Autoregressive spatial analysis and individual tree modeling as strategies for the management of Eremanthus erythropappus

Scolforo, Henrique Ferraço; Scolforo, José Roberto Soares; Mello, José Márcio de; Filho, Antônio Carlos Ferraz; Rossoni, Diogo Francisco; Altoé, Thiza Falqueto; Oliveira, Antônio Donizette de; Lima, Renato Ribeiro de

doi:10.1007/s11676-015-0185-y

Cited by 9 publications

(12 citation statements)

References 17 publications

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“…The amount of fertilizer was defined in accordance with the soil fertility analysis in the experiment area. Scolforo et al (2015) studied nutrient effect on candeia tree growth and concluded that this is the optimal fertilization application. Weed and ant control were carried out periodically.…”

Section: Experimental Design and Data Collectionmentioning

confidence: 99%

Management strategies of Eremanthus erythropappus (DC.) MacLeish under different initial spacing

et al. 2016

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Eremanthus erythropappus, commonly known as candeia, is an income-generating tree native to Brazil. This is due to the high durability of its wood and its essential oil containing the active component alpha bisabolol. Despite this economic potential, until the early 2000's no studies existed to explore the sustainable management in areas in which the species naturally occurs or for establishing commercial plantations. This study proposes new management strategies based on an individual tree model, and evaluates the growth behavior of candeia trees planted in different spacing. The experiment was installed in March 2002, in Carrancas municipality, Minas Gerais state, Brazil. The experimental area was divided into 4 blocks with 4 different spacings as treatments. The individual model used to propose the best management system uses development of crown area as a function of DBH. The results showed that candeia trees were sensitive to initial spacing variation. With increased initial spacing, candeia trees reached competition later, as demonstrated by crown area development. Thus, candeia trees planted at a wider spacing maintain a desirable growth rate without need for thinning for a longer time, compared to trees planted at narrower spacing. The fitted individual tree model presented in this study showed consistent results and flexibility, providing alternatives for different management strategies. The best growth response was obtained for planting densities greater than 3.75 m² per tree, which corresponds to a spacing of 1.5 x 2.5 m.Index terms: Crown area; stand density; monomolecular model; individual tree model. RESUMOEremanthus erythropappus, conhecida vulgarmente por candeia, é uma árvore nativa do Brasil, geradora de renda devido à elevada durabilidade apresentada por sua madeira e, também, pelo seu óleo produzido conter, como ingrediente majoritário, o alfa bisabolol. Apesar deste potencial econômico, até o início do ano 2000, a espécie não contemplava estudos sobre seu sistema de cultivo, tanto para o manejo sustentável em áreas de ocorrência natural quanto para o estabelecimento de plantios comerciais. Este estudo propõe estudar novas estratégias de manejo com base em modelo de árvore individual, e avaliar o crescimento da candeia em diferentes espaçamentos. O experimento teve início em março de 2002, no município de Carrancas, Minas Gerais, Brasil. A área experimental foi dividida em quatro blocos, com quatro diferentes espaçamentos como tratamentos. O modelo avaliado para definir o melhor sistema de manejo foi baseado na relação entre o desenvolvimento da área de copa e do DAP das árvores. Os resultados mostraram que a candeia foi sensível a variação no espaçamento inicial. Aumentando o espaçamento inicial, a competição entre as árvores de candeia ocorre mais tarde, ou seja, à medida que o espaçamento aumenta demora-se mais para que o plantio perca o ritmo desejado de crescimento. O modelo testado foi consistente e a técnica baseada na árvore individual apresentou flexibilidade, fornecendo alte...

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Section: Experimental Design and Data Collectionmentioning

confidence: 99%

Management strategies of Eremanthus erythropappus (DC.) MacLeish under different initial spacing

et al. 2016

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“…When the MSE was confronted one-by-one between classical ANOVA and ANOVA-AR (AR1, AR2, AR3), the reduction occurs in 96%, 98% and 100% of the experiments. Scolforo et al (2016) noted the same reduction in a study of tree modeling as strategies for the management of Eremanthus erythropappus. The ANOVA-AR showed a reduction of MSE and it was capable to detect differences between treatments, which was unable to detect by classical ANOVA.…”

