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MDPI AG, a publisher of open-access scientific journals, was spun off from the Molecular Diversity Preservation International organization. It was formally registered by Shu-Kun Lin and Dietrich Rordorf in May 2010 in Basel, Switzerland, and maintains editorial offices in China, Spain and Serbia. MDPI relies primarily on article processing charges to cover the costs of editorial quality control and production of articles. Over 280 universities and institutes have joined the MDPI Institutional Open Access Program; authors from these organizations pay reduced article processing charges. MDPI is a member of the Committee on Publication Ethics, the International Association of Scientific, Technical, and Medical Publishers, and the Open Access Scholarly Publishers Association (OASPA).
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Displaying 136 - 140 of 1524Conserving Potential and Endangered Species of Pericopsis mooniana Thwaites in Indonesia
Indonesia has around 4000 wood species, and 10% (400) of species are categorized as commercial wood. One species is kayu kuku (Pericopsis mooniana Thwaites), native to Southeast Sulawesi. This species is considered a fancy wood used for sawn timber, veneer, plywood, carving, and furniture. The high demand for wood caused excessive logging and threatened its sustainability. In addition, planting P. mooniana has presented several challenges, including seedling production, viability and germination rate, nursery technology, and silviculture techniques.
Functional Diversity of Soil Microorganisms and Influencing Factors in Three Typical Water-Conservation Forests in Danjiangkou Reservoir Area
As a key part of the forest ecosystem, soil microorganisms play extremely important roles in maintaining the ecological environment and the security of water quality in reservoir areas. However, it is not clear whether there are differences in the functional diversity of soil microorganisms in different types of water-conservation forests in reservoir areas, and which factors affect the functional diversity of soil microorganisms.
Forest Land Resource Information Acquisition with Sentinel-2 Image Utilizing Support Vector Machine, K-Nearest Neighbor, Random Forest, Decision Trees and Multi-Layer Perceptron
Forestry work involves scientific management and the effective utilization of forest land resources, and finding economical, efficient and accurate acquisition methods for forest land resource information. In previous land-use classification research, machine learning algorithms have achieved good results, and Sentinel public data have been used in various remote sensing applications. However, there is a paucity of research using these data to evaluate the performance of machine learning algorithms in the extracting of complex forest land resource information.
Spatio-Temporal Evolution and Driving Factors of Landscape Pattern in a Typical Hilly Area in Southern China: A Case Study of Yujiang District, Jiangxi Province
As the most intuitive manifestation of land use/land cover change, the spatio-temporal evolution of landscape patterns has significant implications for optimizing regional landscape pattern and land use management. Based on multi-period remote sensing data, we selected an optimal scale (570 m) and used the geographic detector model to analyze the spatio-temporal changes in the landscape pattern of a typical hilly area (Yujiang District, Yingtan City, Jiangxi Province) in southern China.
Evaluation of Plant Growth and Potential of Carbon Storage in the Restored Mangrove of an Abandoned Pond in Lubuk Kertang, North Sumatra, Indonesia
Mangrove forest in Lubuk Kertang Village, West Brandan sub-district has been converted around 20 ha annually (1996–2016) into various non-forest land use. Rehabilitation can be a solution to restore the condition of the ecosystem so that it can resume its ecological and economic functions. This paper discusses the evaluation of mangrove rehabilitation carried out by planting 6000 propagules in December 2015 and 5000 seedlings in May 2016 with Rhizophora apiculata species in abandoned ponds. Monitoring was carried out every 6 months from 2016 to 2022.