Sustaining forest biodiversity: Exploring the effect of long-term natural disturbance dynamics on contemporary lichen communities in primary forest ecosystems by Rhiannon Gloor, Marek Svitok, Martin Mikoláš, Jeňýk Hofmeister, Josef Halda, Pavel Janda, Francesco Maria Sabatini, Lucie Zemanová, Arne Buechling, Daniel Kozák, Matej Ferenčík, Michal Frankovič, Martin Dušátko, Miroslav Svoboda

“…Total species richness indirectly benefited from both historical and recent higher-severity disturbances via increased standing dead tree basal area and canopy openness respectively - likely through the presence of both pioneer and late-successional species associated with these conditions. …”
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Effects of pruning on canopy microenvironment, branch composition and nut quality in Xinjiang walnut by HAN Liqun, ZHAO Yu, ZHAO Guoqing, ZHANG Hui, MA Kai

“…For the tall arboreal trees like walnut, adopting efficient and simple pruning method can significantly reduce production costs and enhance economic benefits. …”
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Integrating Objective and Subjective Thermal Comfort Assessments in Urban Park Design: A Case Study of Monteria, Colombia by Jhoselin Rosso-Alvarez, Juan Jiménez-Caldera, Gabriel Campo-Daza, Richard Hernández-Sabié, Andrés Caballero-Calvo

“…In contrast, 90.91% of respondents stated that tree cover improved their thermal experience. The results indicate a strong correlation between vegetation density, surface type, and users’ perceived comfort. …”
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Dissolved Oxygen Modeling by a Bayesian-Optimized Explainable Artificial Intelligence Approach by Qiulin Li, Jinchao He, Dewei Mu, Hao Liu, Shicheng Li

“…Dissolved oxygen (DO) is a vital water quality index influencing biological processes in aquatic environments. …”
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Using machine learning to identify key predictors of maternal success in sheep for improved lamb survival by Ebru Emsen, Bahadir Baran Odevci, Muzeyyen Kutluca Korkmaz

“…This study investigates key physiological, genetic, and environmental factors influencing maternal success in sheep to enhance lamb survival and maternal quality. …”
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The Study on Landslide Hazards Based on Multi-Source Data and GMLCM Approach by Zhifang Zhao, Zhengyu Li, Penghui Lv, Fei Zhao, Lei Niu

“…The southwest region of China is characterized by numerous rugged mountains and valleys, which create favorable conditions for landslide disasters. The landslide-influencing factors show different sensitivities regionally, which induces the occurrence of disasters to different degrees, especially in small sample areas. …”
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Global Research Trends in Performance-Based Structural Design: A Comprehensive Bibliometric Analysis by Mistreselasie S. Abate, Ana Catarina Jorge Evangelista, Vivian W. Y. Tam

“…However, previous studies have lacked crucial components such as local soil condition, ground response analysis, topographic influences, active fault characteristics, slip rates, groundwater behaviour, and slope considerations. …”
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IMPLEMENTATION OF MAPPING-BASED MACHINE LEARNING ALGORITHM AS NON-STRUCTURAL DISASTER MITIGATION TO DETECT LANDSLIDE SUSCEPTIBILITY IN TAKARI DISTRICT by Sefri Imanuel Fallo, Lidia Paskalia Nipu

“…A range of machine learning algorithms, including Support Vector Machine, Naive Bayes Classifier, Ordinal Logistic Regression, Random Forest, and Decision Tree, were harnessed to evaluate rainfall data within the context of landslide susceptibility. …”
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A Comparative Analysis of Black-Box and Glass-Box Models for Poplar Plantation Mapping with Remote Sensing Data by M. Y. Ozturk, I. Colkesen

“…Poplar trees are essential for industrial afforestation applications due to their globally recognized plantation practices, reputation, ability to produce a large quantity of raw material in a short time, diverse applications in wood production, suitability for hybridisation and breeding implementations, and the availability of various species and clones adapted to the soil and climate conditions. …”
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Enhancing the Accuracy of Land Use/Cover Map Using Some Spectral Indices in Sarab County–East Azerbaijan by A. Sarabchi, H. Rezaei, F. Shahbazi

“…Results and Discussion Field observations revealed that the study area could be categorized into 12 primary LULC units, including irrigated farms, flow farming, dry farming, traditional gardens (with no evident order observed among planted trees), modern gardens (featuring regular rows where soil reflectance is visible between tree rows), grasslands, degraded grasslands, highland pastures (covered by Astragalus spp., dominantly), lowland pastures (covered by halophyte plants), salt domes (with no or very poor vegetation), outwash areas (River channel with many waterways), and resistant areas. …”
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Advance, steadfast, retreat? Growth and establishment of white spruce seedlings at treelines in Alaska by Andreas Burger, Mario Trouillier, Martin Wilmking

