[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124018-en":3,"doc-seo-124018-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},124018,8796095461564,"Liam","https://ap-avatar.wpscdn.com/davatar_155a257f0dc6eb9ab79c44ca47cae57d",8,"Research & Report","Predicting tree survival in agroforestry systems using machine learning classification algorithms","The study applies machine learning classification to predict tree survival in agroforestry systems, where forests underpin ecological balance and biodiversity yet face risks from climate change, human disturbance, diseases, and pests. A dataset incorporating biochemical and symbiotic variables—phenol content, presence of arbuscular mycorrhizal fungi (AMF), lignin, and nonstructural carbohydrates (NSC)—is used to train a C4.5 decision-tree model, achieving 86.02% accuracy. Correlation analysis identifies phenols and AMF as the most significant determinants, supporting improved biochemical and symbiotic management strategies and future research directions for sustainable forest conservation.","Predicting tree survival in agroforestry systems using machine learning classification algorithms  \nKirill Kravtsov1,2*, Vladislav Kukartsev 1,2, Elina Stepanova 3, and Tatiana Soloveva 2  \n1Reshetnev Siberian State University of Science and Technology, 660037, Krasnoyarsk, Russia. 2Bauman Moscow State Technical University, Artificial Intelligence Technology Scientific and Education Center, 105005 Moscow, Russia  \n3Krasnoyarsk State Agrarian University 660049, Krasnoyarsk, Russia  \nAbstract. This article discusses the application of machine learning algorithms to predict the survival of trees in agroforestry systems. Forests play a key role in maintaining ecological balance and biodiversity, but their survival is subject to many threats, including climate change, anthropogenic impacts, diseases and pests. The study used a dataset containing data on various factors affecting the survival of trees, such as the content of phenols, the presence of arbuscular mycorrhizal fungi (AMF), lignin and nonstructural carbohydrates (NSC). The classification model was built using the C4.5 decision tree algorithm, which demonstrated high accuracy (86.02%) in predicting the survival of trees. Correlation analysis revealed that phenolsand AMF are the most significant factors determining the survival of trees.  \nThese results highlight the importance of biochemical and symbiotic factors for tree health. The article also discusses the importance of various factors and suggests directions for future research aimed at improving the management of forest ecosystems in agroforestry systems. The use of machine learning methods allows not only to improve the accuracy of forecasting, but also to develop more effective strategies for the conservation  \nand sustainable management of forests.  \n1 Introduction  \nForests play a key role in maintaining ecological balance and biodiversity. They are home to many species of plants and animals, participate in the carbon and water cycle, promote soil formation and prevent erosion. Forests also have a significant impact on climate by absorbing carbon dioxide and releasing oxygen, which helps mitigate the effects of global warming. Despite their importance, forest ecosystems face many threats, including climate change, anthropogenic impacts, diseases and pests [1, 2] . Figure 1 shows an illustration of what a forest ecosystem with affected trees looks like.  \n* Corresponding author: [rhfdwjdr1@gmail.com](rhfdwjdr1@gmail.com)  \n© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 ([https://creativecommons.org/licenses/by/4.0/](https://creativecommons.org/licenses/by/4.0/)).  \nFig. 1. Forest ecosystem: tree survival and biodiversity.  \nClimate change, which leads to changes in temperature and precipitation patterns, can negatively affect forest health. Anthropogenic impacts such as deforestation, urbanization and pollution also seriously threaten forest ecosystems. Diseases and pests such as bark beetles and fungal infections can destroy large areas of forests, which highlights the need to develop methods to predict the survival of trees [2, 3] .  \nVarious methods and algorithms are used to predict the survival of trees, including decision trees (C4.5, Random Forest), neural networks and support vector machines (SVMs) . Classification and regression methods such as CART and its derivatives (bagging, random forests) are often used to analyze the survival of trees. These methods are useful for creating classification and forecasting rules based on data on the characteristics of trees and the environment [4] .  \nNeural networks can capture complex nonlinear relationships between input variables and tree survival, which makes them useful for forecasting in complex ecosystems. Support vector machines (SVMs) are used for classification and regression in tree survival tasks, providing accurate predictions based on the analysis of hi","cbCaierlMBYnj32S","https://ap.wps.com/l/cbCaierlMBYnj32S","pdf",2236722,1,7,"English","en",105,"# Abstract\n# 1 Introduction\n## Threats to forest ecosystems and need for prediction\n## Prior prediction methods and model families\n## Comparative strengths and limitations of classifiers\n# 2 Materials and methods\n## Dataset description\n## Data preprocessing: missing values, normalization, encoding","[{\"question\":\"How does the study predict tree survival in agroforestry systems?\",\"answer\":\"It uses a classification approach with a C4.5 decision-tree algorithm trained on environmental and biochemical factors related to tree health and survival.\"},{\"question\":\"What dataset features are emphasized in the model?\",\"answer\":\"The dataset includes phenol content, AMF presence, lignin, and nonstructural carbohydrates (NSC) as key factors affecting survival.\"},{\"question\":\"Which factors most influence tree survival according to the analysis?\",\"answer\":\"Correlation analysis shows phenols and AMF are the most significant determinants for predicting tree survival.\"}]","Predicting tree survival in agroforestry systems using machine learning classification algorithms | PDF",1785819890,18,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"predicting-tree-survival-in-agroforestry-systems-using-machine-learning-classification-algorithms","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/predicting-tree-survival-in-agroforestry-systems-using-machine-learning-classification-algorithms/124018/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"How does the study predict tree survival in agroforestry systems?","Question",{"text":75,"@type":76},"It uses a classification approach with a C4.5 decision-tree algorithm trained on environmental and biochemical factors related to tree health and survival.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What dataset features are emphasized in the model?",{"text":80,"@type":76},"The dataset includes phenol content, AMF presence, lignin, and nonstructural carbohydrates (NSC) as key factors affecting survival.",{"name":82,"@type":73,"acceptedAnswer":83},"Which factors most influence tree survival according to the analysis?",{"text":84,"@type":76},"Correlation analysis shows phenols and AMF are the most significant determinants for predicting tree survival.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,119,122,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},9,"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]