scholarly journals Development and Evaluation of Black Spruce (Picea mariana (Miller) B.S.P.) Diameter Increment Models across Silvicultural Treatments in Northern Minnesota, USA

Forests ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 747 ◽  
Author(s):  
Brian Anderson ◽  
Matthew Russell ◽  
Marcella Windmuller-Campione ◽  
Brian Palik ◽  
Douglas Kastendick
Keyword(s):  
Fixed Effects ◽  
Growth Models ◽  
Black Spruce ◽  
Mixed Effects ◽  
Diameter Growth ◽  
Fixed Effects Model ◽  
Important Species ◽  
Silvicultural Treatments ◽  
Wide Range ◽  
Lake States

The black spruce cover type occupies roughly 10% of Minnesota’s 7 million hectares of forestland, and is an important species, both ecologically and economically. A clearcut regeneration harvest is the main silvicultural system in black spruce in this region. The effects of managing black spruce with alternative silvicultural methods in the Lake States remains largely understudied. Here, we examine a silviculture study in lowland black spruce to assess the performance of two diameter growth models fit to this data compared to a widely-used model. Six silvicultural treatments (clearcut strips, clearcut patches, thinning, group selection, single-tree selection, and shelterwood) and a control were treated and measured around 1950, with a follow-up measurement occurring 10 years later. Fixed- and mixed-effects growth-models were adapted from the previous work, and fit to 10,231 observations and compared to a recently released diameter growth model. The mixed-effects model using treatment, compartment, and plot as nested random effects outperformed the fixed-effects model, and outperformed a model proposed for use in the Lake States variant of the Forest Vegetation Simulator that was fit to this data. This modeling approach of localized growth models across a wide-range of diameters (9.1–32.1 cm) more accurately predicted the diameter growth in lowland black spruce than the conventional approach of using separate models for large (>12.7 cm) and small (≤12.7 cm) diameter trees.

scholarly journals Proposals for Nothofagus antarctica diameter growth estimation: simple vs. global models

2014 ◽  
Vol 60 (No. 8) ◽  
pp. 307-317 ◽  
Author(s):  
H. Ivancich ◽  
G.J. Martínez Pastur ◽  
M.V. Lencinas ◽  
J.M. Cellini ◽  
P.L. Peri
Keyword(s):  
Tree Growth ◽  
Growth Models ◽  
Site Quality ◽  
Diameter Growth ◽  
Wide Range ◽  
Nothofagus Antarctica ◽  
Simple Growth ◽  
Simple Equations ◽  
Diameter Growth Models ◽  
Stand Conditions

Tree growth is one of the main variables needed for forest management planning. The use of simple models containing traditional equations to describe tree growth is common. However, equations that incorporate different factors (e.g. site quality of the stands, crown classes of the trees, silvicultural treatments) may improve their accuracy in a wide range of stand conditions. The aim of this work was to compare the accuracy of tree diameter growth models using (i) a family of simple equations adjusted by stand site quality and crown class of trees, and (ii) <br /> a unique global equation including stand and individual tree variables. Samplings were conducted in 136 natural even-aged Nothofagus antarctica (Forster f.) Oersted stands in Southern Patagonia (Argentina) covering age (20&ndash;200 years), <br /> crown class and site quality gradients. The following diameter growth models were fitted: 16 simple equations using two independent variables (age and one equation for each stand site quality or crown class) based on Richards model, plus a unique global equation using three independent variables (age, stand site quality and crown class). Simple equations showed higher variability in their accuracy, explained between 54% and 92% of the data variation. The global model presented similar accuracy like the better equations of the simple growth models. The unification of the simple growth models into a unique global equation did not greatly improve the accuracy of estimations, but positively influenced the biological response of the model. Another advantage of the global equation is the simple use under a wide range of natural stand conditions. The proposed global model allows to explain the tree growth of N. antarctica trees along the natural studied gradients. &nbsp; &nbsp;

scholarly journals Model of mixed effects of height dependence on tree diameters in pine stands

