A generalized nonlinear mixed-effects height to crown base model for Mongolian oak in northeast China

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60460709%3A41320%2F17%3A71970" target="_blank" >RIV/60460709:41320/17:71970 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.foreco.2016.09.012" target="_blank" >http://dx.doi.org/10.1016/j.foreco.2016.09.012</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.foreco.2016.09.012" target="_blank" >10.1016/j.foreco.2016.09.012</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A generalized nonlinear mixed-effects height to crown base model for Mongolian oak in northeast China

Popis výsledku v původním jazyce

Tree height to crown base (HCB) is an important variable commonly included as one of the predictors in growth and yield models that are the decision-support tools in forest management. In this study, we developed a generalized nonlinear mixed-effects individual tree HCB model using data from a total of 3133 Mongolian oak (Quercus mongolica) trees on 112 sample plots allocated in Wangqing Forest Bureau of northeast China. Because observations taken from same sample plots were highly correlated with each other, the random effects at the levels of both sample plots and stands with different site conditions (blocks) were taken into consideration to develop a two-level nonlinear mixed-effects HCB model. The results showed that the significant predictors included total tree height, diameter at breast height (DBH), dominant height, and total basal area of all trees with DBH larger than a target tree per sample plot. Modelling the random effects at block level alone led to highly significant correla

Název v anglickém jazyce

A generalized nonlinear mixed-effects height to crown base model for Mongolian oak in northeast China

Popis výsledku anglicky

Tree height to crown base (HCB) is an important variable commonly included as one of the predictors in growth and yield models that are the decision-support tools in forest management. In this study, we developed a generalized nonlinear mixed-effects individual tree HCB model using data from a total of 3133 Mongolian oak (Quercus mongolica) trees on 112 sample plots allocated in Wangqing Forest Bureau of northeast China. Because observations taken from same sample plots were highly correlated with each other, the random effects at the levels of both sample plots and stands with different site conditions (blocks) were taken into consideration to develop a two-level nonlinear mixed-effects HCB model. The results showed that the significant predictors included total tree height, diameter at breast height (DBH), dominant height, and total basal area of all trees with DBH larger than a target tree per sample plot. Modelling the random effects at block level alone led to highly significant correla

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

40102 - Forestry

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2017

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Forest Ecology and Management

ISSN

0378-1127

e-ISSN

—

Svazek periodika

384

Číslo periodika v rámci svazku

JAN

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

10

Strana od-do

34-43

Kód UT WoS článku

000390727600005

EID výsledku v databázi Scopus

2-s2.0-84994035479