“…Abstract Range dynamics of tree species are largely driven by seedling establishment and survival, mainly at and beyond current treelines. …”
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The Role of Plant Evolutionary History in Shaping the Variation in Specific Leaf Area Across China by Minyue Si, Caiyi Zhang, Chunzhu Xiang, Mingxia Jiang, Linwei Guo, Junjiong Shao

“…The relationship between SLA and environmental variables (climatic conditions and soil properties) was different between angiosperms and gymnosperms, with the climatic conditions having larger influences on SLA than the soil properties, implying interactive effects between environment and evolutionary history on SLA. …”
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Regression Analysis of Heat Release Rate for Box-Type Power Bank Based on Experimental and Machine Learning Methods by Shihan Luo, Hua Chen, Xiaobing Mao, Wenbing Zhu, Yuanyi Xie, Wenbin Wei, Mengmeng Jiang, Chenyang Zhang, Chaozhe Jiang

“…This study uses experimental testing and machine learning regression analysis to explore the heat release rate (HRR) characteristics and influencing factors of box-type power banks under fire conditions. …”
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Integrating Soil, Leaf, Fruitlet, and Fruit Nutrients, Along with Fruit Quality, to Predict Post-Storage Quality of Staccato Sweet Cherries by Mehdi Sharifi, William Wolk, Keyvan Asefpour Vakilian, Hao Xu, Stephanie Slamka, Karen Fong

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Machine learning for asphaltene polarizability: Evaluating molecular descriptors by Arun K. Sharma, Owen McMillan, Selsela Arsala, Supreet Gandhok, Rylend Young

“…Asphaltenes are complex polycyclic organic molecules in crude oil that readily aggregate and precipitate under varying thermodynamic conditions. Their structural heterogeneity influences key physicochemical properties, including solubility, stability, and reactivity. …”
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Investigating the Distribution Dynamics of the <i>Camellia</i> Subgenus <i>Camellia</i> in China and Providing Insights into <i>Camellia</i> Resources Management Under Future Clima... by Yue Xu, Bing-Qian Guan, Ran Chen, Rong Yi, Xiao-Long Jiang, Kai-Qing Xie

“…Rapid climate change has significantly impacted species distribution patterns, necessitating a comprehensive understanding of dominant tree dynamics for effective forest resource management and utilization. …”
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Identifying drivers of surface ozone bias in global chemical reanalysis with explainable machine learning by K. Miyazaki, Y. Marchetti, J. Montgomery, S. Lu, K. Bowman

“…The global distributions of ozone bias predicted by ML revealed systematic patterns influenced by meteorological conditions, geographic features, anthropogenic activities, and biogenic emissions. …”
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Anthropogenic Drivers of Small-Island Effects in Urban Remnant Woody Plants by Di Kong, Kai Wang, Lin Dong, Jinming Yang, Zhiwen Gao, Hong Liang

“…For trees, the SIE was influenced by the distance to the source of species, <i>GDP</i>, night light intensity, and perimeter–area ratio. …”
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Yield, Production Losses, Fertility Status, and Soil Microbial Population in Three Different Cocoa (Theobroma cacao L.)-Based Cropping Systems in an Oxisol in Southern Cameroon by Pierre Germain Ntsoli, Idriss Djoko Kouam, Roland Wilfried Titti, Georges Marius Etame Kossi, David Brondon Mouthe, Aoudou Yaouba

“…Cocoa is a vital crop globally, yet its production is influenced by various cropping systems that can significantly affect its field performance and long-term sustainability. …”
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Prediction of Pollutant Emissions from a Low-Speed Marine Engine Based on Harris Hawks Optimization and Lightgbm by Yue Chen, Yulong Shen, Miaomiao Wen, Cunfeng Wei, Junjie Liang, Yuanqiang Li, Ying Sun

“…The results show that changes in engine control parameters have significant influences on NOx and soot emissions from the engine, which can serve as the basis for the selection of the LGB model features; the LGB model was able to accurately predict pollutant concentrations from the engine with much higher accuracy than a single decision tree (DT) model; combining with HHO, the predictive ability of the LGB model was significantly improved, such as for the validation set prediction results, the mean absolute error (MAE) was reduced by about 20%, the mean squared error (MSE) was reduced by about 30%, and the coefficient of determination (R²) was increased by about 0.005; and the importance analysis of the model features indicated that the combustion condition of the fuel was highly correlated with the generation of the pollutants, and the fuel injection phases can be adjusted in practice to achieve highly efficient and low-emission processes of combustion. …”
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