Hasil untuk "Forestry"

J. Barceló, C. Poschenrieder

R. Guha

D. Nepstad, Georgia O. Carvalho, A. Barros et al.

Arun Agrawal, Elinor Ostrom

D. Jiang, Ying Wang, Bin Li et al.

Dr. D. Jiang, Y. Wang, Prof. B. Li, Prof. C. Sun, S. Qi College of Science Northeast Forestry University Harbin 150040, P. R. China E-mail: libinzh62@163.com Prof. B. Li Post-Doctoral Mobile Research Station of Forestry Engineering Northeast Forestry University Harbin 150040, P. R. China Dr. Z. Wu Key Laboratory of Engineering Dielectrics and Its Application Ministry of Education Harbin University of Science and Technology Harbin 150040, P. R. China E-mail: zijian.wu@hrbust.edu.cn Prof. H. Yan School of Mechatronics Engineering Harbin Institute of Technology Harbin 150001, P. R. China Dr. L. Xing MIIT Key Laboratory of Critical Materials Technology for New Energy Conversion and Storage School of Chemistry and Chemical Engineering Harbin Institute of Technology Harbin 150001, P. R. China Prof. Y. Li College of Materials Science and Engineering North University of China Taiyuan 030051, P. R. China

Laura Nikinmaa, Laura Nikinmaa, Marcus Lindner et al.

Loukaiya Zorobouragui, Loukaiya Zorobouragui, Isidore Houaga et al.

Understanding farmers’ breeding systems and preferred traits is crucial for establishing effective genetic improvement programs. This study investigated Gudali cattle breed selection, breeding objectives, and selection criteria in North-east Benin (Malanville and Tchaourou). We surveyed 120 Gudali cattle farmers using a structured questionnaire and conducted hierarchical clustering using R software. We identified the distribution of farmers based on herd composition and production systems. Farmers were grouped into four classes: Sedentary Purebreds (16.67%), Transhumant Purebreds (33.33%), Sedentary Mixed Breeds (34.17%), and Transhumant Mixed Breeds (15.83%), with average Gudali herd sizes ranging from 23.68 to 90.11 heads depending on the system. The overall average herd size was 42.67 ± 6.00 heads. The majority of farmers owned different breeds, including Borgou (26.67%), Yakana (26.67%), and Azawak (7.5%), with only 32.5% having Gudali only herds. Farmers chose Gudali cattle for their milk production, good growth and market value, with 96.67% prioritizing milk production. The main selection criterion was coat color in all breeding systems with respective indices of 0.59; 0.57; 0.54 and 0.47 respectively for sedentary purebred; sedentary mixed breed; transhumant purebred and transhumant mixed breed systems. Most mixed breed farmers (55.84%) cross Gudali with local breeds for better dairy performance. While only 3.33% of farmers were aware of community-based breeding programs (CBBP), there was strong interest (95%) in participating. Potential challenges such as access to feed and disease management were reported. The proposed mitigation strategies include establishing pasture areas and strengthening collaboration among stakeholders. Implementing CBBP programs by incorporating farmers’ preferences and practices, could sustainably improve Gudali cattle productivity and resilience in Benin.

Stefanie Simpson, Lindsey S. Smart, Lindsey S. Smart et al.

