Growth and Physiological Performances of Melia azedarach L. by Foliar Application of 24-Epibrassinolide under Salt Stress

Salinity is a serious environmental problem following a worsening trend. This study investigates the role of 24-epibrassinolide(EBR) in regulating plant growth and physiological performances, particularly in alleviating the negative effects of salt stress. Melia azedarach L. seedlings from two seed sources, Sheyang (SY) and Xiashu (XS), were exposed to sea salt and treated with different concentrations of EBR within a 60-day period. The results demonstrate that appropriate EBR application improved the seedlings’ stress tolerance by promoting growth and physiological systems. In terms of the relative increment, it showed that a difference of 1.45% and 1.13% in the SY and XS groups was the positive effect of the highest EBR treatment concentration. As for diameter growth, the difference observed was 2.51% and 1.80% for the SY and XS groups, respectively. In all physiological measurements, including the content of photosynthetic pigments, water relations, membrane stability, osmolytes and antioxidant enzymes, significant changes generally observed between salt stress alone and the highest EBR treatment concentration. A better performance was observed in the SY seed source, which is of a coastal nature. These findings contribute to our understanding of Melia azedarach’s adaptation to changing environments and provide potential for further molecular studies as well as valuable insights for forestry, agricultural and ecological research.

Genotyping of Vanilla planifolia Jacks ex Andrews from the Totonacapan region using Inter-Simple Sequence Repeat markers

Vanilla is the only genus of plants in the Orchidaceae family used in the food industry, being the most widely used flavoring worldwide and the second most valuable economically. Cultivation is of great biocultural importance in the Totonacapan region, in the state of Veracruz, as this region is considered its center of origin and distribution. However, little is known regarding the number of genotypes present in this area, as well as the genetic diversity, which is vital for the improvement of this crop. Therefore, the objective of this study was to perform the genotyping of 60 Vanilla planifolia accessions from the Germplasm Bank of The National Institute of Forestry, Agriculture, and Livestock Research (Instituto Nacional de Investigaciones Forestales, Agrícolas y Pecuarias - INIFAP), Experimental Field Ixtacuaco, which were selected and collected in the Totonacapan region. For this purpose, the number of V. planifolia genotypes was determined based on ISSR (Inter-Simple Sequence Repeat) molecular markers. Three DNA extraction protocols from plants and fungi described in the literature were evaluated, and a fourth protocol was adapted with different procedures from the previous protocols, seeking to obtain a high concentration and good quality and integrity. Once quality DNA was obtained, fourteen ISSR primers were evaluated, of which three primers that showed the highest number of amplified bands were selected. Subsequently, the genotyping of the 60 accessions was carried out, resulting in nine genotypes with primer 808 and six genotypes with primers 812 and 856. These results allowed the genotyping of Vanilla planifolia accessions with ISSR markers, which will help evaluate the genetic diversity of this crop in the Totonacapan region in the future.

&lt;i&gt;Diospyros&lt;/i&gt; &lt;i&gt;crassiflora&lt;/i&gt; (HIERN) surface and subsoil leaf litter decomposition pattern along a time gradient in a humid rainforest

Litter decomposition is a crucial bedrock of nutrient recycling, organic matter accumulation, soil physicochemical properties, biodiversity and life support of forest and agroforestry systems. We therefore investigated &lt;i&gt;Diospyros&lt;/i&gt; &lt;i&gt;crassiflora&lt;/i&gt; surface and subsoil leaf litter decomposition pattern along a duration gradient in a humid rainforest. The study was conducted in the nursery of the humid forest research station of the Forestry Research Institute of Nigeria (FRIN) in Umuahia, Abia State. One gram (1g) of &lt;i&gt;D.&lt;/i&gt; &lt;i&gt;crassiflora&lt;/i&gt; fresh leaf litter was placed on the surface and subsoil of 4kg of topsoil contained in 32cm x 20cm polyethene bags; there were a total of 108 bags in a completely randomized experimental design layout and the treatments were the duration gradient of litter decomposition which were: 2, 4, 6, 8, 10, 12, and 14 weeks; on each of the duration, litter was collected from nine of the polyethene bags for laboratory analysis and estimate of decomposition rate. The results showed a significantly high initial decomposition rate (3.19±0.13 %day-1; 4.28±0.03 %day-1) in the 2 week duration followed by significant continuous decline until the lowest (0.04±0.00%day-1; 0.28±0.02%day-1) in the 14 week in the surface and subsoil respectively. There was a positive correlation (r=0.80) in decomposition rate between the surface and subsoil leaf litter, which yielded a model with a significant R2 (0.64), for site-specific estimates of decomposition rate &lt;i&gt;D.&lt;/i&gt; &lt;i&gt;crassiflora&lt;/i&gt; leaf litter. A steeper and smoother subsoil cumulative percentage decomposition curve showed that leaf litter decomposition was significantly faster in the subsoil than surface soil.&#x0D;

