Management of Field Windbreaks by Bijay Tamang, Michael G. Andreu, Melissa H. Friedman, Donald L. Rockwood

“…Published by the UF School of Forest Resources and Conservation, September 2009. …”
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Cassia grandis, Pink Shower by Michael G. Andreu, Melissa H. Friedman, Robert J. Northrop

“…Northrop, and published by the UF Department of School of Forest Resources and Conservation, July 2012. …”
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Common Woody Plants of Florida Scrub Ecosystems by Lynn Proenza, Michael Andreu

“…This 14-page fact sheet was written by Lynn Proenza and Michael Andreu and published by the UF Department of School of Forest Resources and Conservation, October 2012. …”
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Longleaf Pine Regeneration by Chris Demers, Alan Long, Patrick Minogue

“…Published by the UF Department of School of Forest Resources and Conservation, November 2010. …”
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How does dispersal shape the genetic patterns of animal populations in European cities? A simulation approach by Savary, Paul, Tannier, Cécile, Foltête, Jean-Christophe, Bourgeois, Marc, Vuidel, Gilles, Khimoun, Aurélie, Moal, Hervé, Garnier, Stéphane

“…Hence, population-level genetic diversity was higher in forests than in UGS and genetic differentiation was higher between UGS populations than between forest populations. …”
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The clinical prediction model to distinguish between colonization and infection by Klebsiella pneumoniae by Xiaoyu Zhang, Xifan Zhang, Deng Zhang, Jing Xu, Jingping Zhang, Xin Zhang

“…Six predictive models were constructed using 15 key influencing factors, including Classification and Regression Trees (CART), C5.0, Gradient Boosting Machines (GBM), Support Vector Machines (SVM), Random Forest (RF), and Nomogram. The Random Forest model performed best among all indicators (accuracy 0.93, precision 0.98, Brier Score 0.06, recall 0.72, F1 Score 0.83, AUC 0.99). …”
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Vegetation disturbance and regrowth dynamics in shifting cultivation landscapes by Yamini Bhat, Subrata Nandy, Krishna Das, Muna Tamang, Hitendra Padalia, Arun Jyoti Nath, Koushik Majumdar, Rocky Pebam, Pynkhlainbor Thongni, Bandana Kurmi, Ashesh Kumar Das, S. P.S. Kushwaha, R. P. Singh

“…Six land use and land cover classes, viz., forests and trees outside forests, rubber plantation, shifting cultivation, water bodies, agriculture, and settlements, were mapped with an accuracy of 83.08% using a random forest classifier. …”
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Monitoring Soil Salinity in Arid Areas of Northern Xinjiang Using Multi-Source Satellite Data: A Trusted Deep Learning Framework by Mengli Zhang, Xianglong Fan, Pan Gao, Li Guo, Xuanrong Huang, Xiuwen Gao, Jinpeng Pang, Fei Tan

“…The study applied four types of feature selection algorithms: Random Forest (RF), Competitive Adaptive Reweighted Sampling (CARS), Uninformative Variable Elimination (UVE), and Successive Projections Algorithm (SPA). …”
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Savoirs médicinaux interspécifiques et interactions entre cornacs et éléphants dans le district de Thongmyxay au Laos by Jean-Marc Dubost, Eric Deharo, Sysay Palamy, Chithdavone Her, Chiobouaphong Haekovilay, Lamxay Vichith, Sébastien Duffilot, Sabrina Krief

“…The medicinal uses they make of some of these plants in their households are more consistent with their observations of these elephant behaviours than it is with the use of the same items by local healers, suggesting a transfer of medicinal knowledge from elephants to mahouts.Since some of the village elephants in Thongmyxay are still periodically released and come into contact with their wild counterparts, the domestication space forms an interface between humans, wild elephants and the forest, and we discuss conversely the possibility of knowledge transfer from mahouts to village elephants through the ethnoveterinary care they receive.This knowledge which is precious for the health and well-being of people and elephants in Laos is threatened by the reduction of the forest cover sheltering the resources used, and by the relocation of village elephants to tourist centres. …”
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Evaluation of the Effectiveness of Multiple Machine Learning Methods in Remote Sensing Quantitative Retrieval of Suspended Matter Concentrations: A Case Study of Nansi Lake in Nort... by Xiuyu Liu, Zhen Zhang, Tao Jiang, Xuehua Li, Yanyi Li

