Hasil untuk "Forestry"

H. Kaufman

J. Delouche, C. C. Baskin

B. Brown, M. Hanson, D. Liverman et al.

Delun Lai, Kai Kang, Ke Xu et al.

The rapid advancement of Unmanned Aerial Vehicle (UAV) technology has facilitated dynamic, high-resolution remote sensing, significantly benefiting applications in agriculture, forestry, urban planning, and disaster management. However, detecting small objects in UAV imagery remains challenging due to severe scale variations and environmental complexities. While traditional detection methods and even many advanced YOLO variants achieve reasonable performance, they often either incur high computational costs or fail to preserve the fine-grained features essential for reliably detecting extremely small targets. To overcome these limitations, we propose SRD-YOLOv5, an enhanced version of the lightweight YOLOv5n model, distinguished by its novel multi-scale feature fusion framework. Our approach introduces two innovative modules: the Scale Sequence Feature Fusion Module (SSFF) and the Multi-Scale Feature Extraction Module (MSFE), which collaboratively capture global contextual information and preserve detailed semantic cues that are typically lost in conventional fusion techniques. Furthermore, we incorporate an Extremely Small Target Detection Layer (ESTDL) specifically designed to retain high-resolution features for micro-scale object detection. Additionally, the implementation of a Decoupled Head, which independently processes regression and classification tasks, further optimizes the detection of small targets by reducing task conflicts and improving localization precision. Experimental results demonstrate that SRD-YOLOv5 outperforms existing methods in detecting small targets within UAV remote sensing images. It achieves higher accuracy while maintaining low computational demands, making it suitable for real-time applications in UAV remote sensing.

Satriagasa Muhammad Chrisna, Suryatmojo Hatma, Kusumandari Ambar et al.

Accurate land use information is vital for effective watershed monitoring and management. This study explores the use of ChatGPT-4o, a multimodal large language model (LLM), to interpret UAV-derived orthomosaics in the Tamansari Catchment, Central Java, Indonesia. High-resolution imagery from 2018 and 2025 was analyzed through natural language prompts to identify land use types and detect changes over time. Results revealed a significant shift toward intensive agriculture, with agroforestry decreasing from 32.3% to 4.8% and secondary forest cover halving from 19.4% to 9.7%. A hybrid validation strategy was applied, combining internal spatial consistency checks with external visual verification using Google Street View. While the method does not produce pixel-based classification maps, it enables descriptive interpretation without requiring advanced technical skills. The findings demonstrate that ChatGPT-4o can serve as a rapid, accessible, and cost-effective tool for participatory watershed monitoring, especially in data-scarce or low-resource environments. Further integration with ground-truth data is recommended to improve accuracy.

Aldair A. Meza-Santiago, Maria Guadalupe Hernandez-Herrera, Erick A. Zuñiga-Estrada et al.

While fruit is a common ingredient in beer, our research takes a unique approach by studying the effects of pomegranate juice (PJ) on the physicochemical and nutraceutical characteristics of craft fruit beer. These properties have been studied in PJ and other beverages using pomegranate; however, there is insufficient information on fruit beer. PJ, known for its health benefits, was obtained by compressing the fruit in a manual press and characterizing it. The base beer, a blonde ale with two hops, Cascade (C) and Saaz (S), was used. PJ was added to the beer during the second and third fermentation steps. Beer quality was analyzed using ASBC methods: phenolic compounds, sugars, and ethanol content by HPLC, and antioxidant capacity by ORAC. PJ presented a pH of 3.8 and 14°Brix. The beer evaluated was the third fermentation beer called 3FC and 3FS; due to the type of hops used, in general, 3FS presented better physicochemical characteristics; the relevant result was alcohol content around 6.0%, but ethanol content by HPLC was 7.36% for 3FS and 7.19% for 3FC. PJ in phenolic compounds provides the beer with 4-hydroxybenzoic acid, epicatechin, and synaptic acid. However, the hop used influenced the phenolic profile of each beer. The antioxidant capacity of 3FC was higher at 19.75 mm ET/L. In conclusion, our study demonstrated that pomegranate juice in a fruit beer style provides good physicochemical and nutraceutical characteristics, offering a unique twist to the craft beer industry.

S. Schmidheiny

Yuting Zhao, Jungho Im, Zhen Zhen et al.