2021 ◽  
Author(s):  
Н.Н. Дубенок ◽  
В.В. Кузьмичев ◽  
А.В. Лебедев
Keyword(s):  
Fixed Effects ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Fixed Effects Model ◽  
Permanent Sample Plots ◽  
Diameter At Breast Height ◽  
Breast Height ◽  
Russian State ◽  
Pine Stands ◽  
The Relationship

Основными исходными данными для определения запаса служат результаты обмеров диаметров и высот деревьев. Но обмеры диаметров деревьев на высоте груди выполнить намного проще, чем обмеры высот, поэтому ограничиваются замерами высот 15–25 деревьев. Цель исследования – по материалам измерения модельных деревьев в сосновых древостоях выбрать наиболее адекватную простую модель, которая передает зависимость между высотой деревьев и диаметром на высоте груди. Объектом исследования послужили сосновые древостои искусственного происхождения на постоянных пробных площадях в Лесной опытной даче Российского государственного агарного университета – МСХА имени К.А. Тимирязева. В работе используются данные обмеров деревьев на 17 постоянных пробных площадях с 1934 по 2005 гг. Возраст древостоев на момент проведения измерений от 50 до 125 лет. По итогам проведения 77 перечетов массив данных составил 1157 наблюдений. И модель фиксированных эффектов, и модель смешанных эффектов адекватно описали зависимость между высотами и диаметрами деревьев в культурах сосны. Но, как и ожидалось, первая модель имеет худшие значения метрик качества по сравнению со второй. Модель со смешанными эффектами более точно предсказывает значения высот по сравнению с моделью фиксированных эффектов. Недостающие значения высот большого количества деревьев на участке можно вычислить более точно с помощью модели смешанных эффектов, а не применения модели фиксированных эффектов или использования только фиксированной части (средний отклик) модели смешанных эффектов. Применение разработанной модели должно ограничиваться только в тех условиях, к которым относятся экспериментальные материалы The main data for the stock of research results is the diameter of measurements and heights of trees. But measurements of the diameter at breast height are much easier to perform than measurements of heights, therefore, they are limited to measuring the heights of 15–25 trees. The aim of the study is to select the most adequate simple model based on the measurements of model trees in pine antiquities, which conveys the relationship between the height of trees and the diameter at breast height. The object of the study was pine stands of artificial origin on permanent test plots in the Forest Experimental Station Russian State Agararian University – Moscow Timiriazev Agricultural Academy. The work uses data from tree measurements on 17 permanent sample plots from 1934 to 2005. The age of the stands at the time of measurements was from 50 to 125 years. As a result of 77 enumerations, the data array amounted to 1157 observations. Both the fixed effects model and the mixed effects model adequately describe the relationship between heights and diameters of trees in pine stumps. But, as expected, the first model has worse quality metrics than the second. The mixed effects model more accurately predicts heights from the fixed effects model. The missing heights of a large number of trees on a site can be calculated accurately using mixed effects models, rather than using fixed effects models or using only a fixed portion (mean response) of the mixed effects model. The application of the developed model should be limited only in those conditions to which the experimental materials are applied.

scholarly journals Association of Metformin Use with Asthma Exacerbation in Patients with Concurrent Asthma and Diabetes: A Systematic Review and Meta-Analysis of Observational Studies

2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Li Wen ◽  
Wang Zhong ◽  
Yihui Chai ◽  
Qin Zhong ◽  
Jie Gao ◽  
...  
Keyword(s):  
Emergency Room ◽  
Asthma Exacerbation ◽  
Observational Studies ◽  
Fixed Effects ◽  
Meta Analysis ◽  
Emergency Department Visits ◽  
Emergency Room Visits ◽  
Fixed Effects Model ◽  
Adjusted Risk ◽  
Wide Range

