scholarly journals Biomass Estimation Models for Six Shrub Species in Hunshandake Sandy Land in Inner Mongolia, Northern China

Forests ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 167
Author(s):  
Xueling Yao ◽  
Guojing Yang ◽  
Bo Wu ◽  
Lina Jiang ◽  
Feng Wang
Keyword(s):  
Water Conservation ◽  
Inner Mongolia ◽  
Estimation Methods ◽  
Biomass Estimation ◽  
Sandy Land ◽  
Shrub Species ◽  
Allometric Models ◽  
Volume Model ◽  
Shrub Biomass ◽  
Estimation Models

Shrub biomass estimation is valuable in assessing ecological health, soil, and water conservation capacity, and carbon storage in arid areas, where trees are scattered, and shrubs are usually dominant. Most shrub biomass estimation models are derived from trees designed for trees, yet shrubs and trees show significant differences in morphology. However, current biomass estimation methods specifically for shrubs are still lacking. This study aimed to test various predictors’ performance in estimating shrub biomass, particularly providing an improved cone frustum volume model as a new predictor. Seven different variables, including three univariates and four composite variables, were selected as predictors in allometric models. Six dominant shrub species of different sizes and morphology in the semi-arid Hunshandake Sandy Land in Inner Mongolia were selected as samples to test the seven predictors’ performances in above-ground biomass estimation. Results showed that the single measurements performed poorly and were not suitable for shrub biomass estimation. The allometric models, including crown-related volumes as predictors, performed much better and were considered ideal for common shrub biomass estimation. The improved cone frustum volume model had more flexible geometric for shrubs of different shapes and sizes, with high fitting accuracy and stability among all the volume predictors. Therefore, we recommend the volume of an inverted cone frustum with a crown diameter and ground diameter as the long and short diameters as an excellent predictor of shrub biomass estimation, especially when studies involve various shrub species, and a general model would be needed.

scholarly journals A biomass equation dataset for common shrub species in China

2021 ◽  
Author(s):  
Yang Wang ◽  
Wenting Xu ◽  
Zhiyao Tang ◽  
Zongqiang Xie
Keyword(s):  
Terrestrial Ecosystem ◽  
Structure And Function ◽  
Biomass Estimation ◽  
Ecosystem Structure ◽  
Biomass Equation ◽  
Shrub Species ◽  
Biomass Equations ◽  
Shrub Biomass ◽  
And Function ◽  
Ecosystem Structure And Function

Abstract. Shrub biomass equations provide an accurate, efficient and convenient method in estimating biomass of shrubland ecosystems and biomass of the shrub layer in forest ecosystems at various spatial and temporal scales. In recent decades, many shrub biomass equations have been reported mainly in journals, books and postgraduate's dissertations. However, these biomass equations are applicable for limited shrub species with respect to a large number of shrub species widely distributed in China, which severely restricted the study of terrestrial ecosystem structure and function, such as biomass, production, and carbon budge. Therefore, we firstly carried out a critical review of published literature (from 1982 to 2019) on shrub biomass equations in China, and then developed biomass equations for the dominant shrub species using a unified method based on field measurements of 738 sites in shrubland ecosystems across China. Finally, we constructed the first comprehensive biomass equation dataset for China’s common shrub species. This dataset consists of 822 biomass equations specific to 167 shrub species and has significant representativeness to the geographical, climatic and shrubland vegetation features across China. The dataset is freely available at https://doi.org/10.11922/sciencedb.00641 for noncommercial scientific applications, and this dataset fills a significant gap in woody biomass equations and provides key parameters for biomass estimation in studies on terrestrial ecosystem structure and function.

