linear mixed model to describe the basal area increment for indivudual cedro (cedrela odorata l.)trees in occidental amazon, brazil

Clicks: 16
ID: 178259
2013
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #138 of 152 articles by views in journal of organic chemistry

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 152 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Abstract

http://dx.doi.org/10.5902/1980509810557

Reliable growth data from trees are important to establish a rational forest management. Characteristics from trees, like the size, crown architecture and competition indices have been used to mathematically describe the increment efficiently when associated with them. However, the precise role of these effects in the growth-modeling destined to tropical trees needs to be further studied. Here we reconstructed the basal area increment (BAI) of individual Cedrelaodorata trees, sampled at Amazon forest, to develop a growth-model using potential-predictors like: (1) classical tree size; (2) morphometric data; (3) competition and (4) social position including liana loads. Despite the large variation in tree size and growth, we observed that these kinds of predictor variables described well the BAI in level of individual tree. The fitted mixed model achieve a high efficiency (R2=92.7 %) and predicted 3-years BAI over bark for trees of Cedrelaodorata ranging from 10 to 110 cm at diameter at breast height. Tree height, steam slenderness and crown formal demonstrated high influence in the BAI growth model and explaining most of the growth variance (Partial R2=87.2%). Competition variables had negative influence on the BAI, however, explained about 7% of the total variation. The introduction of a random parameter on the regressions model (mixed modelprocedure) has demonstrated a better significance approach to the data observed and showed more realistic predictions than the fixed model.

Reference Key
cunha2013cincialinear Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Thiago Augusto da Cunha;César Augusto Guimarães Finger;Paulo Renato Schneider
Journal journal of organic chemistry
Year 2013
DOI
10.5902/1980509810557
URL
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

No comments yet. Be the first to comment on this article.