Plant Ecology

Biomass estimation models for two dominant desert shrubs on the northern slopes of Kunlun Mountain

  • ZHANG Yuanmei ,
  • SUN Guili ,
  • LU Yan ,
  • LI Li ,
  • ZHANG Zhihao ,
  • ZHANG Dongdong
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  • 1. College of Forestry and Langscape Architeture, Xinjiang Agricultural University, Urumqi 830052, Xinjiang, China
    2. Key Laboratory of Forestry Ecology and Industrial Technology in Arid Areas, Urumqi 830052, Xinjiang, China
    3. Xinjiang Desert Plant Roots Ecology and Vegetation Restoration Laboratory, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, Xinjiang, China
    4. Cele National Station of Observation and Research for Desert-Grassland Ecosystem, Cele 848300, Xinjiang, China
    5. College of Life Sciences, Shihezi University, Shihezi 832003, Xinjiang, China

Received date: 2023-06-11

  Revised date: 2023-09-08

  Online published: 2024-03-11

Abstract

Mathematical modeling is an important method for estimating shrub biomass. In this study, two desert shrubs, Reaumuria soongarica and Sympegma regelii, commonly found in the Piedmont belt of the northern slopes of the mid-Kunlun Mountains, were observed. The whole-plant harvesting method was employed, and plant height (H), canopy area (S), and plant volume (V) were used as independent variables. Plant above-ground biomass (W1), below-ground biomass (W2), and whole-plant biomass (W3) were used as dependent variables to establish the function model. The selection of optimal biomass estimation models for these two desert shrubs was based on the largest determination coefficient (R2), smallest estimated standard deviation (SEE), and significance level (P < 0.001). The results indicated that quadratic function models were optimal for estimating biomass in both R. soongarica and S. regelii, except for the whole-plant optimal prediction model of S. regelii, which followed a linear function. For R. soongarica, the highest correlation was observed between plant volume (V) and biomass, with R2 ranging from 0.820 to 0.920. For S. regelii, the highest correlation was between canopy area (S) and biomass, with R2 ranging from 0.935 to 0.973. All optimal models for biomass estimation in R. soongarica and S. regelii passed the significance test (P<0.001), with fit rates ranging from 84.1% to 95.6%. These models were deemed reliable for biomass estimation. The outcomes of this study can offer valuable insights for studying carbon stocks and evaluating carbon sink potential in desert ecosystems.

Cite this article

ZHANG Yuanmei , SUN Guili , LU Yan , LI Li , ZHANG Zhihao , ZHANG Dongdong . Biomass estimation models for two dominant desert shrubs on the northern slopes of Kunlun Mountain[J]. Arid Zone Research, 2024 , 41(2) : 284 -292 . DOI: 10.13866/j.azr.2024.02.11

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