Effects of climate and competition on crown width: a case of Korean pine plantations

Yan, Yunfei; Wang, Junjie; Mahardika, Surya Bagus; Jiang, Lichun

doi:10.1007/s10342-022-01515-y

Cited by 6 publications

(3 citation statements)

References 73 publications

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“…This study ultimately decided to choose an intermediate tree sampling design as the final sampling design because its RMSE was consistently smaller than that of the random tree sampling design (Table 6). This finding is consistent with that of Crecente-Campo et al [74] and Yan et al [75] in predicting tree height and crown width. A possible reason may be that intermediate trees provide more effective information by occupying the largest proportion in each plantation [75].…”

Section: Selection Of Calibration Strategiessupporting

confidence: 92%

“…This finding is consistent with that of Crecente-Campo et al [74] and Yan et al [75] in predicting tree height and crown width. A possible reason may be that intermediate trees provide more effective information by occupying the largest proportion in each plantation [75]. Although the random tree sampling design can generate more reliable and accurate predictions by averaging multiple simulation results [57,68], the repeated random sampling consumed a significant amount of time and effort in the forest survey.…”

Section: Selection Of Calibration Strategiessupporting

confidence: 92%

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Assessment of Potential Prediction and Calibration Methods of Crown Width for Dahurian Larch (Larix gmelinii Rupr.) in Northeastern China

Liu,

Wang,

Jiang

2023

Forests

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Crown width (CW) is an important indicator for assessing tree health, vitality, and stability, as well as being used to predict forestry models and evaluate forest dynamics. However, acquiring CW data is laborious and time-consuming, making it crucial to establish a convenient and accurate CW prediction model for forest management. In this study, we developed three models capable of conducting calibration: generalized models (GM), quantile regression models (QR), and mixed-effects models (MIXED). The aim was to effectively improve the prediction accuracy of CW using data from Dahurian larch (Larix gmelinii Rupr.) in Northeastern China. Different sampling designs were applied, including selecting the thickest, thinnest, intermediate, and random trees, with 1 to 10 sample trees for each design. The results showed that all models achieved accurate CW predictions. MIXED displayed the most superior fitting statistics than GM and QR. In model validation, with the increase in the number of sample trees, the model prediction accuracy gradually improved and the model differences gradually reduced. MIXED produced the smallest RMSE, MAE, and MAPE across all sampling designs. The intermediate tree sampling design with the best validation statistics for the given sample size was selected as the final sampling design. Under intermediate tree sampling design, MIXED required a minimum of five sample trees, while GM and QR required at least five and six sample trees for calibration, respectively. Generally, we suggested selecting MIXED as the final CW prediction model and using the intermediate tree sampling design of five trees per plot. This study could provide ideas and support for forest managers to accurately and efficiently predict CW.

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Section: Selection Of Calibration Strategiessupporting

confidence: 92%

Section: Selection Of Calibration Strategiessupporting

confidence: 92%

Assessment of Potential Prediction and Calibration Methods of Crown Width for Dahurian Larch (Larix gmelinii Rupr.) in Northeastern China

Liu,

Wang,

Jiang

2023

Forests

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“…In contrast, models that include appropriate environmental variables will allow stakeholders to accurately identify the conditions under which species become vulnerable and make more adaptive strategic decisions. Some research has developed climate-sensitive CW models (Wang et al, 2022;Wenyan et al, 2022;Yan et al, 2022), but models developed for pure stands may not be applicable to mixed forests of multiple species (Forrester et al, 2017). Condés et al (2020) developed CW models for each of the five pine species that included species mixing effects and tested the response of crown plasticity along a drought gradient.…”

Section: Introductionmentioning

confidence: 99%

Developing crown width model for mixed forests using soil, climate and stand factors

Tian,

He,

Jiang

et al. 2024

Journal of Ecology

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The tree crown is a useful measure of tree vigour and is highly relevant to a tree's environmental adaptability. Crown allometry depends on environmental and stand conditions. Several studies have focussed on the effects of climate change and competitive intensity on the crown, but the regulatory role of soil resources and diversity on crown allometry and carbon allocation has been neglected. Data from 20,994 trees in 232 mixed forests collected between 2011 and 2019 were located near four major mountain ranges in northeast China. The proposed crown width model includes the stand developmental stage, soil, climate, competition intensity, species mixture, species diversity, structural diversity and their interactions. We observed that the cross‐species allometric scaling exponent does not conform to the universal scaling law. Our results showed that crown width increased with increasing soil bulk density, quadratic mean diameter and coefficient of diameter variation but decreased with increasing de Martonne aridity index, basal area, Simpson index and species mixture. The interaction between quadratic mean diameter and soil bulk density had a significant negative effect on crown width. The influence of a particular factor within the interaction term on crown width was modulated by the gradients of other factors. Furthermore, soil bulk density contributed more to crown width modelling than the aridity index, and structural diversity had a greater effect on crown width than species diversity. Synthesis. Our results provide new insights into the environmental variability of crown allometry in mixed forests under global change, which is critical for improving regional and global estimates of forest biomass and carbon stocks.

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Nonlinear mixed-effect branch growth model development for planted Korean pine in Northeast China

Liu,

Feng,

Gao

et al. 2024

Trees

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Effects of climate and competition on crown width: a case of Korean pine plantations

Cited by 6 publications

References 73 publications

Assessment of Potential Prediction and Calibration Methods of Crown Width for Dahurian Larch (Larix gmelinii Rupr.) in Northeastern China

Assessment of Potential Prediction and Calibration Methods of Crown Width for Dahurian Larch (Larix gmelinii Rupr.) in Northeastern China

Developing crown width model for mixed forests using soil, climate and stand factors

Nonlinear mixed-effect branch growth model development for planted Korean pine in Northeast China

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