Modeling Variation in Crown Profile with Tree Status and Cardinal Directions for Planted Larix olgensis Henry Trees in Northeast China

Accurate quantification of tree biomass is critical and essential for calculating carbon storage, as well as for studying climate change, forest health, forest productivity, nutrient cycling, etc. Tree biomass is typically estimated using statistical models. Although various biomass models have been developed thus far, most of them lack a detailed investigation of the additivity properties of biomass components and inherent correlations among the components and aboveground biomass. This study compared the nonadditive and additive biomass models for larch (Larix olgensis Henry) trees in Northeast China. For the nonadditive models, the base model (BM) and mixed effects model (MEM) separately fit the aboveground and component biomass, and they ignore the inherent correlation between the aboveground and component biomass of the same tree sample. For the additive models, two aggregated model systems with one (AMS1) and no constraints (AMS2) and two disaggregated model systems without (DMS1) and with an aboveground biomass model (DMS2) were fitted simultaneously by weighted nonlinear seemingly unrelated regression (NSUR) and applied to ensure additivity properties. Following this, the six biomass modeling approaches were compared to improve the prediction accuracy of these models. The results showed that the MEM with random effects had better model fitting and performance than the BM, AMS1, AMS2, DMS1, and DMS2; however, when no subsample was available to calculate random effects, AMS1, AMS2, DMS1, and DMS2 could be recommended. There was no single biomass modeling approach to predict biomass that was best for all aboveground and component biomass except for MEM. The overall ranking of models based on the fit and validation statistics obeyed the following order: MEM > DMS1 > AMS2 > AMS1> DMS2 > BM. This article emphasized more on the methodologies and it was expected that the methods could be applied by other researchers to develop similar systems of the biomass models for other species, and to verify the differences between the aggregated and disaggregated model systems. Overall, all biomass models in this study have the benefit of being able to predict aboveground and component biomass for larch trees and to be used to predict biomass of larch plantations in Northeast China.

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Prediction of branch growth using quantile regression and mixed-effects models: An example with planted Larix olgensis Henry trees in Northeast China

Forest Ecology and Management ◽

10.1016/j.foreco.2021.119407 ◽

2021 ◽

Vol 496 ◽

pp. 119407

Author(s):

Zheng Miao ◽

Faris Rafi Almay Widagdo ◽

Lihu Dong ◽

Fengri Li

Keyword(s):

Quantile Regression ◽

Northeast China ◽

Mixed Effects ◽

Mixed Effects Models ◽

Larix Olgensis ◽

Branch Growth ◽

Larix Olgensis Henry

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Spatial and Seasonal Variations of Standardized Photosynthetic Parameters under Different Environmental Conditions for Young Planted Larix olgensis Henry Trees

Forests ◽

10.3390/f9090522 ◽

2018 ◽

Vol 9 (9) ◽

pp. 522 ◽

Cited By ~ 1

Author(s):

Qiang Liu ◽

Fengri Li

Keyword(s):

Environmental Conditions ◽

Seasonal Variations ◽

Seasonal Pattern ◽

Repeated Measurements ◽

Seasonal Patterns ◽

Photosynthetic Parameters ◽

Relative Depth ◽

Larix Olgensis ◽

Vertical Variations ◽

Larix Olgensis Henry

Understanding the spatial and seasonal variations in leaf physiology is critical for accurately modeling the carbon uptake, physiological processes and growth of entire canopies and stands. For a 17-year-old Larix olgensis Henry plantation, vertical whorl-by-whorl sampling and analyses of seasonally repeated measurements of major photosynthetic parameters were conducted, and the correlations between photosynthetic parameters and environmental conditions, leaf morphological traits and spatial position within the crown were analyzed. According to the correlations, the photosynthetic parameters were standardized based on the environmental conditions to avoid the influence of the changing environment on the patterns of spatial and seasonal variations of photosynthetic parameters. The results showed that the standardized light-saturated net photosynthetic rate (SPmax), standardized dark respiration (SRd) and standardized stomatal conductance under saturated light (Sgs-sat) were all negatively related to the relative depth into the crown (RDINC) throughout the growing season. However, their vertical patterns were different during the development of the phenological phase. In addition, different gradients of environmental conditions also influenced the values and the range of the vertical variation in photosynthesis. High temperature and low humidity usually resulted in smaller values and weaker vertical variations of SPmax and Sgs-sat, but larger values and more obvious vertical variations in SRd. SPmax and Sgs-sat usually exhibited a parabolic seasonal pattern in different vertical positions within the crown; however, SRd generally followed a concave pattern. These seasonal patterns were all weaker with increasing RDINC. Different environments also exhibited a significant influence on the seasonal patterns of photosynthesis. We suggested that standardization is necessary before analyzing spatial and seasonal variations. A single environmental condition could not represent the spatial and seasonal patterns under all gradients of the environment. Spatial and seasonal variations should be simultaneously analyzed because they are related to each other.

