scholarly journals Stand Diameter Distribution Modeling and Prediction Based on Maximum Entropy Principle

Forests ◽  
2019 ◽  
Vol 10 (10) ◽  
pp. 859 ◽  
Author(s):  
Yuling Chen ◽  
Baoguo Wu ◽  
Zhiqiang Min
Keyword(s):  
Weibull Distribution ◽  
Maximum Entropy ◽  
Measurement Data ◽  
Similarity Index ◽  
Distribution Model ◽  
Diameter Distribution ◽  
Weibull Function ◽  
Prediction Ability ◽  
Actual Distribution ◽  
Modeling And Prediction

Research Highlights: Improving the prediction accuracy represents a popular forest simulation modeling issue, and exploring the optimal maximum entropy (MaxEnt) distribution is a new effective method for improving the diameter distribution model simulation precision to overcome the disadvantages of Weibull. Background and Objectives: The MaxEnt distribution is the closest to the actual distribution under the constraints, which are the main probability density distributions. However, relatively few studies have addressed the optimization of stand diameter distribution based on MaxEnt distribution. The objective of this study was to introduce application of the MaxEnt distribution on modeling and prediction of stand diameter distribution. Materials and Methods: The long-term repeated measurement data sets consisted of 260 diameter frequency distributions from China fir (Cunninghamia lanceolate (Lamb.) Hook) plantations in the southern China Guizhou. The Weibull distribution and the MaxEnt distribution were applied to the fitting of stand diameter distribution, and the modeling and prediction characteristics of Weibull distribution and MaxEnt distribution to stand diameter distribution were compared. Results: Three main conclusions were obtained: (1) MaxEnt distribution presented a more accurate simulation than three-parametric Weibull function; (2) the Chi-square test showed diameter distributions of unknown stands can be well estimated by applying MaxEnt distribution based on the plot similarity index method (PSIM) and Weibull distribution based on the parameter prediction method (PPM); (3) the MaxEnt model can deal with the complex nonlinear relationship and show strong prediction ability when predicting the stand distribution structure. Conclusions: With the increase of sample size, the PSIM has great application prospects in the dynamic prediction system of stand diameter distribution.

Performance of Weibull function as a diameter distribution model for Pinus thunbergii stands in the eastern coast of South Korea

2016 ◽  
Vol 13 (5) ◽  
pp. 822-830 ◽  
Author(s):  
Azyleah Cañizares Abino ◽  
Sung Yong Kim ◽  
Roscinto Ian Canicosa Lumbres ◽  
Mi Na Jang ◽  
Ho Joong Youn ◽  
...  
Keyword(s):  
South Korea ◽  
Pinus Thunbergii ◽  
Distribution Model ◽  
Diameter Distribution ◽  
Eastern Coast ◽  
Weibull Function

scholarly journals Application of diameter distribution model for volume estimation in Tectona grandis L.f. stands in the Oluwa forest reserve, Nigeria

2020 ◽  
Vol 7 (3) ◽  
pp. 573-580
Author(s):  
I. Y. Egonmwan ◽  
◽  
F. N. Ogana ◽  
Keyword(s):  
Weibull Distribution ◽  
Tectona Grandis ◽  
Volume Estimation ◽  
Distribution Model ◽  
Diameter Distribution ◽  
Distribution Models ◽  
Forest Reserve ◽  
Relative Rank ◽  
Silvicultural Treatments ◽  
Product Specifications

The ability to predict the distribution of diameters in a stand is essential for forest managers to make informed management decisions such as prescription of silvicultural treatments and harvesting regimes. Such information is preferably derived from suitable distribution model. This study evaluated the performance of four distribution models in describing the structure of the teak stands in Oluwa Forest Reserve, Nigeria. Data were collected from 12 temporary sample plots of 20 × 20 m size in the teak stand. Maximum likelihood estimator was used to fit the distribution models: beta, gamma, Johnson SB, and Weibull to the diameter data from the teak stand. Relative rank-sum derived from four indices was used to conclude on the most suitable distribution for the stand. The results showed that the Weibull distribution was the most suitable function for the teak stand with a relative rank-sum of 4.0. Application of Weibull distribution together with suitable height-diameter and volume models estimated yield of 136.281 m3 ha-1 within timber size class (diameter ≥30 cm). And a total of 309.640 m3 ha-1 was estimated for the stand. Other product specifications were also provided. This would help in the routine management of the stand.

scholarly journals MODEL DISTRIBUSI DIAMETER LIMA JENIS POHON PADA HUTAN TROPIKA BASAH DI KABUPATEN MAMUJU, SULAWESI BARAT

PERENNIAL ◽  
2010 ◽  
Vol 6 (1) ◽  
pp. 44
Author(s):  
Beta Putranto
Keyword(s):  
Tree Species ◽  
Polynomial Function ◽  
Natural Forest ◽  
Distribution Model ◽  
Diameter Distribution ◽  
Weibull Function ◽  
Suitable Model ◽  
Stem Number ◽  
Tree Diameter ◽  
Tree Diameter Distribution

