On the evaluation of competition indices – The problem of overlapping samples

Pedersen, Rune Østergaard; Næsset, Erik; Gobakken, Terje

doi:10.1016/j.foreco.2013.07.040

Cited by 16 publications

(10 citation statements)

References 36 publications

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“…As suggested by Pedersen et al (2013) we applied the Spearman rank correlation (Spearman's rho) to characterize the relationship between the 5-year tree diameter increment (i d5 ) and the competition indices. The Spearman correlation is able to consider potential nonlinear trends frequently seen in growth and competition studies, besides it is valid for the data size larger than 10 (Siegel, 1956) which was applicable to our data.…”

Section: Statistical and Comparative Analyses Of Competition Indicesmentioning

confidence: 99%

Analysis of Individual Tree Competition on Diameter Growth of Silver Birch in Estonia

2015

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Aim of study: The present study evaluates a set of competition indices including spatially explicit indices combined with different competitor selection approaches and non-spatially explicit competition indices. The aim was to quantify and describe the neighbouring effects on the tree diameter growth of silver birch trees.Area of study: Region throughout Estonia. Material and methods:Data from the Estonian Network of Forest Research Plots was used. After quantifying the selected indices, the best non-spatial indices and spatial indices (combined with neighbour selection methods) were separately devised into a growth model as a predictor variable to assess the ability of the diameter growth model before and after adding competition measures. To test the species-specific effect on the competition level, the superior indices were recalculated using Ellenberg's light indicators and incorporated into the diameter growth model.Main results: Statistical analyses showed that the diameter growth is a function of neighbourhood interactions and spatial indices were better growth predictors than non-spatial indices. In addition, the best selections of competitive neighbours were acquired based on the influence zone and the competition elimination angle concepts, and using Ellenberg's light values had no significant improvement in quantifying the competition effects.Research highlights: Although the best ranking spatial competition measures were superior to the best non-spatial indices, the differences were negligible.

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Section: Statistical and Comparative Analyses Of Competition Indicesmentioning

confidence: 99%

Analysis of Individual Tree Competition on Diameter Growth of Silver Birch in Estonia

2015

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“…As equações ajustadas por Wachtel (1990) e Nutto, Spathelf e Rogers (2005), ambas em árvores do interior de florestas, estimaram diâmetro de copa menores que as demais, ao longo das classes de DAP. Esta diferença pode estar relacionada com a tipologia florestal do local, a densidade da floresta, o grau de competição entre árvores (DANIELS; BURKHART; CLASON, 1986;GETZIN et al, 2008;PEDERSEN et al, 2013), o instrumento usado na medição da área de projeção horizontal da copa (BECHTOLD;MIELKE;ZARNOCH, 2002;FIALA;GRAY, 2006), entre outros fatores.…”

Section: Resultsunclassified

Modelagem Do Espaço De Crescimento Para Araucária

Costa¹,

Finger²

2018

Ciênc. Florest.

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Este estudo foi desenvolvido com objetivo de modelar o espaço de crescimento para árvores de Araucaria angustifolia (Bertol.) Kuntze. Um total de 869 araucárias foram amostradas em três municípios no sul do Brasil, sendo 175 árvores com crescimento livre de competição nos municípios de Canoinhas-SC e Lages-SC, e 694 sob influência da competição em floresta natural nos municípios de São Francisco de Paula-RS e Lages-SC. Em cada árvore, foi medido o diâmetro a altura do peito, altura total e raios de copa seguindo as direções dos pontos cardeais. O diâmetro de copa foi determinado dobrando o valor do raio médio da copa. Três modelos foram ajustados e avaliados quanto ao ajuste, à precisão e à análise gráfica dos resíduos, segundo o município e a condição de crescimento. Na comparação das equações, a análise de covariância não indicou diferença significativa entre nível e inclinação das equações de diâmetro de copa de árvores livres e sob competição nos diferentes locais em que os dados foram amostrados. Uma única equação foi definida para estimar o diâmetro de copa em função do diâmetro a altura do peito para a espécie.

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“…This can be inferred, when the planting distance is small, the growth space is limited, resulting in competition between the forest resources situation is more serious; In contrast, when a large planting distance, the index than other stand competition from the plant have the trend is clearly reduced, showing its growing space broader trees, trees contribute to growth, the degree of competition for resources is low. Pedersen et al, (2013) estimated the stand value and calculated 7 stand competition by airborne LiDAR. And separated the competition index into space, non-space, and echo 3 types.…”

Section: Establish the Stand Competition Indexmentioning

confidence: 99%

Study on the Explainable Ability by Using Airborne Lidar in Stand Value and Stand Competition

Huang¹,

Yeh²,

Chen³

et al. 2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Forest canopy structure is composed by the various species. Sun light is a main factor to affect the crown structures after tree competition. However, thinning operation is an appropriate way to control canopy density, which can adjust the competition conditions in the different crown structures. Recently, Airborne Light Detection and Ranging (LiDAR), has been established as a standard technology for high precision three dimensional forest data acquisition; it could get stand characteristics with three-dimensional information that had develop potential for the structure characteristics of forest canopy. The 65 years old, different planting density of Cryptomeria japonica experiment area was selected for this study in Nanytou, Taiwan. Use the LiDAR image to estimate LiDAR characteristic values by constructed CHM, voxel-based LiDAR, mu0ltiple echoes, and assess the accuracy of stand characteristics with intensity values and field data. The competition index was calculated with field data, and estimate competition index of LiDAR via multiple linear regression. The results showed that the highest accuracy with stand characteristics was stand high which estimate by LiDAR, its average accuracy of 91.03%. LiDAR raster grid size was 20 m × 20 m for the correlation was the best, however, the higher canopy density will reduce the accuracy of the LiDAR characteristic values to estimate the stand characteristics. The significantly affect canopy thickness and the degree of competition in different planting distances.

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On the evaluation of competition indices – The problem of overlapping samples

Cited by 16 publications

References 36 publications

Analysis of Individual Tree Competition on Diameter Growth of Silver Birch in Estonia

Analysis of Individual Tree Competition on Diameter Growth of Silver Birch in Estonia

Modelagem Do Espaço De Crescimento Para Araucária

Study on the Explainable Ability by Using Airborne Lidar in Stand Value and Stand Competition

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