Blue carbon ecosystems, such as mangroves, tidal marshes, and seagrasses, are important for climate mitigation. As carbon sinks, they often exhibit higher per hectare carbon storage capacity and sequestration rates than terrestrial systems. These ecosystems provide additional benefits, including enhancing water quality, sustaining biodiversity, and maintaining coastal resilience to climate change impacts. The widespread loss of blue carbon ecosystems due to anthropogenic activities can contribute to increasing carbon emissions globally. Monetizing blue carbon through carbon credits offers an avenue to generate revenue and incentivize conservation and restoration efforts. However, limited data on project costs and carbon benefits make prioritization of blue carbon projects challenging. To address these challenges, we have developed, in collaboration with blue carbon experts, the Blue Carbon Cost Tool. This is a user-friendly interface enabling comparison of three core market project components – 1) carbon credit estimation, 2) project cost estimation, and 3) a qualitative, non-economic feasibility assessment – to assess and compare potential for blue carbon projects. Tool simulations with data available from nine countries demonstrate (a) how factors such as country, ecosystem type and project scale drive variability, (b) the need for local or project-specific data to enhance accuracy and reduce uncertainty, particularly in tidal marsh and seagrass systems, and (c) that higher price tolerance or upfront capital is needed to bridge implementation and maintenance cost gaps. The Blue Carbon Cost Tool can aid project developers and investors to better understand market opportunity and the resources needed to develop high quality blue carbon market projects.

Guozhe Zhang, Yu Zhao, Zhiqiang Wu et al.

Lagerstroemia indica is popular for its bright flower colors and long bloom period. However, although L. indica has a long flowering period, the flowering time of a single flower is short, lasting only 1−2 d. Petal expansion is a key process that affects the length and ornamental quality of the flowering period. However, the molecular mechanism of petal expansion in L. indica remains unclear. The molecular mechanisms underlying flower opening in L. indica were investigated through transcriptome sequencing of flower buds and blooms at four developmental stages. Analysis of differentially expressed genes (DEGs) indicated enrichment in cellular processes, metabolic regulation, and biological signaling pathways. KEGG pathway analysis revealed significant roles for carbohydrate, lipid, and amino acid metabolism in the flowering process. Additional pathway analysis identified key genes and processes related to carbohydrate utilization, hormone signaling, water transport, and cell wall expansion that contribute to petal opening regulation. A comprehensive examination of the expansin gene family proteins, known for promoting cell wall loosening and extension, identified 27 expansin genes in L. indica, which were categorized into four subfamilies with conserved structures and motifs. Of these, LiEXPA10, LiEXPA19, LiEXLA1, and LiEXLA2 showed heightened expression in the later stages of flowering (S3−S4), suggesting a central role in petal expansion. Functional validation in Arabidopsis thaliana demonstrated that LiEXLA1 and LiEXLA2 promote accelerated flowering and enhanced petal expansion in transgenic lines. These findings offer new insights into the genetic and molecular basis of flower opening in L. indica and provide a foundation for breeding strategies aimed at improving ornamental traits.

D. Nowak, J. Dwyer

Ana I. de Castro, Yeyin Shi, J. Maja et al.

This paper reviewed a set of twenty-one original and innovative papers included in a special issue on UAVs for vegetation monitoring, which proposed new methods and techniques applied to diverse agricultural and forestry scenarios. Three general categories were considered: (1) sensors and vegetation indices used, (2) technological goals pursued, and (3) agroforestry applications. Some investigations focused on issues related to UAV flight operations, spatial resolution requirements, and computation and data analytics, while others studied the ability of UAVs for characterizing relevant vegetation features (mainly canopy cover and crop height) or for detecting different plant/crop stressors, such as nutrient content/deficiencies, water needs, weeds, and diseases. The general goal was proposing UAV-based technological solutions for a better use of agricultural and forestry resources and more efficient production with relevant economic and environmental benefits.