The objective of this research is to establish the most suitable tree diameter distribution model for five tree species on tropical rain forest in Mamuju District. This research was conducted on two locations. The 50 square plots were sampled systematically for seedling, sapling, pole and tree measurements of bintangur, jambu-jambu, lada-lada, matoa and nyatoh species. The distance among plots was 50 m. Variables to be measured were stem number of seedlings to trees and tree diameter at breast height (1,3 m) of saplings to trees. About 70% of the data were used to establish the best model, the rest of 30% were used to validate the model. Models to be analyzed were fourth-order semi-logarithmic transformed polynomial function, Weibull density function and monotonic decreasing Weibull function. The results show that the five tree species have a similar diameter distribution pattern. The shape of this distribution is the typical of uneven-aged stand distribution on natural forest, namely reversed J shape. The most suitable model for five species is second-order semi-logarithmic transformed polynomial function. Key words: model, diameter distribution, natural forest, uneven-aged stand.

A Blind Spot in the Use of the Weibull Function for Modeling Diameter Distributions

2020 ◽  
Author(s):  
Adrian Norman Goodwin
Keyword(s):  
Lower Bound ◽  
Blind Spot ◽  
Forest Growth ◽  
Growth And Yield ◽  
Diameter Distribution ◽  
Absolute Difference ◽  
Weibull Function ◽  
Distribution Models ◽  
Difference Statistic ◽  
Diameter Distributions

Abstract Diameter distribution models based on probability density functions are integral to many forest growth and yield systems, where they are used to estimate product volumes within diameter classes. The three-parameter Weibull function with a constrained nonnegative lower bound is commonly used because of its flexibility and ease of fitting. This study compared Weibull and reverse Weibull functions with and without a lower bound constraint and left-hand truncation, across three large unthinned plantation cohorts in which 81% of plots had negatively skewed diameter distributions. Near-optimal lower bounds for the unconstrained Weibull function were negative for negatively skewed data, and the left-truncated Weibull using these bounds was 14.2% more accurate than the constrained Weibull, based on the Kolmogorov-Smirnov statistic. The truncated reverse Weibull fit dominant tree distributions 23.7% more accurately than the constrained Weibull, based on a mean absolute difference statistic. This work indicates that a blind spot may have developed in plantation growth modeling systems deploying constrained Weibull functions, and that left-truncation of unconstrained functions could substantially improve model accuracy for negatively skewed distributions.

scholarly journals A Bioclimate-Based Maximum Entropy Model for Comperiella calauanica Barrion, Almarinez and Amalin (Hymenoptera: Encyrtidae) in the Philippines

Insects ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 26
Author(s):  
Billy Joel M. Almarinez ◽  
Mary Jane A. Fadri ◽  
Richard Lasina ◽  
Mary Angelique A. Tavera ◽  
Thaddeus M. Carvajal ◽  
...  
Keyword(s):  
Maximum Entropy ◽  
Habitat Suitability ◽  
Species Distribution Model ◽  
Biological Control Agent ◽  
The Philippines ◽  
Distribution Model ◽  
Field Surveys ◽  
Probability Of Occurrence ◽  
Precipitation Seasonality ◽  
Bioclimatic Variables

Comperiella calauanica is a host-specific endoparasitoid and effective biological control agent of the diaspidid Aspidiotus rigidus, whose outbreak from 2010 to 2015 severely threatened the coconut industry in the Philippines. Using the maximum entropy (Maxent) algorithm, we developed a species distribution model (SDM) for C. calauanica based on 19 bioclimatic variables, using occurrence data obtained mostly from field surveys conducted in A. rigidus-infested areas in Luzon Island from 2014 to 2016. The calculated the area under the ROC curve (AUC) values for the model were very high (0.966, standard deviation = 0.005), indicating the model’s high predictive power. Precipitation seasonality was found to have the highest relative contribution to model development. Response curves produced by Maxent suggested the positive influence of mean temperature of the driest quarter, and negative influence of precipitation of the driest and coldest quarters on habitat suitability. Given that C. calauanica has been found to always occur with A. rigidus in Luzon Island due to high host-specificity, the SDM for the parasitoid may also be considered and used as a predictive model for its host. This was confirmed through field surveys conducted between late 2016 and early 2018, which found and confirmed the occurrence of A. rigidus in three areas predicted by the SDM to have moderate to high habitat suitability or probability of occurrence of C. calauanica: Zamboanga City in Mindanao; Isabela City in Basilan Island; and Tablas Island in Romblon. This validation in the field demonstrated the utility of the bioclimate-based SDM for C. calauanica in predicting habitat suitability or probability of occurrence of A. rigidus in the Philippines.

Comparison of two parameter recovery methods for the transformation of Pinus sylvestris yield tables into a diameter distribution model

2021 ◽  
Vol 78 (1) ◽  
Author(s):  
Francisco Mauro ◽  
Antonio García-Abril ◽  
Esperanza Ayuga-Téllez ◽  
Alberto Rojo-Alboreca ◽  
Ruben Valbuena ◽  
...  
Keyword(s):  
Pinus Sylvestris ◽  
Distribution Model ◽  
Diameter Distribution ◽  
Parameter Recovery ◽  
Two Parameter ◽  
Recovery Methods
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