Developing national and regional individual tree biomass models and analyzing impact of climatic factors on biomass estimation for poplar plantations in China

Zeng, Weisheng; Yang, Xueyun

doi:10.1007/s00468-020-02020-8

Cited by 9 publications

(4 citation statements)

References 30 publications

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“…In past studies, the climate, topography, human disturbance, and forest management activities have influenced changes in forest structure and accumulation to some extent. Zeng [35] developed a climate-sensitive individual tree biomass model by combining the mean annual temperature (T) and annual precipitation (P) to analyze the influence of climatic factors on biomass estimation, and the results showed that mean annual precipitation influences the predicted biomass. Propastin [36] used geographically weighted regression to conclude that a strong correlation exists between the vegetation and rainfall in central Sulawesi by modeling the relationship between the vegetation and climate.…”

Section: Discussionmentioning

confidence: 99%

Growing Stock Volume Estimation for Daiyun Mountain Reserve Based on Multiple Linear Regression and Machine Learning

Wei¹,

Fan²

2022

Sustainability

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Remote sensing provides an easy, inexpensive, and rapid method for detecting forest stocks. However, the saturation of data from different satellite sensors leads to low accuracy in estimations of the growing stock volume in natural forests with high densities. Thus, this study added actual data to improve the accuracy. The Daiyun Mountain Reserve was the study area. Landsat 8 operational land imager data were combined with remote sensing data and actual measurements. Multiple linear regression (MLR) and machine learning methods were used to construct a model for estimating the growing stock volume. The decision tree model showed the best fit. By adding the measured data to the model, the saturation could effectively be overcome to a certain extent, and the fitting effect of all the models can be improved. Among the estimation models using only remote sensing data, the normalized difference vegetation index showed the strongest correlation with the model, followed by the annual rainfall and slope. The decision tree model was inverted to produce a map of the accumulation distribution. From the map, the storage volume in the west was lower than that in the east and was primarily confined to the middle-altitude area, consistent with field survey results.

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Section: Discussionmentioning

confidence: 99%

Growing Stock Volume Estimation for Daiyun Mountain Reserve Based on Multiple Linear Regression and Machine Learning

Wei¹,

Fan²

2022

Sustainability

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“…In past few decades, many different forms of allometric equations ( Ter-Mikaelian and Korzukhin, 1997 ; Muukkonen, 2007 ; Henry et al., 2011 ; Yuen et al., 2016 ) have been developed, and tree-level biomass models are the most accurate ( Zeng et al., 2021 ). To date, an allometric relationship of the power exponent is the primary model used to estimate the biomass of a single tree, and these models are divided into process and empirical models ( Fehrmann and Kleinn, 2006 ; Zianis et al., 2016 ).…”

Section: Introductionmentioning

confidence: 99%

“…Trees are important carbon sinks and also Larch ( Larix principis-rupprechtii Mayr) is one of the main afforestation tree species that has high social, economic and ecological value in northern China; it grows well and widely in warm temperate subalpine areas owing to its strong ability to adapt to the environment and the utility and performance of its wood ( Qiu et al., 2019 ; Dong et al., 2019 ; Li et al., 2020 ). To achieve the goal of neutralizing global carbon and reducing its peak, accurate estimations of the biomass of Larix principis-rupprechtii are highly significant for the research on stand structure and function ( Pan et al., 2013 ), evaluation of its production potential ( Duan et al., 2018 ), and climate impact and adaptation ( Rizvi et al., 2011 ; Zeng et al., 2021 ). However, a process model with the fixed position diameter (DBH) could mislead the universal scaling laws and lead to some deviation for the biomass model ( Fehrmann and Kleinn (2006) ; Cienciala et al., 2013 ; Zianis et al., 2016 ).…”

Section: Introductionmentioning

confidence: 99%

Biomass allometric models for Larix rupprechtii based on Kosak’s taper curve equations and nonlinear seemingly unrelated regression

Wang

Zhang

et al. 2023

Front. Plant Sci.