Accurate quantification of individual tree parameters is vital for precise forest inventory and sustainable forest management. However, in dense forests, terrestrial laser scanning (TLS), which can provide accurate and detailed forest structural measurements, is limited to capturing the complete tree structure due to the lack of upper canopy views, resulting in an underestimation of tree height. Combining TLS with unmanned aerial vehicle laser scanning (ULS) is an effective way to overcome this limitation. Thus, it is vital to register multi-platform Light Detection and Ranging (LiDAR) data for various forestry applications. This study proposed three automated and nearly parameter-free optimized coarse-to-fine algorithms (i.e. FPFH-based optimized ICP (F-OICP), RANSAC-based optimized ICP (R-OICP), and NDT-based optimized ICP (N-OICP)) to accurately register TLS and ULS point data for individual tree crown delineation and parameters (diameter at breast height (DBH) and tree height) estimations in different forest types (i.e. coniferous, mixed broadleaf-coniferous, and broadleaf). Results showed that the proposed optimized algorithms had a good registration performance, with an average RMSE of about 8.3 cm for the transformation error; and obtained stable and high accuracies of individual tree crown delineation (ITCD) (F-score: 0.7), DBH (R2: 0.9, RMSE <1.85 cm), and tree height (R2: 0.8, RMSE <0.37 m) estimates for three forest types. F-OICP performed the best in tree height estimation, reducing the RMSE by 48%, 12%, and 12% compared to iterative closest point (ICP), R-OICP, and N-OICP, respectively. Stand type significantly impacted ITCD and individual tree parameter estimations. The ITCD and DBH estimation accuracy of coniferous forests were marginally higher than those of broadleaf forests (F-score: 0.78 vs. 0.78, DBH RMSE: 1.57 vs. 1.74), while those of mixed broadleaf-coniferous forests were the lowest (F-score: 0.71, DBH RMSE: 2.19). The accuracies of tree height estimates in coniferous forests were the highest (R2: 0.87, RMSE: 0.21 m), followed by mixed broadleaf-coniferous (R2: 0.84, RMSE: 0.37 m) and broadleaf (R2: 0.84, RMSE: 0.44 m) forests. This work developed automated, nearly parameter-free, and effective registration algorithms and recommended F-OICP to be the most appropriate for dense forests (i.e. natural secondary forests). The optimized registration algorithms facilitate the ability for the synergistic use of multi-platform LiDAR and offer appealing and promising approaches for future accurate quantification of individual tree parameters, efficient forest inventories, and sustainable forest management.

Alexandra Maria Ferreira Silveira, Ricardo Antonio Marenco

ABSTRACT The simultaneous effect of elevated CO2 concentration and drought on trees is still under investigation in the Amazon. We evaluated the effect of CO2 levels (400 and 800 ppm) and water regimes (50% and 100% soil field capacity) on photosynthetic traits, chlorophyll fluorescence, and total biomass accumulation in Ceiba pentandra. In well-watered plants, light-saturated photosynthesis (PN-sat) increased in plants exposed to elevated CO2, but both PN-sat and stomatal conductance decreased in response to water deficit. The maximum carboxylation rate of Rubisco declined under elevated CO2, which indicates down-regulation of photosynthesis at elevated CO2. The Fv/Fm ratio was not affected by treatments. Notwithstanding, total plant biomass and leaf area were reduced by 34-37% under water deficit, but they were not affected by CO2 levels. The PN-sat values measured in well-irrigated plants at ambient CO2 were similar to those observed in plants subjected to elevated CO2 and water deficit (p = 0.26). We concluded that the effect of water deficit on PN-sat was mitigated by elevated CO2. These results suggest that the increase of atmospheric CO2 concentrations associated to climate changes can at least partly offset the negative effect of drought in this multiuse and widely distributed species.