Background. Asthma and diabetes are both diseases that affect a wide range of people worldwide. As a common treatment for diabetes, metformin has also been reported to be effective in improving asthma outcomes. We conducted a combined analysis to examine the efficacy of metformin in reducing asthma exacerbation in patients with concurrent asthma and diabetes. Methods. We searched the PubMed, Embase, and CENTRAL databases for articles published prior to April 2020 to find observational studies of individuals with concurrent asthma and diabetes that compared the risk of asthma exacerbation between metformin users and nonusers. Two researchers separately screened the studies, extracted data, and evaluated the risk of bias. The primary outcome was the adjusted risk of asthma exacerbation. The secondary outcomes were the adjusted risk of asthma-related hospitalization and emergency room visits. Review Manager was used for data analysis and plotting. I2 and χ2 tests were used to estimate heterogeneity. A random effects or fixed effects model was used depending on the heterogeneity. Odds ratios were calculated for dichotomous variables. Results. We included two studies with a total of 25252 patients. The pooled effect size showed that metformin was inversely associated with a risk of asthma exacerbation (OR = 0.65, 95% CI 0.28–1.48; χ2 = 5.42, P=0.02; I2 = 82%), asthma-related emergency department visits (OR = 0.81, 95% CI 0.74–0.89; χ2 = 0.36, P=0.55; I2 = 0%), and hospitalizations (OR = 0.43, 95% CI 0.14–1.29; χ2 = 4.01, P=0.05; I2 = 75%). Conclusion. This meta-analysis suggested that metformin decreased the risk of asthma-related emergency room visits for patients with concurrent asthma and diabetes. Metformin reduced the risk of asthma-related hospitalization and exacerbation but was not statistically significant. More randomized trials involving larger samples should be considered, and the mechanisms of these effects need to be fully elucidated.

A note on Griffing's models for the diallel cross

1975 ◽  
Vol 85 (3) ◽  
pp. 575-576 ◽  
Author(s):  
B. K. Thompson
Keyword(s):  
Fixed Effects ◽  
Diallel Cross ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Fixed Effects Model

SUMMARYSome misconceptions concerning the application of Griffing's fixed effects model I and mixed effects model B are discussed.

scholarly journals Validation Metrics for Fixed Effects and Mixed-Effects Calibration

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Nathan W. Porter ◽  
Kathryn A. Maupin ◽  
Laura P. Swiler ◽  
Vincent A. Mousseau
Keyword(s):  
Experimental Data ◽  
Computational Model ◽  
Fixed Effects ◽  
Calibration Method ◽  
Mixed Effects ◽  
Calibration Model ◽  
Fixed Effects Model ◽  
Validation Metrics ◽  
Calibration Methods ◽  
History Of Use

Abstract The modern scientific process often involves the development of a predictive computational model. To improve its accuracy, a computational model can be calibrated to a set of experimental data. A variety of validation metrics can be used to quantify this process. Some of these metrics have direct physical interpretations and a history of use, while others, especially those for probabilistic data, are more difficult to interpret. In this work, a variety of validation metrics are used to quantify the accuracy of different calibration methods. Frequentist and Bayesian perspectives are used with both fixed effects and mixed-effects statistical models. Through a quantitative comparison of the resulting distributions, the most accurate calibration method can be selected. Two examples are included which compare the results of various validation metrics for different calibration methods. It is quantitatively shown that, in the presence of significant laboratory biases, a fixed effects calibration is significantly less accurate than a mixed-effects calibration. This is because the mixed-effects statistical model better characterizes the underlying parameter distributions than the fixed effects model. The results suggest that validation metrics can be used to select the most accurate calibration model for a particular empirical model with corresponding experimental data.

An imputation approach for fitting two-part mixed effects models for longitudinal semi-continuous data

2020 ◽  
Vol 29 (11) ◽  
pp. 3351-3361
Author(s):  
Hyoyoung Choo-Wosoba ◽  
Debamita Kundu ◽  
Paul S Albert
Keyword(s):  
Random Effects ◽  
Fixed Effects ◽  
Clinical Trial Data ◽  
Mixed Effects ◽  
Mixed Effects Models ◽  
Unbiased Estimation ◽  
Continuous Components ◽  
Wide Range ◽  
Parameter Values ◽  
Imputation Approach

Two-part mixed effects models are often used for analyzing longitudinal data with many zeros. Typically, these models are formulated with binary and continuous components separately with random effects that are correlated between the two components. Researchers have developed maximum-likelihood and Bayesian approaches for fitting these models that often require using particular software packages or very specialized software. We propose an imputation approach that will allow practitioners to separately use standard linear and generalized linear mixed models to estimate the fixed effects for two-part mixed effects models with complex random effects structures. An approximation to the conditional distribution of positive measurements given an individual’s pattern of non-zero measurements is proposed that can be easily estimated and then imputed from. We show that for a wide range of parameter values, the imputation approach results in nearly unbiased estimation and can be implemented with standard software. We illustrate the proposed imputation approach for the analysis of longitudinal clinical trial data with many zeros.

