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

Abstract

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.

UAV and Satellite Synergies for Mapping Grassland Aboveground Biomass in Hulunbuir Meadow Steppe

“…Plant structural properties are considered significant for AGB estimation since the AGB is essentially a 3D complex plant trait [24,73,74]. At the same time, due to the saturation of optical signals, the AGB in mature grassland is easy to underestimate [20].…”

Ecuaciones para estimar biomasa de candelilla (Euphorbia antisyphilitica Zucc) en Chihuahua, México

“…La predicción de biomasa o volúmenes en especies de porte arbustivo, suele presentar valores aceptables. Sin embargo, los estadísticos de prueba comúnmente presentan valores más bajos en comparación con la predicción de biomasa en taxones arbóreos, especialmente en coníferas, las cuales por lo general mantienen formas cónicas y sólidas, a diferencia de los arbustos, los cuales son muy ramificados y poco uniformes (Pando-Moreno et al, 2004;Zhang et al, 2016;Vargas-Larreta et al, 2017;Yao et al, 2021). En este sentido, el presente estudio no fue la excepción, ya que los máximos valores en el coeficiente de determinación (R 2 adj ) fueron de 0.84 en comparación con ecuaciones de modelos para especies arbóreas, cuyos coeficientes son generalmente superiores a 0.90 (Vargas-Larreta et al, 2017).…”

Comparison of Three Approaches for Estimating Understory Biomass in Yanshan Mountains

“…According to a previous field survey, the morphology of low-statured trees in the Yanshan Mountains was similar to that of the tree species. Thus, inventory-based parameters like diameter, height, and crown area can be effective in describing their structure; the AGB of the low-statured trees can be more accurately estimated using the inventory method, whereas shrub species, owing to their irregular morphology and inventory parameters like basal diameter and height, are difficult to acquire and may not be effective in describing structural information at individual scale, thus affecting accuracy in biomass estimation [45]. Therefore, evaluating other approaches and determining a better solution for understory quantification in the Yanshan Mountains are necessary.…”