F. Schinner, W. V. Mersi

R. Baumgartner

The United Nations adopted the Agenda 2030 with its core element, the 17 Sustainable Development Goals (SDGs), in September 2015. In order to achieve these goals within the coming years, intense efforts are required by all political and societal actors. Although the first definitions of sustainable development referred to the forest sector, the question remains: what contribution can forestry make to achieving the Sustainable Development Goals? Therefore, the direct positive and negative effects of forestry itself on sustainability are analyzed, and it is discussed how sustainable forest management could contribute to achieving other Sustainable Development Goals in addition to SDG 15. This analysis reveals that forestry plays a dual role, i.e., forestry can achieve positive sustainability effects but can also have negative impacts. It is thus recommended to use integrated assessment approaches to analyze whether a specific forest-related policy or strategy is contributing to sustainable development. Beside quantitative integrated assessments, the use of qualitative frameworks like the Framework for Strategic Sustainable Development is proposed. It is also suggested to operationalize the concept of second-order sustainability performance for the forest sector in future research.

Candido Mendoza Pérez, Carlos Ramirez Ayala, Antonio Martinez Ruiz et al.

This study aimed to estimate the tomato leaf area index (LAI) by comparing two methods (destructive and interception of photosynthetically active radiation) and the consequent relationship to fruit yield and quality. The experiment was carried out in a greenhouse with tezontle (red volcanic scoria) as the substrate and a drip irrigation system. The experiment consisted of three treatments: T1, T2 and T3, with one, two and three stems per plant, respectively. The LAI was measured with a ceptometer that estimates the intercepted radiation above and below the canopy. Maximum LAI was found at 1413 cumulative growing degree days (CGDD). Those indexes were 3.69, 5.27 and 6.16 for T1, T2 and T3, respectively. Individual correlation models were fitted linearly between the two methods. The R2 values were 0.98, 0.99 and 0.99 with yields of 20, 18 and 17 kg m-2 for T1, T2 and T3, respectively. In addition, T1 produced better fruit size quality with approximately 69, 23 and 8% classified as first, second and third class, respectively. Only 1% was classified as a small fruit. Increasing the number of stems per plant increased the LAI and fruit number but decreased fruit size. Highlights: • The leaf area index (LAI) is a very important variable for growth and development of crops. • The ceptometer proved to be a fast, useful and statistically reliable method to estimate LAI. • The increase of photosynthetically active radiation favors the photosynthetic efficiency per unit area. • The number of stems per plant increase the LAI, dry matter accumulation, plant height and the number of fruits. However, the size of fruit decreases.

Jie Ye, Chao Wang, Chao Gao et al.

While the combination of synthetic and biological systems offers an appealing strategy for solar-to-fuel conversion, such hybrid systems typically suffer from low selectivity. Here, authors integrate a bimetallic alloy with a CdS-containing methanogen for selective CO2 reduction to methane.

Lis Nur Ajijah, Rahmat Safe'i, Slamet Budi Yuwono

Partsipasi masyarakat dalam pengelolaan hutan sangat penting bagi keberhasilan program Pengelolaan Hutan Berbasis Masyarakat (PHBM). Partisipasi komunitas berdampak positif pada kegiatan dari tahap perencanaan sampai tahap evaluasi, operasi pengelolaan hutan. Penelitian ini bertujuan untuk mengukur sejauh mana keterlibatan masyarakat dalam pengelolaan hutan di HKm Harapan Sentosa. Penentuan responden dilakukan dengan teknik purposive sampling menggunakan key actors yang terdiri dari ketua, pengurus inti serta anggota kelompok di HKm Harapan Sentosa. Pengolahan data tingkat partisipasi ini menggunakan skala likert. Hasil penelitian diperoleh data rata-rata tingkat partisipasi anggota masyarakat gapoktan di HKm Harapan Sentosa termasuk kedalam kategori sedang dengan rentang nilai 40-55. Hal ini menunjukkan bahwa masyarakat Gapoktan belum terlibat langsung dalam setiap kegiatan pengelolaan hutan yang dimulai dari tahap perencanaan sampai dengan tahap pemantauan dan evaluasi.