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Estimation and calibration of stem diameter distribution using UAV laser scanning data: A case study for larch (Larix olgensis) forests in Northeast China

Remote Sensing of Environment ◽

10.1016/j.rse.2021.112769 ◽

2022 ◽

Vol 268 ◽

pp. 112769

Author(s):

Yuanshuo Hao ◽

Faris Rafi Almay Widagdo ◽

Xin Liu ◽

Ying Quan ◽

Zhaogang Liu ◽

...

Keyword(s):

Northeast China ◽

Laser Scanning ◽

Stem Diameter ◽

Diameter Distribution ◽

Larix Olgensis

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Impacts of climate change on biological rotation of Larix olgensis plantations for timber production and carbon storage in northeast China using the 3-PGmix model

Ecological Modelling ◽

10.1016/j.ecolmodel.2020.109267 ◽

2020 ◽

Vol 435 ◽

pp. 109267

Author(s):

Yalin Xie ◽

Xiangdong Lei ◽

Jingning Shi

Keyword(s):

Climate Change ◽

Carbon Storage ◽

Northeast China ◽

Timber Production ◽

Larix Olgensis ◽

Impacts Of Climate Change

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Simulation of climate change and thinning effects on productivity of Larix olgensis plantations in northeast China using 3-PGmix model

Journal of Environmental Management ◽

10.1016/j.jenvman.2020.110249 ◽

2020 ◽

Vol 261 ◽

pp. 110249 ◽

Cited By ~ 3

Author(s):

Yalin Xie ◽

Haiyan Wang ◽

Xiangdong Lei

Keyword(s):

Climate Change ◽

Northeast China ◽

Larix Olgensis

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Response of radial growth to climate change for Larix olgensis along an altitudinal gradient on the eastern slope of Changbai Mountain, Northeast China

Chinese Journal of Plant Ecology ◽

10.17521/cjpe.2015.0216 ◽

2016 ◽

Vol 40 (1) ◽

pp. 24-35 ◽

Cited By ~ 2

Author(s):

YU Jian ◽

◽

...

Keyword(s):

Climate Change ◽

Northeast China ◽

Radial Growth ◽

Altitudinal Gradient ◽

Changbai Mountain ◽

Larix Olgensis ◽

Eastern Slope

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Effects of Graphene on Larix olgensis Seedlings and Soil Properties of Haplic Cambisols in Northeast China

Forests ◽

10.3390/f11030258 ◽

2020 ◽

Vol 11 (3) ◽

pp. 258 ◽

Cited By ~ 1

Author(s):

Jinfeng Song ◽

Kai Cao ◽

Chengwei Duan ◽

Na Luo ◽

Xiaoyang Cui

Keyword(s):

Northeast China ◽

Chemical Properties ◽

Average Diameter ◽

Available Phosphorus ◽

Larix Olgensis ◽

Nitrogen And Phosphorus ◽

Low Concentrations ◽

Physiological Indexes ◽

High Concentrations ◽

Phosphorus And Potassium

We investigated the impacts of graphene application at different concentrations on the growth and physiological characteristics of Changbai larch (Larix olgensis A. Henry) seedlings and the chemical properties and enzyme activities of Haplic Cambisols under these seedlings. The aim is to evaluate the environmental effects of graphene on the afforestation species and the zonal forest soils of Northeast China. Seedlings receiving 0 (CK), 25, 50, 100, 250, or 500 mg L−1 graphene were incubated for 30, 40, or 50 days. Low concentrations (25–50 mg L−1) of graphene increased the dry masses of root, stem, and leaf; however, high concentrations (100–500 mg L−1) inhibited them. Compared with those under 0 mg L−1 graphene, the root length, surface area, volume, and average diameter all increased during the early stages of incubation (i.e., 30 and 40 days) under low concentration of graphene (<50 or 100 mg L−1) and decreased at higher graphene concentration (>100 mg L−1); at 50 days, they were significantly inhibited. At 30 days, graphene decreased superoxide dismutase (SOD) and peroxidase (POD) activities, as well as pigment, soluble protein, and proline contents, and the decline increased with increasing graphene concentration; at 40 and 50 days, the above parameters increased initially and then decreased, reaching a maximum at 50 mg L−1. The changes in relative conductivity and malondialdehyde (MDA), superoxide anion and hydrogen peroxide contents were the opposite of those in the physiological indexes mentioned above. Therefore, graphene caused different degrees of oxidative stress in L. olgensis seedlings. At 30 days, graphene generally increased the organic matter, hydrolytic nitrogen, and available phosphorus and potassium contents of Haplic Cambisols, but these parameters decreased at 40 and 50 days. Graphene generally decreased acid phosphatase, urease, dehydrogenase, and catalase activities. Therefore, when graphene reaches a certain content level in this soil, it may also affect nitrogen and phosphorus cycling.

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