Modeling individual-tree mortality in Pyrenean oak (Quercus pyrenaica Willd.) stands

Tree mortality is an important process in forest ecosystem dynamics and is one of the least understood phenomena, because of the complex interactions between different environmental stresses, minimal understanding of whole-plant mortality processes, and a chronic shortage of data. A multilevel logistic regression model was developed for predicting the probability of mortality in individual trees with the objective of improving long-term planning in Spanish pyrenean oak forests. The data came from one 10-year re-measurement of the permanent plot network belonging to the Spanish National Forest Inventory distributed throughout north-west Spain. The probability of mortality decreased with increasing individual diameter at breast height and increasing ratio of the height of subject tree to the dominant height of the sample plot. The resulting mortality model was evaluated using an independent data set from a region close to the study area. The regeneration of pyrenean oak generally takes place through stump and/or root sprouting; so stand dynamics differ from those of others species. The model developed is expected to improve the accuracy of stand forecasts in northwest Spain. © 2010 INRA, EDP Sciences.

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Bibliographic Details
Main Authors: Adame, P., del Río, M., Cañellas, I.
Format: artículo biblioteca
Language:English
Published: BioMed Central 2010
Subjects:Individual-tree mortality model, Logistic regression, Mixed model, Rebollo oak, Mediteranean oak,
Online Access:http://hdl.handle.net/20.500.12792/1296
http://hdl.handle.net/10261/292249
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spelling dig-inia-es-10261-2922492023-02-20T07:27:01Z Modeling individual-tree mortality in Pyrenean oak (Quercus pyrenaica Willd.) stands Adame, P. del Río, M. Cañellas, I. Individual-tree mortality model Logistic regression Mixed model Rebollo oak Mediteranean oak Tree mortality is an important process in forest ecosystem dynamics and is one of the least understood phenomena, because of the complex interactions between different environmental stresses, minimal understanding of whole-plant mortality processes, and a chronic shortage of data. A multilevel logistic regression model was developed for predicting the probability of mortality in individual trees with the objective of improving long-term planning in Spanish pyrenean oak forests. The data came from one 10-year re-measurement of the permanent plot network belonging to the Spanish National Forest Inventory distributed throughout north-west Spain. The probability of mortality decreased with increasing individual diameter at breast height and increasing ratio of the height of subject tree to the dominant height of the sample plot. The resulting mortality model was evaluated using an independent data set from a region close to the study area. The regeneration of pyrenean oak generally takes place through stump and/or root sprouting; so stand dynamics differ from those of others species. The model developed is expected to improve the accuracy of stand forecasts in northwest Spain. © 2010 INRA, EDP Sciences. 2023-02-20T07:27:01Z 2023-02-20T07:27:01Z 2010 artículo Annals of Forest Science 67: e810 (2010) 1286-4560 http://hdl.handle.net/20.500.12792/1296 http://hdl.handle.net/10261/292249 10.1051/forest/2010046 1297-966X en none BioMed Central
institution INIA ES
collection DSpace
country España
countrycode ES
component Bibliográfico
access En linea
databasecode dig-inia-es
tag biblioteca
region Europa del Sur
libraryname Biblioteca del INIA España
language English
topic Individual-tree mortality model
Logistic regression
Mixed model
Rebollo oak
Mediteranean oak
Individual-tree mortality model
Logistic regression
Mixed model
Rebollo oak
Mediteranean oak
spellingShingle Individual-tree mortality model
Logistic regression
Mixed model
Rebollo oak
Mediteranean oak
Individual-tree mortality model
Logistic regression
Mixed model
Rebollo oak
Mediteranean oak
Adame, P.
del Río, M.
Cañellas, I.
Modeling individual-tree mortality in Pyrenean oak (Quercus pyrenaica Willd.) stands
description Tree mortality is an important process in forest ecosystem dynamics and is one of the least understood phenomena, because of the complex interactions between different environmental stresses, minimal understanding of whole-plant mortality processes, and a chronic shortage of data. A multilevel logistic regression model was developed for predicting the probability of mortality in individual trees with the objective of improving long-term planning in Spanish pyrenean oak forests. The data came from one 10-year re-measurement of the permanent plot network belonging to the Spanish National Forest Inventory distributed throughout north-west Spain. The probability of mortality decreased with increasing individual diameter at breast height and increasing ratio of the height of subject tree to the dominant height of the sample plot. The resulting mortality model was evaluated using an independent data set from a region close to the study area. The regeneration of pyrenean oak generally takes place through stump and/or root sprouting; so stand dynamics differ from those of others species. The model developed is expected to improve the accuracy of stand forecasts in northwest Spain. © 2010 INRA, EDP Sciences.
format artículo
topic_facet Individual-tree mortality model
Logistic regression
Mixed model
Rebollo oak
Mediteranean oak
author Adame, P.
del Río, M.
Cañellas, I.
author_facet Adame, P.
del Río, M.
Cañellas, I.
author_sort Adame, P.
title Modeling individual-tree mortality in Pyrenean oak (Quercus pyrenaica Willd.) stands
title_short Modeling individual-tree mortality in Pyrenean oak (Quercus pyrenaica Willd.) stands
title_full Modeling individual-tree mortality in Pyrenean oak (Quercus pyrenaica Willd.) stands
title_fullStr Modeling individual-tree mortality in Pyrenean oak (Quercus pyrenaica Willd.) stands
title_full_unstemmed Modeling individual-tree mortality in Pyrenean oak (Quercus pyrenaica Willd.) stands
title_sort modeling individual-tree mortality in pyrenean oak (quercus pyrenaica willd.) stands
publisher BioMed Central
publishDate 2010
url http://hdl.handle.net/20.500.12792/1296
http://hdl.handle.net/10261/292249
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