Mohd Hafizuddin-Syah Bangun Abdullah, Shahida Shahimi, Amran Arifin

In a wake of concern towards sustainable palm oil products, the Malaysian government had continuously formulated various guidelines for palm oil industries in fulfilling the international sustainability requirement. In 2013, Malaysia has launched Malaysian sustainable palm oil (MSPO), which eventually become mandatory requirement in January 2020, including the independent smallholders. However, the numbers of independent smallholders that acquired MSPO was relatively low, stood at 30.66%. Therefore, this study aims to analyse the perceptions of independent smallholders towards MSPO in Malaysia. A structured questionnaire was used for data collection instrument that been distributed among 350 independent smallholders, with a response rate of 74.5%. Results from descriptive analysis showed that independent smallholders have a good perception towards MSPO certification. Furthermore, multiple regression analysis revealed that all three factors were significant to influence the perceptions, where the risk perception became the most important contributor. This study enhances the awareness of sustainability practices among independent smallholders and contributes to the implementation of MSPO certification. Since risk perception has emerged as the primary contributor, regulators or governing bodies must seriously consider risk mitigation concerning independent smallholders about risk exposure such as continuous monitoring to comply environment impact assessment requirement, improve the availability and accessibility of information and aggressive awareness campaign on MSPO.  

P. Savill

Abstract This chapter describes the origin and introduction; climatic and site requirements, and other silvicultural characteristics; pests and diseases; natural regeneration; flowering, seed production and nursery conditions; conservation; provenance and breeding; timber and uses; area and yield; and place of oaks (Quercus petraea, Q. robur, and Q. rubra) in British forestry.

C. Messier, K. Puettmann, R. Chazdon et al.

The world's forests and forestry sector are facing unprecedented biological, political, social, and climatic challenges. The development of appropriate, novel forest management and restoration approaches that adequately consider uncertainty and adaptability are hampered by a continuing focus on production of a few goods or objectives, strong control of forest structure and composition, and most importantly the absence of a global scientific framework and long‐term vision. Ecosystem‐based approaches represent a step in the right direction, but are limited in their ability to deal with the rapid pace of social, climatic, and environmental changes. We argue here that viewing forest ecosystems as complex adaptive system provides a better alternative for both production‐ and conservation‐oriented forests and forestry. We propose a set of broad principles and changes to increase the adaptive capacity of forests in the face of future uncertainties. These span from expanding the sustained‐yield, single‐good paradigm to developing policy incentives and interventions that promote self‐organization and integrated social‐ecological adaptation.

Menghua Zhang, Xiaoli Cheng, Qinghong Geng et al.

1College of Biology and the Environment, Nanjing Forestry University, Nanjing, Jiangsu, China 2Co‐Innovation Centre for Sustainable Forestry in Southern China, Nanjing Forestry University, Nanjing, Jiangsu, China 3Key Laboratory of Aquatic Botany and Watershed Ecology, Wuhan Botanical Garden, Chinese Academy of Sciences, Wuhan, Hubei, China 4Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, Arizona

F. J. Lozano, R. Lozano

W. van der Gaast, R. Sikkema, M. Vohrer

ABSTRACT This article addresses the question of how forestry projects, given the recently improved standards for the accounting of carbon sequestration, can benefit from existing and emerging carbon markets in the world. For a long time, forestry projects have been set up for the purpose of generating carbon credits. They were surrounded by uncertainties about the permanence of carbon sequestration in trees, potential replacement of deforestation due to projects (leakage), and how and what to measure as sequestered carbon. Through experience with Joint Implementation (JI) and Clean Development Mechanism (CDM) forestry projects, albeit limited, and with forestry projects in voluntary carbon markets, considerable improvements have been made with accounting of carbon sequestration in forests, resulting in a more solid basis for carbon credit trading. The scope of selling these credits exists both in compliance markets, although currently with strong limitations, and in voluntary markets for offsetting emissions with carbon credits. Improved carbon accounting methods for forestry investments can also enhance the scope for forestry in the Nationally Determined Contributions (NDCs) that countries must prepare under the Paris Agreement. POLICY RELEVANCE This article identifies how forestry projects can contribute to climate change mitigation. Forestry projects have addressed a number of challenges, like reforestation, afforestation on degraded lands, and long-term sustainable forest management. An interesting new option for forestry carbon projects could be the NDCs under the Paris Agreement in December 2015. Initially, under CDM and JI, the number of forestry projects was far below that for renewable energy projects. With the adoption of the Paris Agreement, both developed and developing countries have agreed on NDCs for country-specific measures on climate change mitigation, and increased the need for investing in new measures. Over the years, considerable experience has been built up with forestry projects that fix CO2 over a long-term period. Accounting rules are nowadays at a sufficient level for the large potential of forestry projects to deliver a reliable, additional contribution towards reducing or halting emissions from deforestation and forest degradation activities worldwide.