Elevated CO2 concentrations affect the growth patterns of dominant C3 and C4 shrub species differently in the Mu Us Sandy Land of Inner Mongolia

Botany ◽  
2017 ◽  
Vol 95 (9) ◽  
pp. 869-877 ◽  
Author(s):  
Qiaoyan Li ◽  
Liming Lai ◽  
Hui Du ◽  
Wentao Cai ◽  
Tianyu Guan ◽  
...  
Keyword(s):  
Elevated Co2 ◽  
Inner Mongolia ◽  
Growth Patterns ◽  
Sandy Land ◽  
Shrub Species ◽  
Mu Us Sandy Land ◽  
Co2 Concentrations

scholarly journals Accurate Model-Based Point of Gaze Estimation on Mobile Devices

Vision ◽  
2018 ◽  
Vol 2 (3) ◽  
pp. 35 ◽  
Author(s):  
Braiden Brousseau ◽  
Jonathan Rose ◽  
Moshe Eizenman
Keyword(s):  
Eye Tracking ◽  
Mobile Devices ◽  
Head Movements ◽  
Roll Angle ◽  
New Method ◽  
Estimation Methods ◽  
Infrared Light ◽  
Gaze Estimation ◽  
Tracking Systems ◽  
Estimation Models

The most accurate remote Point of Gaze (PoG) estimation methods that allow free head movements use infrared light sources and cameras together with gaze estimation models. Current gaze estimation models were developed for desktop eye-tracking systems and assume that the relative roll between the system and the subjects’ eyes (the ’R-Roll’) is roughly constant during use. This assumption is not true for hand-held mobile-device-based eye-tracking systems. We present an analysis that shows the accuracy of estimating the PoG on screens of hand-held mobile devices depends on the magnitude of the R-Roll angle and the angular offset between the visual and optical axes of the individual viewer. We also describe a new method to determine the PoG which compensates for the effects of R-Roll on the accuracy of the POG. Experimental results on a prototype infrared smartphone show that for an R-Roll angle of 90 ° , the new method achieves accuracy of approximately 1 ° , while a gaze estimation method that assumes that the R-Roll angle remains constant achieves an accuracy of 3.5 ° . The manner in which the experimental PoG estimation errors increase with the increase in the R-Roll angle was consistent with the analysis. The method presented in this paper can improve significantly the performance of eye-tracking systems on hand-held mobile-devices.

scholarly journals Closing a gap in tropical forest biomass estimation: taking crown mass variation into account in pantropical allometries

2016 ◽  
Vol 13 (5) ◽  
pp. 1571-1585 ◽  
Author(s):  
Pierre Ploton ◽  
Nicolas Barbier ◽  
Stéphane Takoudjou Momo ◽  
Maxime Réjou-Méchain ◽  
Faustin Boyemba Bosela ◽  
...  
Keyword(s):  
Tropical Forest ◽  
Reference Model ◽  
Original Data ◽  
Carbon Stocks ◽  
Forest Carbon ◽  
Biomass Estimation ◽  
Systematic Bias ◽  
Data Set ◽  
Allometric Models ◽  
Large Trees

Abstract. Accurately monitoring tropical forest carbon stocks is a challenge that remains outstanding. Allometric models that consider tree diameter, height and wood density as predictors are currently used in most tropical forest carbon studies. In particular, a pantropical biomass model has been widely used for approximately a decade, and its most recent version will certainly constitute a reference model in the coming years. However, this reference model shows a systematic bias towards the largest trees. Because large trees are key drivers of forest carbon stocks and dynamics, understanding the origin and the consequences of this bias is of utmost concern. In this study, we compiled a unique tree mass data set of 673 trees destructively sampled in five tropical countries (101 trees > 100 cm in diameter) and an original data set of 130 forest plots (1 ha) from central Africa to quantify the prediction error of biomass allometric models at the individual and plot levels when explicitly taking crown mass variations into account or not doing so. We first showed that the proportion of crown to total tree aboveground biomass is highly variable among trees, ranging from 3 to 88 %. This proportion was constant on average for trees < 10 Mg (mean of 34 %) but, above this threshold, increased sharply with tree mass and exceeded 50 % on average for trees  ≥  45 Mg. This increase coincided with a progressive deviation between the pantropical biomass model estimations and actual tree mass. Taking a crown mass proxy into account in a newly developed model consistently removed the bias observed for large trees (> 1 Mg) and reduced the range of plot-level error (in %) from [−23; 16] to [0; 10]. The disproportionally higher allocation of large trees to crown mass may thus explain the bias observed recently in the reference pantropical model. This bias leads to far-from-negligible, but often overlooked, systematic errors at the plot level and may be easily corrected by taking a crown mass proxy for the largest trees in a stand into account, thus suggesting that the accuracy of forest carbon estimates can be significantly improved at a minimal cost.