“…Then, seven methods such as linear regression, BP neural network (BP), KNN, random forest (RF), and random forest based on genetic algorithm optimization (GA_RF) are used to construct the inversion model of TSM concentration. …”
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Interspecific medicinal knowledge and Mahout-Elephant interactions in Thongmyxay district, Laos by Jean-Marc Dubost, Eric Deharo, Sysay Palamy, Chithdavone Her, Chiobouaphong Phaekovilay, Lamxay Vichith, Sébastien Duffillot, Sabrina Krief

“…The medicinal uses they make of some of these plants in their households are more consistent with their observations of these elephant behaviours than it is with the use of the same items by local healers, suggesting a transfer of medicinal knowledge from elephants to mahouts.Since some of the village elephants in Thongmyxay are still periodically released and come into contact with their wild counterparts, the domestication space forms an interface between humans, wild elephants and the forest, and we discuss conversely the possibility of knowledge transfer from mahouts to village elephants through the ethnoveterinary care they receive.This knowledge which is precious for the health and well-being of people and elephants in Laos is threatened by the reduction of the forest cover sheltering the resources used, and by the relocation of village elephants to tourist centres. …”
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Comparison of Satellite-based PM2.5 Estimation from Aerosol Optical Depth and Top-of-atmosphere Reflectance by Heming Bai, Zhi Zheng, Yuanpeng Zhang, He Huang, Li Wang

“…For both reflectance-based and AOD-based approaches, our cross validated results show that random forest algorithm achieves the best performance, with a coefficient of determination (R2) of 0.75 and root-mean-square error (RMSE) of 18.71 µg m−3 for the former and R2 = 0.65 and RMSE = 15.69 µg m−3 for the later. …”
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Applying baseflow approach to the environmental flow needs of the Similkameen River Watershed in British Columbia, Canada by Hongli Chen, Qiang Li, Qiaoqiao Wang, Xuanjiao Chai, Yaping Wang

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Nutritional Quality, Potential Health Promoting Properties and Sensory Perception of an Improved Gluten Free Bread Formulation Containing Inulin, Rice Protein and Bioactive Compoun... by Alessandro Guglielmetti, Beatriz Fernandez-Gomez, Giuseppe Zeppa, Dolores del Castillo

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Carbon Credits Through Wood Use: Revisiting the Maximum Potential and Sensitivity to Key Assumptions by Jari Niemi, Sampo Soimakallio, Elias Hurmekoski, Tanja Myllyviita, Janni Kunttu, Federico Lingua, Tord Snäll

“…However, they were very likely to be considerably lower than forest carbon debits resulting from harvesting additional wood for substitution under all considered circumstances and under a wide but reasonable range of stochastic parameter values. …”
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Ulitníky pseudokrasovej tiesňavy Parkaň v pohorí Bachureň na východnom Slovensku by Jakub Repaský, Dagmar Říhová, Kateřina Kubíková, Radovan Coufal, Jan Oravec, Lucie Juřičková

“…These were predominantly forest species (38; 73%), euryvalent species were less represented (13; 25%), and one open country species was also found (1; 2%). …”
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Fortifying IoT Infrastructure Using Machine Learning for DDoS Attack within Distributed Computing-based Routing in Networks by Sharaf Aldeen Abdulkadhum Abbas, Abdullahi Abdu Ibrahim

“…Our results indicate that Random Forest outperforms the other models, achieving an accuracy of 99.2%, a false positive rate of 0.8%, and an AUC-ROC of 0.997. …”
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Overestimating Impacts of Urbanization on Regional Temperatures in Developing Megacity: Beijing as an Example by Wei Cao, Lin Huang, Lulu Liu, Jun Zhai, Dan Wu

“…Comparing the temperature trends of land-use types, forest showed stronger inhibitory effects on temperature increase (−0.085°C/10a). …”
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Tree Diversity and Damage by Cypress Aphid, Cinara cupressi, on Juniperus procera in Gulele Botanical Garden and Entoto by Sitotaw Kebede, Tewodros Mulugeta

“…However, the level of cypress aphid damage on J. procera has never been studied in Entoto Mountain forest and Gullele Botanical Garden (GBG) in Ethiopia. …”
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Hybridize Machine Learning Methods and Optimization Techniques to Analyze and Repair Welding Defects via Digital Twin of Jidoka Simulator by Ahmed M. Abed, Tamer S. Gaafar

“…Hybridising the Random-Forest algorithm with Dingo optimisation and called Regulated Random Forest (RRF) to precisely identify defect clusters and then predict the welding defect growth rate (<inline-formula> <tex-math notation="LaTeX">$\boldsymbol {{R}_{s}}$ </tex-math></inline-formula>) using the Cat-boost optimiser, which is enhanced by a beetle search mechanism called CatBAS. …”
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