K. N. Shivaprakash, Niraj Swami, S. Mysorekar et al.

The recent advancement in data science coupled with the revolution in digital and satellite technology has improved the potential for artificial intelligence (AI) applications in the forestry and wildlife sectors. India shares 7% of global forest cover and is the 8th most biodiverse region in the world. However, rapid expansion of developmental projects, agriculture, and urban areas threaten the country’s rich biodiversity. Therefore, the adoption of new technologies like AI in Indian forests and biodiversity sectors can help in effective monitoring, management, and conservation of biodiversity and forest resources. We conducted a systematic search of literature related to the application of artificial intelligence (AI) and machine learning algorithms (ML) in the forestry sector and biodiversity conservation across globe and in India (using ISI Web of Science and Google Scholar). Additionally, we also collected data on AI-based startups and non-profits in forest and wildlife sectors to understand the growth and adoption of AI technology in biodiversity conservation, forest management, and related services. Here, we first provide a global overview of AI research and application in forestry and biodiversity conservation. Next, we discuss adoption challenges of AI technologies in the Indian forestry and biodiversity sectors. Overall, we find that adoption of AI technology in Indian forestry and biodiversity sectors has been slow compared to developed, and to other developing countries. However, improving access to big data related to forest and biodiversity, cloud computing, and digital and satellite technology can help improve adoption of AI technology in India. We hope that this synthesis will motivate forest officials, scientists, and conservationists in India to explore AI technology for biodiversity conservation and forest management.

J. Fischer, D. Lindenmayer, A. Manning

S. Keola, M. Andersson, Ola Hall

R. Dainelli, P. Toscano, S. F. Di Gennaro et al.

Forest sustainable management aims to maintain the income of woody goods for companies, together with preserving non-productive functions as a benefit for the community. Due to the progress in platforms and sensors and the opening of the dedicated market, unmanned aerial vehicle–remote sensing (UAV–RS) is improving its key role in the forestry sector as a tool for sustainable management. The use of UAV (Unmanned Aerial Vehicle) in precision forestry has exponentially increased in recent years, as demonstrated by more than 600 references published from 2018 until mid-2020 that were found in the Web of Science database by searching for “UAV” + “forest”. This result is even more surprising when compared with similar research for “UAV” + “agriculture”, from which emerge about 470 references. This shows how UAV–RS research forestry is gaining increasing popularity. In Part II of this review, analyzing the main findings of the reviewed papers (227), numerous strengths emerge concerning research technical issues. UAV–RS is fully applicated for obtaining accurate information from practical parameters (height, diameter at breast height (DBH), and biomass). Research effectiveness and soundness demonstrate that UAV–RS is now ready to be applied in a real management context. Some critical issues and barriers in transferring research products are also evident, namely, (1) hyperspectral sensors are poorly used, and their novel applications should be based on the capability of acquiring tree spectral signature especially for pest and diseases detection, (2) automatic processes for image analysis are poorly flexible or based on proprietary software at the expense of flexible and open-source tools that can foster researcher activities and support technology transfer among all forestry stakeholders, and (3) a clear lack exist in sensors and platforms interoperability for large-scale applications and for enabling data interoperability.

T. Asbeck, J. Großmann, Y. Paillet et al.

Purpose of the Review The concept of tree-related microhabitats (TreMs) is an approach to assess and manage multi-taxon species richness in forest ecosystems. Owing to their provision of special habitat features, TreMs are of special interest as a surrogate biodiversity indicator. In particular, in retention forestry, TreMs have gained attention over the past decade as a selection criterion for retained structural elements such as habitat trees. This review seeks to (a) address the suitability of TreMs as biodiversity indicator in the context of retention forestry, (b) summarize drivers of TreM occurrence and the status quo of the implementation of TreM-based retention concepts in forest management, and (c) discuss current and future challenges to the use of TreMs as biodiversity indicator. Recent Findings The TreM concept originated in Europe where it is now increasingly implemented. Most studies of the quantity, quality, and diversity of TreMs are focused on tree species from this region, although it is increasingly applied in other contexts. In addition to tree species, tree dimensions and live status have been identified as the main drivers of TreM occurrence. One major remaining research challenge is to verify relationships between the occurrence and abundance of forest-dwelling species from different taxonomic groups and TreMs to improve the evidence basis of this concept and thus increase its integration in forest conservation approaches. Summary TreMs are not the “silver bullet” indicator to quantify biodiversity of forest dwelling species, but they provide an important tool for forest managers to guide the selection of habitat trees for the conservation of the associated biodiversity.