scholarly journals Does Shrub Encroachment Indicate Ecosystem Degradation? A Perspective Based on the Spatial Patterns of Woody Plants in a Temperate Savanna-Like Ecosystem of Inner Mongolia, China

Forests ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1248
Author(s):  
Xiao Wang ◽  
Lina Jiang ◽  
Xiaohui Yang ◽  
Zhongjie Shi ◽  
Pengtao Yu
Keyword(s):  
Inner Mongolia ◽  
Woody Plants ◽  
Plant Cover ◽  
Distribution Patterns ◽  
Research Area ◽  
Shrub Encroachment ◽  
Point Pattern Analysis ◽  
Point Pattern ◽  
Shrub Species ◽  
Degraded Ecosystems

Shrub encroachment, i.e., shrub emergence or an increase in woody plant cover, has been widely observed in arid and semiarid grasslands and savannas worldwide since the 2000s. However, until now, there has been a clear division of opinion regarding its ecological implications. One view is that shrub encroachment is an indicator of ecological degradation, and the other is that shrub encroachment is a sign of the restoration of degraded ecosystems. This division leads to completely different judgments about the states and transition phases of shrub-encroached ecosystems, which further affects decisions about their conservation and management. To determine whether ecosystems experiencing shrub encroachment are degrading or are in a postdegraded restoration stage, the spatial distributions and interactions of woody plants after shrub encroachment were investigated in this study. An Ulmus pumila-dominated temperate savanna-like ecosystem with significant shrub encroachment in the Otindag Sandy Land, Inner Mongolia, China, was selected as the research area, and woody plants were surveyed within a 25-hectare (500 × 500 m) plot. Spatial point pattern analysis was employed to analyze the distribution patterns of the woody plants. The results indicated different patterns for U. pumila trees, i.e., a random distribution pattern for old trees (with a diameter at breast height (DBH) of more than 20 cm) and aggregated distribution patterns for medium (5 cm ≤ DBH < 20 cm) and juvenile trees (DBH < 5 cm) at scales of 0–9 and 0–12 m, respectively. For most shrubs, there was significant aggregation at a scale of 0–6 m. However, there were significant negative relationships between old U. pumila trees (DBH ≥ 20 cm) and most shrub species, such as Caragana microphylla and Spiraea aquilegifolia. In contrast, there were positive relationships between juvenile trees (DBH < 5 cm) and most shrub species. These results suggest that, to some extent, shrub encroachment may have disrupted the normal succession pattern in the U. pumila community in this area, and without conservation, the original tree-dominated temperate savanna-like ecosystem may continue to deteriorate and eventually become a shrub-dominated temperate savanna-like ecosystem.

Pulmonary blood flow and tissue volume: model analysis of rebreathing estimation methods

1983 ◽  
Vol 55 (1) ◽  
pp. 205-211 ◽  
Author(s):  
G. M. Burma ◽  
G. M. Saidel
Keyword(s):  
Blood Flow ◽  
Pulmonary Blood Flow ◽  
Breathing Pattern ◽  
Estimation Methods ◽  
Balance Model ◽  
Mass Balance Model ◽  
Volume Model ◽  
Dynamic Mass ◽  
Ventilation And Perfusion ◽  
Rebreathing Methods

As the basis for comparing rebreathing methods of estimating pulmonary blood flow (Q) and tissue-capillary volume (Vtc), we use a dynamic mass-balance model for gas species having different physicochemical properties (e.g., He, CO, C2H2). The model accounts for the effects of ventilation and perfusion inhomogeneities, breathing pattern variation, lung and rebreathing-bag volumes, and recirculation. Also, we examine the variability of the estimates caused by random error. In addition to analyzing two well-known methods, we show how an appropriate synthesis of these methods can lead to improved estimates.

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