Forest Biometrics, Inventory, and Modelling of Growth and Yield

A special issue of Forests (ISSN 1999-4907). This special issue belongs to the section "Forest Inventory, Modeling and Remote Sensing".

Deadline for manuscript submissions: 31 July 2024 | Viewed by 1688

Special Issue Editors


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Guest Editor
Departamento de Engenharia, Campus Professora Cinobelina Elvas, Universidade Federal do Piauí, Bom Jesus 64900-000, PI, Brazil
Interests: African mahogany; clear wood production; diameter distributions; dominant height; Eucalyptus plantations; fast growing plantations; forest biomass; forest economy; forest inventory; forest management; forest regeneration; growing space; growth and yield models; height-diameter equations; high-value timber species; horizontal structure; individual tree models; Khaya grandifoliola; leaf area removal; native forest; probability density functions; pruning; reforestation; seasonally dry tropical forests; sampling intensity; site index; solid wood products; species selection; stand density management; thinning; volume equations

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Guest Editor
Instituto de Florestas, Universidade Federal Rural do Rio de Janeiro, Seropédica, Rio de Janeiro 23890-000, Brazil
Interests: Amazonian timber species; commercial timber; diametric structure; forest management; forestry production; geographic information system; geoprocessing; inventory accuracy; merchantable volume; modelling; native woods; national forest inventory; productive capacity; sensors; spatial dependence; suitability maps; uneven-aged forest; spatial distribution; volume equations

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Guest Editor
Fiber Supply Assessment, WSFNR, University of Georgia, Athens, GA 30602, USA
Interests: ADA (algebraic difference approach); GADA (generalized algebraic difference approach); self-referencing functions; self-referencing models; implicit equations; dynamic equations; projection equations; projection models; base-age invariance; path invariance; indifference under reparametrization parameter estimation; model conditioning; well-behaved model; pooled cross-sectional and longitudinal data models; site models; site index models; site-height-age models; anamorphism; polymorphism; complex polymorphism; fixed-effects vs. mixed-effects parameter estimation of self-referencing models; subject specific parameter estimation; variable parameter models

Special Issue Information

Dear Colleagues,

Data-gathering procedures applied in forest trees and stands constitute a fundamental step pertaining to the knowledge and sustainable use of these important resources. In an age where the well-being of humanity is in serious check due to the high reliance in fossil derived fuel and products, solutions based in renewable sources are highly desired. The natural variability of forests will require significant scientific advances in all areas pertaining to the knowledge of current standing stocks and how these stocks will change in the future. Thus, this Special Issue welcomes all studies (i.e., review and research articles) that bring new data and methods about: i) forest biometrics; ii) forest inventory procedures; iii) modeling of forest growth and yield. We welcome studies conducted in all types of trees (e.g., urban, isolated, in rural integration) and forests (e.g., natural, planted, productive, protective) and we particularly encourage studies from underreported areas, such as tropical forests located in low-income countries.

Prof. Dr. Antonio Carlos Ferraz Filho
Prof. Dr. Emanuel José Gomes De Araújo
Prof. Dr. Chris Cieszewski
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Forests is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • mensuration
  • growth dynamics
  • forest management
  • forest inventory
  • data collection
  • remote sensing
  • silviculture
  • statistical methods
  • resource assessment

Published Papers (2 papers)

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Research

16 pages, 1394 KiB  
Article
A Comparison of Probability Density Functions Fitted by Moments and Maximum Likelihood Estimation Methods Used for Diameter Distribution Estimation
by Jose Javier Gorgoso-Varela, Segun M. Adedapo and Friday N. Ogana
Forests 2024, 15(3), 425; https://doi.org/10.3390/f15030425 - 22 Feb 2024
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Abstract
Modeling diameter distribution is a crucial aspect of forest management, requiring the selection of an appropriate probability density function or cumulative distribution function along with a fitting method. This study compared the suitability of eight probability density functions—A Charlier, beta, generalized beta, gamma, [...] Read more.
Modeling diameter distribution is a crucial aspect of forest management, requiring the selection of an appropriate probability density function or cumulative distribution function along with a fitting method. This study compared the suitability of eight probability density functions—A Charlier, beta, generalized beta, gamma, Gumbel, Johnson’s SB, and Weibull (two- and three-parameter)—fitted using both derivative methods (Moments) fitted in SAS/STATTM and optimization methods (MLE) fitted with the ‘optim’ function in R for diameter distribution estimation in forest stands. The A Charlier and Gumbel functions were used for the first time in this type of comparison. The data were derived from 167 permanent sample plots in an Atlantic forest (Quercus robur) and 59 temporary sample plots in tropical forests (Tectona grandis). Fit quality was assessed using various indices, including Kolmogorov–Smirnov, Cramér–von Mises, mean absolute error, bias, and mean squared error. The results indicated that Johnson’s SB function was more suitable for describing the diameter distribution of the stands. Johnson’s SB, three-parameter Weibull, and generalized beta consistently performed well across different fitting methods, while the fits produced by gamma, Gumbel, and two-parameter Weibull were of poor quality. Full article
(This article belongs to the Special Issue Forest Biometrics, Inventory, and Modelling of Growth and Yield)
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19 pages, 5571 KiB  
Article
Improving Volume and Biomass Equations for Pinus oocarpa in Nicaragua
by Luis Alberto Valerio Hernández, Walter Antonio Campos Vanegas, Luis Enrique Cruz Tórrez, José Adolfo Peña Ortiz and Benedicto Vargas-Larreta
Forests 2024, 15(2), 309; https://doi.org/10.3390/f15020309 - 06 Feb 2024
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Abstract
We present a new set of equations for tree level volume and aboveground biomass estimation for ocote pine (Pinus oocarpa Schiede ex Schltdl). These equation systems are the first developed for this species in Nicaragua. The first system includes a taper function, [...] Read more.
We present a new set of equations for tree level volume and aboveground biomass estimation for ocote pine (Pinus oocarpa Schiede ex Schltdl). These equation systems are the first developed for this species in Nicaragua. The first system includes a taper function, a merchantable volume equation, and volume equations for stem, coarse branches, and whole trees. The second system estimates whole tree and individual tree component biomass (stem wood, bark, branches, and needles). Data from 112 sampled trees were used for models’ development. Seemingly Unrelated Iterative Regression and the Generalized Method of Moments were used to simultaneously fit the volume and biomass equations systems, respectively; both methods ensure additivity and compatibility between equations. Weighted regression and a second-order continuous autoregressive error structure were used to correct heteroscedasticity and autocorrelation within the hierarchical dataset. The predictive power of the new proposed equations is higher than the currently used models for P. oocarpa in the country. These equation systems represent a scientific advancement that will enhance forest inventories, optimize timber management of the species, and facilitate accurate monitoring of forest carbon dynamics. Additionally, the new equations will contribute to a more precise accounting of CO2 emissions from the country’s forestry sector. Full article
(This article belongs to the Special Issue Forest Biometrics, Inventory, and Modelling of Growth and Yield)
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