Section: Resultsmentioning

confidence: 85%

“…Thus, the efficiency of the RCBD is often poor in agronomy trials involving a large number of treatments. Scolforo et al (2016) showed a reduction of 90% of MSB, when compare classical ANOVA and ANOVA-AR.…”

Section: Resultsmentioning

confidence: 90%

“…Of these methods, modelling the spatial structure through a separable autoregressive (AR1  AR1) has become attractive and is commonly used in agricultural experimentation (BRAYSHER et al, 2001;CULLIS and GLEESON, 1991;GILMOUR et al, 1997;SCOLFORO et al, 2016;SINGH et al, 2003;YANG et al, 2004). Long (1996) describes an autoregressive analysis of variance that considers the proximity pattern (GUMPERTZ et al, 1997).…”

Section: Introductionmentioning

confidence: 99%

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Autoregressive Analysis of Variance for Experiments With Spatial Dependence Between Plots: A Simulation Study

Rossoni

Lima

2019

Rev. Bras. Biom.

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The analysis of variance remains one of the most appreciated techniques of field experiment, even despite almost a hundred years of its first proposal. However, in many cases, its application can be several impaired due the fact of lack – or even forgotten - of assumptions. In several experiments, the researchers make use of blocks to control the local heterogeneity, nevertheless, in some cases, only this it cannot be enough, especially in experiments where the data have some kind of spatial dependence. Therefore, to increase the accuracy of comparisons between treatments, an alternative is to consider the study of the spatial dependence of the variables in the analysis. With the knowledge of the relative positions of the plots (referenced data), the spatial variability can be used as a positive factor, collaborating with the experimental results. To develop this study we used data generated by simulation. The data was generated according a Randomized Complete Block Design (RCBD), with eighteen and five treatments per block; and several scenarios of spatial dependence in the error. We compared the non-spatial analysis (which considers the errors independent) with spatial analysis (analysis of variance considering the autoregressive model - ANOVA-AR). The use of spatial statistical tools in the analysis of data increased the precision of the analysis, through the reduction of the Mean Squared Error. We also noticed a reduction of Mean Squared Block and Mean Squared Treatment. The greater reduction was notice in ANOVA-AR3 for great part of the simulated scenarios, mainly in those with strong spatial dependence. The experiments with a small number of treatments per block did not present a reduction of Mean Squared Error, however, the reduction of Mean Squared Block and Mean Squared Treatment, ally to the fact that data are spatial dependent justify the use of ANOVA-AR.

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“…However, areas planted with Candeia have been increasing over the years, thus allowing exploitation of the species combined with its conservation in nature, thereby reducing the pressure on native remnants which are already over-exploited, and satisfying the market's appeal for products from planted forests, consequently maintaining the species' ability as a source of income (Scolforo et al, 2016a). The little existing knowledge about the silvicultural characteristics of the species is currently the great limiting factor for Candeia's commercial forestry production.…”

Section: Introductionmentioning

confidence: 99%

Growth of Eremanthus erythropappus (DC.) MacLeish in Different Planting Spacings

et al. 2019

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This study aimed to evaluate the growth of Eremanthus erythropappus (DC.) MacLeish submitted to different planting spacing and growth modelling based on the diameter and crown area projection, as well as to identify the best management strategy to be applied to control the competition, period and intensity of thinning. The evaluated planting spacings were: 1.5 × 1.5 m; 1.5 × 2.0 m; 1.5 × 2.5 m and 1.5 × 3.0 m. Diametric growth modelling in function of the age and crown area projection according to the mixed models methodology was efficient and the individual tree modelling allowed for defining a correct thinning prescription for tree plantations in relation to the percentage of removal needed at each spacing, thus permitting the trees to grow free from competition and produce trees with larger diameters.

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Autoregressive spatial analysis and individual tree modeling as strategies for the management of Eremanthus erythropappus

Cited by 9 publications

References 17 publications

Management strategies of Eremanthus erythropappus (DC.) MacLeish under different initial spacing

Management strategies of Eremanthus erythropappus (DC.) MacLeish under different initial spacing

Autoregressive Analysis of Variance for Experiments With Spatial Dependence Between Plots: A Simulation Study

Growth of Eremanthus erythropappus (DC.) MacLeish in Different Planting Spacings

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