L. Hamelin, M. Borzecka, Małgorzata Kozak et al.

Abstract Bioeconomy is seen as a key strategic innovation pillar in the European Union, and this involves, among other things, mobilizing biomass resources. This study presents a geo-localized methodology in order to quantify the overall (theoretical) residual biomass potential for each NUTS-3 region of the EU-27 + Switzerland (NUTS-3 is the smallest regional division in Eurostat's Nomenclature of Territorial Units for Statistics). Estimates were made for biomass residues stemming from 4 main activities: i) agriculture (straw, manure, residues from pruning permanent plantations); ii) forestry (forestry residues); iii) urban greenery management (residues from managing urban green areas and roadside vegetation); and iv) food waste (agri-industrial food process waste and municipal biodegradable waste). A review of earlier assessments using a variety of spatial coverages is also presented. Our results reveal the importance of residual biomass as a key feedstock for the European bioeconomy: we found that 8500 PJ y−1 are available for these streams (theoretical potential), which corresponds to the whole annual (2015) primary energy consumption of Italy and Belgium combined. Straw (3800 PJ y−1) and forestry residues (3200 PJ y−1) were shown as the top-two contributors. Our geo-localized approach uncovered outliers in terms of regional trends, revealing very specific opportunities for these regions. This includes the NUTS-3 region of Paris (France) where the highest biomass density was found with ca. 25 TJ km−2 (essentially food waste), and the NUTS-3 of Jaen (Spain), the main region of olive oil in the world, with great opportunities stemming from the olive oil industry.

R. Dainelli, P. Toscano, S. F. Di Gennaro et al.

Natural, semi-natural, and planted forests are a key asset worldwide, providing a broad range of positive externalities. For sustainable forest planning and management, remote sensing (RS) platforms are rapidly going mainstream. In a framework where scientific production is growing exponentially, a systematic analysis of unmanned aerial vehicle (UAV)-based forestry research papers is of paramount importance to understand trends, overlaps and gaps. The present review is organized into two parts (Part I and Part II). Part II inspects specific technical issues regarding the application of UAV-RS in forestry, together with the pros and cons of different UAV solutions and activities where additional effort is needed, such as the technology transfer. Part I systematically analyzes and discusses general aspects of applying UAV in natural, semi-natural and artificial forestry ecosystems in the recent peer-reviewed literature (2018–mid-2020). The specific goals are threefold: (i) create a carefully selected bibliographic dataset that other researchers can draw on for their scientific works; (ii) analyze general and recent trends in RS forest monitoring (iii) reveal gaps in the general research framework where an additional activity is needed. Through double-step filtering of research items found in the Web of Science search engine, the study gathers and analyzes a comprehensive dataset (226 articles). Papers have been categorized into six main topics, and the relevant information has been subsequently extracted. The strong points emerging from this study concern the wide range of topics in the forestry sector and in particular the retrieval of tree inventory parameters often through Digital Aerial Photogrammetry (DAP), RGB sensors, and machine learning techniques. Nevertheless, challenges still exist regarding the promotion of UAV-RS in specific parts of the world, mostly in the tropical and equatorial forests. Much additional research is required for the full exploitation of hyperspectral sensors and for planning long-term monitoring.

Yongchao Zhang, Man Liu, Caimei Liu et al.

The adhesive layer is an important factor affecting the mechanical properties of FRP- bamboo scrimber composite beams (FBSCB). However, studies on the interfacial shear stresses in the adhesive layers with both ends of FRP and bamboo scrimber beam aligned have been rarely reported. To this end, a two-parameter theoretical calculation model and a finite element model (FEM) based on cohesive zone model were hereby established to solve for the adhesive layer interface shear stresses, which was verified by four-point bending experiments. The results show that both the two-parameter theoretical model and the FEM can effectively compute the shear stress of the adhesive layer. Meanwhile, the FEM simulation results not only reflect the detailed changes of the shear stress, but also provide a better analysis of the shear stress at the adhesive layer with a small fluctuation range. There are three zones of shear stress at the adhesive layer of FBSCB under four-point bending load, i.e., the bending and shearing zone, the transition zone and the pure bending zone. In the bending and shearing zone, the shear stress of the adhesive layer interface increases 2.61 times and 2.5 times, respectively when the thickness and elastic modulus of FRP increase three times. However, the stress remains constant at zero in the pure bending zone.