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The diameter at breast height (DBH) is the most important independent variable in biomass allometry models based on metabolic scaling theory (MST) or geometric theory. However, the fixed position DBH can be misleading in its use of universal scaling laws and lead to some deviation for the biomass model. Therefore, it is still an urgent scientific problem to build a high-precision biomass model system. A dataset of 114 trees was destructively sampled to obtain dry biomass components, including stems, branches, and foliage, and taper measurements to explore the applicability of biomass components to allometric scaling laws and develop a new system of additive models with the diameter in relative height (DRH) for each component of a Larch (Larix principis-rupprechtii Mayr) plantation in northern China. The variable exponential taper equations were modelled using nonlinear regression. In addition, applying nonlinear regression and nonlinear seemingly unrelated regression (NSUR) enabled the development of biomass allometric models and the system of additive models with DRH for each component. The results showed that the Kozak’s (II) 2004 variable exponential taper equation could accurately describe the stem shape and diameter in any height of stem. When the diameters in relative height were D0.2, D0.5, and D0.5 for branches, stems, and foliage, respectively, the allometric exponent of the stems and branches was the closest to the scaling relations predicted by the MST, and the allometric exponent of foliage was the most closely related to the scaling relations predicted by geometry theory. Compared with the nonlinear regression, the parameters of biomass components estimated by NSUR were lower, and it was close to the theoretical value and the most precise at forecasting. In the study of biomass process modelling, utilizing the DRH by a variable exponential taper equation can confirm the general biological significance more than the DBH of a fixed position.

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“…Populus spp. are able to survive on a variety of barren soils due to their high adaptability, and most can reproduce asexually, yield large amounts of seedlings, renew quickly, and have strong stress resistance [38,39]. The ecological function of poplar planting is to reduce erosion and runoff and to protect soil water content, so poplar has been widely planted as the main afforestation species in the Three-North shelterbelt [40,41].…”

Section: Introductionmentioning

confidence: 99%

Relative Availability of Nitrogen and Calcium Regulates the Growth of Poplar Seedlings Due to Transcriptome Changes

Weng,

Li,

Zhou

et al. 2023

Forests

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The concentrations of exogenous nitrogen and calcium can significantly regulate plant growth and photosynthesis and mutually affect their absorption and utilization. However, whether there is an optimal nitrogen–calcium ratio (N:Ca ratio) in poplar seedling growth and physiological adaptation and what the mechanism of changes in the transcriptome is remain unclear. In this study, three different N:Ca ratios were used to grow poplar seedlings, and physiological and transcriptomic methods were used to study the molecular mechanisms of poplar growth under nitrogen–calcium synergy and to determine the optimal N:Ca ratio for poplar seedling growth. The results of this study showed that maximum poplar seedling growth occurred in the treatment with an N:Ca ratio of 2, which resulted in significantly greater induction of growth than the two other treatments (p < 0.05). Under the lowest N:Ca ratio, poplar seedlings can ensure normal development by regulating photosynthesis, while under the highest N:Ca ratio, regulating nitrogen metabolism can achieve the same result. These results contribute to a better understanding of the molecular mechanisms by which poplar seedlings respond to different ratios of N:Ca. This study provides a valuable basis for exploring the synergistic effects of nitrogen and calcium on the growth of poplar shelterbelts.

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Developing national and regional individual tree biomass models and analyzing impact of climatic factors on biomass estimation for poplar plantations in China

Cited by 9 publications

References 30 publications

Growing Stock Volume Estimation for Daiyun Mountain Reserve Based on Multiple Linear Regression and Machine Learning

Growing Stock Volume Estimation for Daiyun Mountain Reserve Based on Multiple Linear Regression and Machine Learning

Biomass allometric models for Larix rupprechtii based on Kosak’s taper curve equations and nonlinear seemingly unrelated regression

Relative Availability of Nitrogen and Calcium Regulates the Growth of Poplar Seedlings Due to Transcriptome Changes

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