Hegyi competition index decomposition to improve estimation accuracy of Larix olgensis crown radius

Sun, Zhao; Wang, Yifu; Pan, Lina; Sun, Yong

doi:10.1016/j.ecolind.2022.109322

Cited by 7 publications

(5 citation statements)

References 43 publications

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“…In addition, estimating the CR in different basic directions of each tree will be of great value due to the need for explicit crown asymmetry information in numerous research areas such as windthrow susceptibility estimation, and wood quality simulation. (Grote 2003;Kellomäki et al 1999;Krůček et al 2019;Skatter and Kucera 2000;Sun et al 2022). The results indicated that building separate Each of the selected covariables accurately reflects tree growth, resource allocation relationships, or competition with neighboring trees.…”

Section: The Growth Trend Of the Four Crmentioning

confidence: 92%

Two new methods applied to crown width additive models: a case study for three tree species in Northeastern China

Wang

Jiang

Xin

et al. 2023

Annals of Forest Science

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Key message The non-linear seemingly unrelated regression mixed-effects model (NSURMEM) and generalized additive model (GAM) were applied for the first time in crown width (CW) additive models of larch (Larix gmelinii Rupr.), birch (Betula platyphylla Suk.), and poplar (Populus davidiana Dode). The crown radii in four directions (CR) exhibited different growth trends and responded differently to tree size and competition variables. In the absence of calibration, GAM was more accurate than NSURMEM for CR and CW predictions. Context Crown radii in four directions (CR) and crown width (CW) are fundamental indicators used to describe tree crowns. The complexity of the CR growth in four directions of different tree species in natural forests is often ignored. There is logical additivity among CR and CW that is also often overlooked. Furthermore, the existing methods applied to CW additive models have some drawbacks. Aims We aim to: (i) evaluate the utility of two new methods in developing CW additive models for larch (Larix gmelinii Rupr.), birch (Betula platyphylla Suk.), and poplar (Populus davidiana Dode) in natural secondary forests of Northeastern China; and (ii) explore the growth patterns of CR in four directions to gain important ecological insights. Methods The non-linear seemingly unrelated regression mixed-effects model (NSURMEM) and generalized additive model (GAM) were used to develop CW additive models and to explore crown growth patterns. The predictive ability of the additive models was evaluated using leave-one-plot-out cross-validation (LOOCV). Results At a fair level without calibration, GAM provided slightly better results than NSURMEM. The response of the four CR to tree size and competition variables is different and may be non-uniform due to complex stand conditions and tree growth strategies. Conclusion The newly provided methods applied to additive models are available for external datasets. GAM is recommended in the absence of calibration. This study has important implications for the understanding of natural forest dynamics and decision-making for critical stand management.

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Section: The Growth Trend Of the Four Crmentioning

confidence: 92%

Two new methods applied to crown width additive models: a case study for three tree species in Northeastern China

Wang

Jiang

Xin

et al. 2023

Annals of Forest Science

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“…DBH data were used to calculate competition indices to characterize the competitive ability of individuals to their neighbors. The Hegyi index, proposed by Hegyi in 1974 [ 46 ], is the most classical spatial competition index used in forest research to quantify the competitive pressure of trees in forests [ 47 ] Hegyi’s competition index depends on the size and distance of neighboring trees, and was calculated as follows:…”

Section: Methodsmentioning

confidence: 99%

Genomic dissection of additive and non-additive genetic effects and genomic prediction in an open-pollinated family test of Japanese larch