邱国玉1，张鑫2,3，王小芳1，曾韦丹4，裴栋4，王晗3， 阚欢2，袁奖娟2,3QIU Guoyu1, ZHANG Xin2,3, WANG Xiaofang1, ZENG Weidan4, PEI Dong4, WANG Han3, KAN Huan2, YUAN Jiangjuan2,3

旨在为油橄榄作为食品应用提供科学依据，以田园1号、佛奥、鄂植8号、豆果及柯基5种油橄榄果为研究对象，参考国家标准对油橄榄果中主要营养成分、羟基酪醇和橄榄苦苷含量，矿物质元素、氨基酸和脂肪酸组成及含量等进行测定，并通过主成分分析对5种油橄榄果的综合品质进行评价。结果表明：油橄榄果中含量较多的是水分、脂肪和膳食纤维，依次为60.50~68.20 g/100 g、10.20~20.00 g/100 g 和7.03~13.50 g/100 g；矿物元素中K元素含量最高，Na元素仅在佛奥和柯基中检出，Zn元素仅在鄂植8号、豆果、柯基中检出；5种油橄榄果的必需氨基酸含量均占总氨基酸含量的43%左右，与FAO/WHO推荐人体每日所需摄入氨基酸比例接近；氨基酸评分最高的是苯丙氨酸+酪氨酸，其中与FAO/WHO标准最接近的品种是鄂植8号；5种油橄榄果中共检出15种脂肪酸，其中油酸、亚油酸和棕榈酸含量较高；油橄榄果中均含有橄榄苦苷和羟基酪醇，除田园1号外，其余品种中羟基酪醇含量均高于橄榄苦苷；综合评分最高的品种是柯基。综上，油橄榄果中营养成分较为丰富，在食品深加工等方面具有较高的开发利用价值。In order to provide scientific basis for the application of Olea europaea L. fruits as a food product, with five kinds of Olea europaea L. fruits namely Tianyuan No. 1, Foao, Ezhi No. 8, Douguo and Keji as research objects, the contents of basic nutrients, hydroxytyrosol and oleuropein, and the compositon and contents of mineral elements, amino acids and fatty acids were determined by the national standard methods. The comprehensive quality of five kinds of Olea europaea L. fruits was evaluated through principal component analysis. The results showed that the basic nutrients in five kinds of Olea europaea L. fruits were mainly water, fat and dietary fiber, and the contents were 60.50-68.20 g/100 g, 10.20-20.00 g/100 g and 7.03-13.50 g/100 g, respectively. The content of K in mineral elements was the highest. The element Na was only detected in Foao and Keji, and the element Zn was only detected in Ezhi No.8, Douguo and Keji. The content of essential amino acid in five kinds of Olea europaea L. fruits was accounted for about 43% of the total amino acid content, which was close to the FAO/WHO recommended daily intake of amino acids. The highest amino acid score was phenylalanine (Phe) + tyrosine (Tyr), and the closest one to FAO/WHO standards was Ezhi No. 8. A total of 15 fatty acids were detected in five kinds of Olea europaea L. fruits, mainly oleic acid, linoleic acid, and palmitic acid. Except for Tianyuan No. 1, the content of hydroxytyrosinol was higher than that of oleuropein in other varieties. The variety with the highest overall rating was Keji. In summary, Olea europaea L. fruits are rich in nutrients and have high development and utilization value in areas such as food deep processing.