scholarly journals Modelling Future Growth of Mountain Forests Under Changing Environments

2021 ◽  
pp. 223-262
Author(s):  
Michal Bosela ◽  
Katarína Merganičová ◽  
Chiara Torresan ◽  
Paolo Cherubini ◽  
Marek Fabrika ◽  
...  
Keyword(s):  
Growth Models ◽  
Model Averaging ◽  
Forest Growth ◽  
Mountain Forests ◽  
Silvicultural Treatments ◽  
Wide Range ◽  
Species Mixture ◽  
Fast Development ◽  
European Mountain ◽  
Future Growth

AbstractModels to predict the effects of different silvicultural treatments on future forest development are the best available tools to demonstrate and test possible climate-smart pathways of mountain forestry. This chapter reviews the state of the art in modelling approaches to predict the future growth of European mountain forests under changing environmental and management conditions. Growth models, both mechanistic and empirical, which are currently available to predict forest growth are reviewed. The chapter also discusses the potential of integrating the effects of genetic origin, species mixture and new silvicultural prescriptions on biomass production into the growth models. The potential of growth simulations to quantify indicators of climate-smart forestry (CSF) is evaluated as well. We conclude that available forest growth models largely differ from each other in many ways, and so they provide a large range of future growth estimates. However, the fast development of computing capacity allows and will allow a wide range of growth simulations and multi-model averaging to produce robust estimates. Still, great attention is required to evaluate the performance of the models. Remote sensing measurements will allow the use of growth models across ecological gradients.

Repeated Measurement Designs

1983 ◽  
Vol 32 (3-4) ◽  
pp. 153-168 ◽  
Author(s):  
A, C. Mukhopadhyay ◽  
Rita Saha
Keyword(s):  
Fixed Effects ◽  
Mixed Effects ◽  
Repeated Measurement ◽  
Mixed Effects Model ◽  
Fixed Effects Model

In the present paper Repeated Measurement Designs (RMD's) have been studied under mixed effects model, assuming unit effects to be random and most of the optimality results of RMD's proved under fixed effects model by Hedayat et. al (1978), Magda (1980) and Cheng et. al (1980) have been reestablished in the context of mixed effects model.

scholarly journals Comparison of Fixed- and Mixed-effects Approaches to Taper Modeling for Scots Pine in West Poland

Forests ◽  
2019 ◽  
Vol 10 (11) ◽  
pp. 975 ◽  
Author(s):  
Karol Bronisz ◽  
Michał Zasada
Keyword(s):  
Random Effects ◽  
Scots Pine ◽  
Fixed Effects ◽  
Mixed Effects ◽  
Mixed Effects Model ◽  
Fixed Effects Model ◽  
Validation Data ◽  
Data Set ◽  
Taper Model ◽  
Model Approach

Diameter measurements along the stem, which are the basis for taper models, usually have a hierarchical structure. Mixed-effects models, where fixed and random effects are distinguished, are a possible solution for this type of data. However, in order to fully absorb the potential of this method, random effects prediction, which requires additional measurements (diameter along stem), is recommended. This article presents a comparison of various fitting methods (mixed- and fixed-effects model approaches) of the variable-exponent taper model created by Kozak for determining the outside bark diameter along the stem and predicting the tree volume of Scots pine trees in west Poland. During the analysis, it was assumed that no additional measured data were available for practical use; therefore, for the mixed-effects model approach, fixed effects prediction without random effects was applied. Both fitting strategies were compared based on modeling and an independent validation data set. The comparison of mixed- and fixed-effects fitting strategies for the diameter along the stem indicated that the taper model fitted using the mixed-effects model approach better fit the data. Moreover, the error rate for the total tree volume prediction for the independent data set was lower for the mixed-effects model solution than for the fixed-effects one.

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