Nonlinear Quantile Mixed-Effects Models for Prediction of the Maximum Crown Width of <i>Fagus sylvatica</i> L., <i>Pinus nigra</i> Arn. and <i>Pinus brutia</i> Ten.
In the current study, a novel approach combining quantile regression with nonlinear mixed-effects (<i>QR-NLME</i>) modeling was applied to predict the maximum crown width (<i>cw<sub>max</sub></i>) of three economically important forest species—the European beech (...
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MDPI AG
2022-03-01
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| Online Access: | https://www.mdpi.com/1999-4907/13/4/499 |
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| author | Dimitrios I. Raptis Vassiliki Kazana Stavros Kechagioglou Angelos Kazaklis Christos Stamatiou Dimitra Papadopoulou Thekla Tsitsoni |
| author_facet | Dimitrios I. Raptis Vassiliki Kazana Stavros Kechagioglou Angelos Kazaklis Christos Stamatiou Dimitra Papadopoulou Thekla Tsitsoni |
| author_sort | Dimitrios I. Raptis |
| collection | DOAJ |
| description | In the current study, a novel approach combining quantile regression with nonlinear mixed-effects (<i>QR-NLME</i>) modeling was applied to predict the maximum crown width (<i>cw<sub>max</sub></i>) of three economically important forest species—the European beech (<i>Fagus sylvatica</i> L.), the black pine (<i>Pinus nigra</i> Arn.), and the Calabrian pine (<i>Pinus brutia</i> Ten.) at tree level. A power <i>QR-NLME</i> model was fitted first to a dataset including 1414 European beech trees obtained from 29 randomly distributed sample plots, 770 black pine trees from 25 sample plots, and 1880 Calabrian pine trees from 41 sample plots in Greece, to predict the <i>cw<sub>max</sub></i> at tree level. Additionally, a nonlinear mixed-effects model (<i>NLME</i>) was fitted to the same dataset to predict the average crown width at tree level for all species. In the second stage, the crown competition factor (<i>CCF</i>) was estimated based on the population average response of the <i>cw<sub>max</sub></i> predictions. The proposed approach presented sound results when compared with the outcomes of relevant models from other regions fitted to open-grown tree data, and therefore, it can be well implemented on clustered data structures, in cases of absence of open-grown tree data. |
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| institution | Directory Open Access Journal |
| issn | 1999-4907 |
| language | English |
| last_indexed | 2024-03-09T13:40:13Z |
| publishDate | 2022-03-01 |
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| series | Forests |
| spelling | doaj.art-4d46560b2da043e3a6098dd69c79d9a82023-11-30T21:07:55ZengMDPI AGForests1999-49072022-03-0113449910.3390/f13040499Nonlinear Quantile Mixed-Effects Models for Prediction of the Maximum Crown Width of <i>Fagus sylvatica</i> L., <i>Pinus nigra</i> Arn. and <i>Pinus brutia</i> Ten.Dimitrios I. Raptis0Vassiliki Kazana1Stavros Kechagioglou2Angelos Kazaklis3Christos Stamatiou4Dimitra Papadopoulou5Thekla Tsitsoni6Department of Forest and Natural Environment Sciences, International Hellenic University, 66100 Drama, GreeceDepartment of Forest and Natural Environment Sciences, International Hellenic University, 66100 Drama, GreeceDepartment of Forestry and Natural Environment, Aristotle University of Thessaloniki, P.O. Box 262, 54124 Thessaloniki, GreeceOLYMPOS-Centre for Integrated Environmental Management, Kalamaria, 55132 Thessaloniki, GreeceDepartment of Forest and Natural Environment Sciences, International Hellenic University, 66100 Drama, GreeceDepartment of Forest and Natural Environment Sciences, International Hellenic University, 66100 Drama, GreeceDepartment of Forestry and Natural Environment, Aristotle University of Thessaloniki, P.O. Box 262, 54124 Thessaloniki, GreeceIn the current study, a novel approach combining quantile regression with nonlinear mixed-effects (<i>QR-NLME</i>) modeling was applied to predict the maximum crown width (<i>cw<sub>max</sub></i>) of three economically important forest species—the European beech (<i>Fagus sylvatica</i> L.), the black pine (<i>Pinus nigra</i> Arn.), and the Calabrian pine (<i>Pinus brutia</i> Ten.) at tree level. A power <i>QR-NLME</i> model was fitted first to a dataset including 1414 European beech trees obtained from 29 randomly distributed sample plots, 770 black pine trees from 25 sample plots, and 1880 Calabrian pine trees from 41 sample plots in Greece, to predict the <i>cw<sub>max</sub></i> at tree level. Additionally, a nonlinear mixed-effects model (<i>NLME</i>) was fitted to the same dataset to predict the average crown width at tree level for all species. In the second stage, the crown competition factor (<i>CCF</i>) was estimated based on the population average response of the <i>cw<sub>max</sub></i> predictions. The proposed approach presented sound results when compared with the outcomes of relevant models from other regions fitted to open-grown tree data, and therefore, it can be well implemented on clustered data structures, in cases of absence of open-grown tree data.https://www.mdpi.com/1999-4907/13/4/499stochastic approximation of the expectation-maximization algorithmcrown competition factorstand densityforest management |
| spellingShingle | Dimitrios I. Raptis Vassiliki Kazana Stavros Kechagioglou Angelos Kazaklis Christos Stamatiou Dimitra Papadopoulou Thekla Tsitsoni Nonlinear Quantile Mixed-Effects Models for Prediction of the Maximum Crown Width of <i>Fagus sylvatica</i> L., <i>Pinus nigra</i> Arn. and <i>Pinus brutia</i> Ten. Forests stochastic approximation of the expectation-maximization algorithm crown competition factor stand density forest management |
| title | Nonlinear Quantile Mixed-Effects Models for Prediction of the Maximum Crown Width of <i>Fagus sylvatica</i> L., <i>Pinus nigra</i> Arn. and <i>Pinus brutia</i> Ten. |
| title_full | Nonlinear Quantile Mixed-Effects Models for Prediction of the Maximum Crown Width of <i>Fagus sylvatica</i> L., <i>Pinus nigra</i> Arn. and <i>Pinus brutia</i> Ten. |
| title_fullStr | Nonlinear Quantile Mixed-Effects Models for Prediction of the Maximum Crown Width of <i>Fagus sylvatica</i> L., <i>Pinus nigra</i> Arn. and <i>Pinus brutia</i> Ten. |
| title_full_unstemmed | Nonlinear Quantile Mixed-Effects Models for Prediction of the Maximum Crown Width of <i>Fagus sylvatica</i> L., <i>Pinus nigra</i> Arn. and <i>Pinus brutia</i> Ten. |
| title_short | Nonlinear Quantile Mixed-Effects Models for Prediction of the Maximum Crown Width of <i>Fagus sylvatica</i> L., <i>Pinus nigra</i> Arn. and <i>Pinus brutia</i> Ten. |
| title_sort | nonlinear quantile mixed effects models for prediction of the maximum crown width of i fagus sylvatica i l i pinus nigra i arn and i pinus brutia i ten |
| topic | stochastic approximation of the expectation-maximization algorithm crown competition factor stand density forest management |
| url | https://www.mdpi.com/1999-4907/13/4/499 |
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