scholarly journals Mapping Maximum Tree Height of the Great Khingan Mountain, Inner Mongolia Using the Allometric Scaling and Resource Limitations Model

Forests ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 380 ◽  
Author(s):  
Yao Zhang ◽  
Yuli Shi ◽  
Sungho Choi ◽  
Xiliang Ni ◽  
Ranga B. Myneni
Keyword(s):  
Vapor Pressure ◽  
Air Temperature ◽  
Inner Mongolia ◽  
Allometric Scaling ◽  
Tree Height ◽  
Laser Altimeter ◽  
Important Indicator ◽  
Metabolic Scaling ◽  
Resource Limitations ◽  
Maximum Tree Height

Maximum tree height is an important indicator of forest vegetation in understanding the properties of plant communities. In this paper, we estimated regional maximum tree heights across the forest of the Great Khingan Mountain in Inner Mongolia with the allometric scaling and resource limitations model. The model integrates metabolic scaling theory and the water–energy balance equation (Penman–Monteith equation) to predict maximum tree height constrained by local resource availability. Monthly climate data, including precipitation, wind speed, vapor pressure, air temperature, and solar radiation are inputs of this model. Ground measurements, such as tree heights, diameters at breast height, and crown heights, have been used to compute the parameters of the model. In addition, Geoscience Laser Altimeter System (GLAS) data is used to verify the results of model prediction. We found that the prediction of regional maximum tree heights is highly correlated with the GLAS tree heights (R2 = 0.64, RMSE = 2.87 m, MPSE = 12.45%). All trees are between 10 to 40 m in height, and trees in the north are taller than those in the south of the region of research. Furthermore, we analyzed the sensitivity of the input variables and found the model predictions are most sensitive to air temperature and vapor pressure.

scholarly journals Cloth simulation-based construction of pit-free canopy height models from airborne LiDAR data

2020 ◽  
Vol 7 (1) ◽  
Author(s):  
Wuming Zhang ◽  
Shangshu Cai ◽  
Xinlian Liang ◽  
Jie Shao ◽  
Ronghai Hu ◽  
...  
Keyword(s):  
Tree Height ◽  
Point Clouds ◽  
Airborne Lidar ◽  
Canopy Height ◽  
Lidar Data ◽  
Cloth Simulation ◽  
Simulation Based ◽  
Maximum Tree Height ◽  
Airborne Lidar Data ◽  
Better Than

Abstract Background The universal occurrence of randomly distributed dark holes (i.e., data pits appearing within the tree crown) in LiDAR-derived canopy height models (CHMs) negatively affects the accuracy of extracted forest inventory parameters. Methods We develop an algorithm based on cloth simulation for constructing a pit-free CHM. Results The proposed algorithm effectively fills data pits of various sizes whilst preserving canopy details. Our pit-free CHMs derived from point clouds at different proportions of data pits are remarkably better than those constructed using other algorithms, as evidenced by the lowest average root mean square error (0.4981 m) between the reference CHMs and the constructed pit-free CHMs. Moreover, our pit-free CHMs show the best performance overall in terms of maximum tree height estimation (average bias = 0.9674 m). Conclusion The proposed algorithm can be adopted when working with different quality LiDAR data and shows high potential in forestry applications.

Ecological responses of Stipa steppe in Inner Mongolia to experimentally increased temperature and precipitation. 4. Carbon exchange

2018 ◽  
Vol 40 (2) ◽  
pp. 159 ◽  
Author(s):  
Luomeng Chao ◽  
Zhiqiang Wan ◽  
Yulong Yan ◽  
Rui Gu ◽  
Yali Chen ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Inner Mongolia ◽  
Ecosystem Respiration ◽  
Block Design ◽  
Net Ecosystem Exchange ◽  
Carbon Exchange ◽  
Ecosystem Productivity ◽  
Temperature And Precipitation ◽  
Gross Ecosystem Productivity

Aspects of carbon exchange were investigated in typical steppe east of Xilinhot city in Inner Mongolia. Four treatments with four replicates were imposed in a randomised block design: Control (C), warming (T), increased precipitation (P) and combined warming and increased precipitation (TP). Increased precipitation significantly increased both ecosystem respiration (ER) and soil respiration (SR) rates. Warming significantly reduced the ER rate but not the SR rate. The combination of increased precipitation and warming produced an intermediate response. The sensitivity of ER and SR to soil temperature and air temperature was assessed by calculating Q10 values: the increase in respiration for a 10°C increase in temperature. Q10 was lowest under T and TP, and highest under P. Both ER and SR all had significantly positive correlation with soil moisture. Increased precipitation increased net ecosystem exchange and gross ecosystem productivity, whereas warming reduced them. The combination of warming and increased precipitation had an intermediate effect. Both net ecosystem exchange and gross ecosystem productivity were positively related to soil moisture and negatively related to soil and air temperature. These findings suggest that predicted climate change in this region, involving both increased precipitation and warmer temperatures, will increase the net ecosystem exchange in the Stipa steppe meaning that the ecosystem will fix more carbon.

scholarly journals Resource availability and disturbance shape maximum tree height across the Amazon

2020 ◽  
Vol 27 (1) ◽  
pp. 177-189
Author(s):  
Eric B. Gorgens ◽  
Matheus H. Nunes ◽  
Tobias Jackson ◽  
David Coomes ◽  
Michael Keller ◽  
...  
Keyword(s):  
Resource Availability ◽  
Tree Height ◽  
Maximum Tree Height

Responses to air temperature and soil moisture of growth of four dominant species on sand dunes of central Inner Mongolia

2008 ◽  
Vol 121 (5) ◽  
pp. 473-482 ◽  
Author(s):  
Yuanrun Zheng ◽  
Glyn M. Rimmington ◽  
Zhixiao Xie ◽  
Lei Zhang ◽  
Ping An ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Air Temperature ◽  
Inner Mongolia ◽  
Dominant Species ◽  
Sand Dunes

scholarly journals Changes in the timing and duration of the near-surface soil freeze/thaw status from 1956 to 2006 across China

2015 ◽  
Vol 9 (3) ◽  
pp. 1321-1331 ◽  
Author(s):  
K. Wang ◽  
T. Zhang ◽  
X. Zhong
Keyword(s):  
Climate Change ◽  
Air Temperature ◽  
Surface Soil ◽  
Eastern China ◽  
Western China ◽  
Actual Number ◽  
Important Indicator ◽  
Near Surface ◽  
Freeze Thaw ◽  
Using Data

Abstract. The near-surface soil freeze/thaw status is an important indicator of climate change. Using data from 636 meteorological stations across China, we investigated the changes in the first date, the last date, the duration, and the number of days of the near-surface soil freeze over the period 1956–2006. The results reveal that the first date of the near-surface soil freeze was delayed by about 5 days, or at a rate of 0.10 ± 0.03 day yr−1, and the last date was advanced by about 7 days, or at a rate of 0.15 ± 0.02 day yr−1. The duration of the near-surface soil freeze decreased by about 12 days or at a rate of 0.25 ± 0.04 day yr−1, while the actual number of the near-surface soil freeze days decreased by about 10 days or at a rate of 0.20 ± 0.03 day yr−1. The rates of changes in the near-surface soil freeze/thaw status increased dramatically from the early 1990s through the end of the study period. Regionally, the changes in western China were greater than those in eastern China. Changes in the near-surface soil freeze/thaw status were primarily controlled by changes in air temperature, but urbanization may also play an important role.

Sign in / Sign up

Export Citation Format

Share Document