Модель образующей древесного ствола сосны обыкновенной (Pinus sylvestris L.), произрастающей в Костромской области

Models of the stem taper have become widespread in forestry research. Models of the stem taper based on the equations of the stem taper are capable of determining with sufficient accuracy the assortment potential of forest stands. For the Kostroma region, no work has previously been carried out aimed at modeling the stem taper of trunks. Therefore, the goal of the study was to search and justify models of the stem taper of a tree trunk with one equation that most correctly describe the change in tree diameter with height in Scots pine stands growing in the Kostroma region. As experimental data, 10064 measurements of the diameter of 692 pine trees were obtained. To carry out the analysis, 19 models of tree stem taper with one equation were selected. Calculations were carried out in the Python environment. The calculated values of quality metrics, graphical analysis of residuals and errors made it possible to establish that the four-parameter model most adequately describes of the stem taper of pine forest stands in the Kostroma region. The stem diameter predicted using the model at any height makes it possible to analyze the assortment structure without resorting to tree felling. Further research is required aimed at developing standards for the assortment structure of trunks based on the proposed stem taper model.

Influence of habitat, density, lignin structure, and extraction treatment on thermal-softening properties of water-swollen wood: a study of 87 wood specimens

Abstract This study aims to reveal the diversity of thermal-softening temperatures and identify the factors that determine this temperature. To achieve this, the thermal-softening properties of the radial direction of wood were measured under water-saturated conditions for 15 softwood and 72 hardwood specimens. Wood samples were obtained from the xylarium of the Forestry and Forest Products Research Institute, Japan. A dynamic viscoelastic measurement was performed on samples with uniform heating and cooling history because the difference in cooling rate can alter in the mechanical properties of wood. The storage and loss elastic moduli increased linearly as wood density increased, regardless of the wood species. However, the thermal-softening temperature (defined in this study as the peak temperature of loss tangent) was unrelated to the density, anatomical features, species, latitude, and annual rainfall in the habitat. When the relationship between thermal-softening temperature and lignin structure was investigated, a negative correlation was observed between the thermal-softening temperature and the syringyl ratio (syringyl/(syringyl+guaiacyl)) of lignin aromatics. This indicates that the thermal-softening temperature is higher for wood species with denser lignin structures, supporting the prior research showed correlation between thermal-softening temperature and methoxyl group content of wood.

UAVs for forestry: Metric-semantic mapping and diameter estimation with autonomous aerial robots

To properly monitor the growth of forests and administer effective methods for their cultivation, forestry researchers require access to quantitative metrics such as diameter at breast height and stem taper profile of trees. These metrics are tedious and labor-intensive to measure by hand, especially at the scale of vast forests with thick undergrowth. Autonomous mobile robots can help to scale up such operations and provide an efficient method to capture the data. We present a set of algorithms for autonomous navigation and fine-grained metric-semantic mapping with a team of aerial robots in under-canopy forest environments. Our autonomous UAV system has 3D flight capabilities and relies only on a LIDAR and an IMU for state estimation and mapping. This allows each robot to accurately navigate in challenging forest environments with drastic terrain changes regardless of illumination conditions. Our deep-learning-driven fine-grained metric-semantic mapping module is capable of detecting and extracting detailed information such as the position, orientation, and stem taper profile of trees. This map of tree trunks is represented as a set of sparse cylinder models. Our semantic place recognition module leverages this sparse representation to efficiently estimate the relative transformation between multiple robots, and merge their information to build a globally consistent large-scale map. This ultimately allows us to scale up operations with multiple robots. Our system is able to achieve a mean absolute error of 1.45 cm for diameter estimation and 13.2 cm for relative position estimation between a pair of robots after place recognition and map merging

