A method to derive a tree survival model from any existing stand survival model
This study addresses a situation in which a forest manager has been using a whole-stand model that seems to predict well for their stands and now wants to derive an individual-tree model from it to form an integrated system that can perform well at both stand and tree levels. A simple method was dev...
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Veröffentlicht in: | Canadian journal of forest research 2019-12, Vol.49 (12), p.1598-1603 |
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creator | Cao, Quang V |
description | This study addresses a situation in which a forest manager has been using a whole-stand model that seems to predict well for their stands and now wants to derive an individual-tree model from it to form an integrated system that can perform well at both stand and tree levels. A simple method was developed to derive tree survival models from three existing stand-level survival models. The derived tree survival models were based on the difference between the diameter of a given tree and the diameter at which tree and stand survival probabilities are equal. For stand survival prediction, each stand model performed less adequately than its derived tree model, and one of the derived tree survival models was the best overall. For tree survival prediction, the same derived tree model also performed best overall. Even though only three stand-level survival models were considered in this study, the method presented here should be applicable to any stand survival model. When no tree survival data were available, tree survival models derived from stand survival models ranked lowest in terms of performance but produced acceptable evaluation statistics for predicting tree-level survival. |
doi_str_mv | 10.1139/cjfr-2019-0171 |
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A simple method was developed to derive tree survival models from three existing stand-level survival models. The derived tree survival models were based on the difference between the diameter of a given tree and the diameter at which tree and stand survival probabilities are equal. For stand survival prediction, each stand model performed less adequately than its derived tree model, and one of the derived tree survival models was the best overall. For tree survival prediction, the same derived tree model also performed best overall. Even though only three stand-level survival models were considered in this study, the method presented here should be applicable to any stand survival model. 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A simple method was developed to derive tree survival models from three existing stand-level survival models. The derived tree survival models were based on the difference between the diameter of a given tree and the diameter at which tree and stand survival probabilities are equal. For stand survival prediction, each stand model performed less adequately than its derived tree model, and one of the derived tree survival models was the best overall. For tree survival prediction, the same derived tree model also performed best overall. Even though only three stand-level survival models were considered in this study, the method presented here should be applicable to any stand survival model. When no tree survival data were available, tree survival models derived from stand survival models ranked lowest in terms of performance but produced acceptable evaluation statistics for predicting tree-level survival.</description><subject>Analysis</subject><subject>Forest management</subject><subject>individual-tree model</subject><subject>least squares</subject><subject>loblolly pine</subject><subject>logistic regression</subject><subject>maximum de vraisemblance</subject><subject>maximum likelihood</subject><subject>Methods</subject><subject>modèle d’arbre individuel</subject><subject>moindres carrés</subject><subject>Performance evaluation</subject><subject>pin à encens</subject><subject>Predictions</subject><subject>régression logistique</subject><subject>Statistical analysis</subject><subject>Studies</subject><subject>Survival</subject><subject>Trees</subject><issn>0045-5067</issn><issn>1208-6037</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNqV0r1rGzEYBnBRWqibds0s2inDJfo6STca07SBEEOSzkLRvbJl7k62JJvkv8-ZZIiLIQQNEuL3vNLwIHRKyTmlvLlwK58qRmhTEaroJzShjOhKEq4-owkhoq5qItVX9C3nFSGES04maD7FPZRlbHGJuIUUdoAtLgkA523ahZ3tcB9b6LBPscd2eMLwGHIJwwLnYof2P_YdffG2y_DjdT9B_y5_38_-VtfzP1ez6XXlatGU6kE5B8QLVlOgjlHZCq50ywX4xoNqNFe1Bs9YozSp2XiSTjjlWw6SeSH4Cfr1Mned4mYLuZhV3KZhfNIwTrWWVOg3amE7MGHwsSTr-pCdmUqiG8Gk1KOqjqgFDJBsFwfwYbw-8D-PeLcOG_MWnR9B42qhD-7o1LODwGgKPJaF3eZsru5uP2BvDu3rR1yKOSfwZp1Cb9OTocTsi2P2xTH74ph9ccYAfQkMySXIYJNbvpd5Bi_KwaA</recordid><startdate>20191201</startdate><enddate>20191201</enddate><creator>Cao, Quang V</creator><general>NRC Research Press</general><general>Canadian Science Publishing NRC Research Press</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ISN</scope><scope>ISR</scope><scope>7SN</scope><scope>7SS</scope><scope>7T7</scope><scope>8FD</scope><scope>C1K</scope><scope>FR3</scope><scope>P64</scope><scope>RC3</scope><scope>U9A</scope></search><sort><creationdate>20191201</creationdate><title>A method to derive a tree survival model from any existing stand survival model</title><author>Cao, Quang V</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c549t-b7cce0f4251e1c216d4378d34ef9fe7983758ef22978052ef26c4c7fd3e62f443</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Analysis</topic><topic>Forest management</topic><topic>individual-tree model</topic><topic>least squares</topic><topic>loblolly pine</topic><topic>logistic regression</topic><topic>maximum de vraisemblance</topic><topic>maximum likelihood</topic><topic>Methods</topic><topic>modèle d’arbre individuel</topic><topic>moindres carrés</topic><topic>Performance evaluation</topic><topic>pin à encens</topic><topic>Predictions</topic><topic>régression logistique</topic><topic>Statistical analysis</topic><topic>Studies</topic><topic>Survival</topic><topic>Trees</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Cao, Quang V</creatorcontrib><collection>CrossRef</collection><collection>Gale In Context: Canada</collection><collection>Gale In Context: Science</collection><collection>Ecology Abstracts</collection><collection>Entomology Abstracts (Full archive)</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Engineering Research Database</collection><collection>Biotechnology and BioEngineering Abstracts</collection><collection>Genetics Abstracts</collection><jtitle>Canadian journal of forest research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Cao, Quang V</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A method to derive a tree survival model from any existing stand survival model</atitle><jtitle>Canadian journal of forest research</jtitle><date>2019-12-01</date><risdate>2019</risdate><volume>49</volume><issue>12</issue><spage>1598</spage><epage>1603</epage><pages>1598-1603</pages><issn>0045-5067</issn><eissn>1208-6037</eissn><abstract>This study addresses a situation in which a forest manager has been using a whole-stand model that seems to predict well for their stands and now wants to derive an individual-tree model from it to form an integrated system that can perform well at both stand and tree levels. A simple method was developed to derive tree survival models from three existing stand-level survival models. The derived tree survival models were based on the difference between the diameter of a given tree and the diameter at which tree and stand survival probabilities are equal. For stand survival prediction, each stand model performed less adequately than its derived tree model, and one of the derived tree survival models was the best overall. For tree survival prediction, the same derived tree model also performed best overall. Even though only three stand-level survival models were considered in this study, the method presented here should be applicable to any stand survival model. When no tree survival data were available, tree survival models derived from stand survival models ranked lowest in terms of performance but produced acceptable evaluation statistics for predicting tree-level survival.</abstract><cop>Ottawa</cop><pub>NRC Research Press</pub><doi>10.1139/cjfr-2019-0171</doi><tpages>6</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Analysis Forest management individual-tree model least squares loblolly pine logistic regression maximum de vraisemblance maximum likelihood Methods modèle d’arbre individuel moindres carrés Performance evaluation pin à encens Predictions régression logistique Statistical analysis Studies Survival Trees |
title | A method to derive a tree survival model from any existing stand survival model |
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