Dong,

Xie,

Zhang

et al. 2024

BMC Genomics

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Genomic dissection of genetic effects on desirable traits and the subsequent use of genomic selection hold great promise for accelerating the rate of genetic improvement of forest tree species. In this study, a total of 661 offspring trees from 66 open-pollinated families of Japanese larch (Larix kaempferi (Lam.) Carrière) were sampled at a test site. The contributions of additive and non-additive effects (dominance, imprinting and epistasis) were evaluated for nine valuable traits related to growth, wood physical and chemical properties, and competitive ability using three pedigree-based and four Genomics-based Best Linear Unbiased Predictions (GBLUP) models and used to determine the genetic model. The predictive ability (PA) of two genomic prediction methods, GBLUP and Reproducing Kernel Hilbert Spaces (RKHS), was compared. The traits could be classified into two types based on different quantitative genetic architectures: for type I, including wood chemical properties and Pilodyn penetration, additive effect is the main source of variation (38.20-67.46%); for type II, including growth, competitive ability and acoustic velocity, epistasis plays a significant role (50.76-91.26%). Dominance and imprinting showed low to moderate contributions (< 36.26%). GBLUP was more suitable for traits of type I (PAs = 0.37–0.39 vs. 0.14–0.25), and RKHS was more suitable for traits of type II (PAs = 0.23–0.37 vs. 0.07–0.23). Non-additive effects make no meaningful contribution to the enhancement of PA of GBLUP method for all traits. These findings enhance our current understanding of the architecture of quantitative traits and lay the foundation for the development of genomic selection strategies in Japanese larch.

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“…The lack of correlation between the Hegyi index and the BAI (r = −0.019, p > 0.05, Figure 6B) could be due to the relative position of the trees in the plot and the directionality of competitive pressure. Trees near the plot's edge may not account for competition outside the plot [49]. Furthermore, competition from different directions can lead to varying competitive pressures, which is not taken into account by the Hegyi index.…”

Section: Radial Growth Responses To Competitionmentioning

confidence: 99%

Radial Growth of Dahurian Larch (Larix gmelinii) Responses to Climate and Competition

Li,

Zhang,

Wei

et al. 2024

Forests

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The phenomenon of divergent responses in tree ring radial growth to climate change has been observed in the mid- and high-latitude regions of the Northern Hemisphere amidst global warming. However, the stability of the responses of the primary conifer species to climate factors in the mountainous regions of northeastern China remains unclear. Additionally, it is uncertain whether the radial growth in this area consistently responds to different competition indices. In our study, we developed tree ring width chronologies for Dahurian larch (Larix gmelinii) and analysed the radial growth responses to the regional climate from 1980 to 2012. This analysis was conducted by correlating meteorological data from different physiological stages of trees. We also evaluated the reliability of competition indices in predicting tree growth by constructing multiple linear regression models. Furthermore, we explored the relationship between the Basal Area Increment (BAI) of each tree and the competition indices in the sample plot over the previous five years. Our results showed that the temperature during the Non-Structural Carbohydrate (NSC) accumulation period and the NSC consumption period was significantly negatively correlated with the Ring Width Index (RWI) of Dahurian larch. Conversely, the RWI was significantly positively correlated with precipitation during these periods. The Standardised Precipitation Evapotranspiration Index (SPEI) at any period had a significantly positive correlation with the RWI. These findings suggest that future radial growth is likely to continue to be constrained by rising temperatures and water scarcity. Our findings also demonstrated that radial growth was less negatively impacted by competition from nearby trees and more influenced by the initial size of the tree. Compared to models that included other indices, models that included the BAL index as a single explanatory variable demonstrated superior statistical effectiveness. Our research suggests that before evaluating the competitive effects of the neighbourhood on radial growth, it is necessary to consider the stand diversity of tree species and the parameters related to spatial structure when selecting an appropriate competition index.

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Hegyi competition index decomposition to improve estimation accuracy of Larix olgensis crown radius

Cited by 7 publications

References 43 publications

Two new methods applied to crown width additive models: a case study for three tree species in Northeastern China

Two new methods applied to crown width additive models: a case study for three tree species in Northeastern China

Genomic dissection of additive and non-additive genetic effects and genomic prediction in an open-pollinated family test of Japanese larch

Radial Growth of Dahurian Larch (Larix gmelinii) Responses to Climate and Competition

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