Multi-scale biomass estimation of an alpine desert shrub based on relative cover: A case study of Asterothamnus centraliasiaticus in the Qaidam Desert on the Qinghai-Tibet Plateau

Biomass estimates and the allocation characteristics of shrubs are essential indicators for studying the structure, function, and material and energy flows of alpine desert ecosystems. However, conventional destructive biomass estimation methods are unsuitable for large-scale application in alpine desert areas that are characterized by sparse vegetation and comprise extremely fragile ecosystems. In this study, we propose a multi-scale method for estimating the biomass of alpine desert shrubs based on relative cover and verified its accuracy, feasibility, and efficiency using data obtained from 100 individual plants and 27 quadrat plots of Asterothamnus centraliasiaticus, an important species growing in the Qaidam Desert on the Qinghai-Tibet Plateau. Having gained this information, we developed models to estimate the new branch (NBB), aboveground (AGB), and belowground (BGB) biomasses of A. centraliasiaticus at individual, quadrat, and regional scales. The modelling results revealed that an allometric relationship model (power law function) could be used to accurately represent the synergistic relationship between plant morphological variables and biomass increases at all assessed scales. Moreover, we established that at the individual scale, estimation models (NBB = 0.3015 x C1.0610 and AGB =1.0046 x C1.4239) incorporating canopy area (C) as a parameter can better reflect the cumulative characteristics of the new branch and aboveground biomasses of A. centraliasiaticus, respectively, whereas canopy volume (CH, resembles a cylinder) is the most appropriate parameter for the model (BGB = 0.3262 x CH0.8822) used to estimate belowground biomass. In addition, at the sample scale, the total canopy cover (TC) of A. centraliasiaticus in the sample was established to be an appropriate parameter for estimating total biomass (TNBB = 0.0042 x TC1.4647, TAGB = 0.0033 x TC1.6308, and TBGB = 0.0110 x TC1.2554). Furthermore, at the regional scale, we found that incorporating relative canopy cover (RC) in models was effective for estimating the biomass density of A. centraliasiaticus (DNBB = 0.0012 x RC1.4647, DAGB = 0.0014 x RC1.6308, and DBGB = 0.0020 x RC1.2554) and can be combined with regional area estimates to determine the total biomass of A. centraliasiaticus at any spatial scale. On the basis of our findings, we established that the biomass estimation model for alpine desert shrubs, incorporating the parameter relative cover, can effectively solve the longstanding problem of scale conversion and facilitates the rapid and accurate estimation of the biomass components of alpine desert shrubs. In future studies, biomass could be efficiently estimated by combining models based on the relative cover data of shrub communities in relevant areas obtained using aerial photography and remote sensing. The results of this study have important implications for estimating the biomass of alpine desert shrubs, and will accordingly make a valuable contribution to the management of alpine desert ecosystems.