The main forest species encountered in southern and central Benin, West Africa.

The south of Benin, a country in West Africa, is still home to remnants of dense forests that benefit from a particularly rainy sub-equatorial climate, with annual rainfall of up to 1,200 mm. These forest ecosystems are an integral part of the West African forest block, which stretches from Liberia to Togo. However, despite their richness and ecological importance, these forests are unfortunately subject to strong human pressures, particularly from slash-and-burn agriculture, intensive logging and the growing urbanisation of coastal areas. Preserving these forests is crucial, however, as they are home to remarkable plant and animal biodiversity, with many endemic species. What's more, these forests play an essential role in regulating the local climate, protecting soil and water resources, as well as providing local populations with a vital source of energy wood, non-timber forest products and support for their traditional agricultural practices. Faced with these conservation challenges, identifying and characterising the main tree species found in the forests of southern and central Benin, forest species and their ecology is an essential prerequisite for implementing sustainable management and restoration strategies for these threatened forest ecosystems in southern Benin. This work aims to identify and draw attention to the different forest species, specially tree forest species present in southern and central Benin. The dataset provides information on forest species found in southern and central Benin, West Africa. This dataset is extremely useful for forestry research, as it focuses mainly on the various forest species of major importance. It can be used as a basis for characterising individuals or populations of species, based on their abundance in relation to anthropogenic pressure and changes in environmental conditions.These species are characteristic of forests and, above all, are of particular interest both to populations and to managers of protected areas. Field collections were initiated in 2007 as part of natural forest inventory work. The data collected have been completed by various field works that followed this work on forest species in southern Benin. The latest version of the dataset is publicly and freely accessible on the GBIF website at the address https://www.gbif.org/dataset/aff3a10a-a86b-4eff-98e4-d63f92fd6f7e.It should be noted that the fact that the collection and monitoring were carried out in southern Benin, a region known for its great diversity of species, over a period of 10 years making these data particularly relevant information to study the effects of climate change and human pressure on ecosystems in this area.

Journal of Forest Business Research: a leading platform for advancing forest business and investment science research

The Journal of Forest Business Research (JFBR), an international peer-reviewed and open-access journal, has been developed to offer a novel publication avenue for forest business research contributions. This effort has been motivated by the realization that there were no dedicated forest business scientific journals in existence and the need to have a scientific journal to support growing volume of forest business research. The journal aims to effectively meet the needs of contributors and readers by bringing together academic and professional business research in forestry. The following section describes why there is a need for the JFBR and what makes this journal a leading platform for advancing forest business and investment science research. Then, we summarize all the papers included in our two issues in 2023. This year, we delivered to hands of our readers over 340 pages of high-quality forest business and investment science research. The articles published in 2023 discussed, among others, forest carbon and its contribution to total timberland investment returns, capital investment and annual expenditures related to forests in the United States (U.S.), wood pellet manufacturing industry from residents’ perspectives in the U.S. South, discount rates in forest management decisions, the effect of various COVID-19 policies on standing timber prices in the U.S. South, the relationships between innovation constructs and demographic and management attributes of wood furniture firms in Kenya, the economic feasibility of silviculture investments to reduce butt rot and ungulate browse damage in Canada, the sustainability of the production, processing, and exporting systems of frankincense (Boswellia papyrifera) in Ethiopia, and the development of the Iranian wood products industry over the past two decades. All these articles truly show the international character of forest business research. In the final section, we indicate what types of articles we are seeking and how you can support our efforts.