2020Land Degradation and DevelopmentRequires access

Aboveground and belowground biomass and its' allometry for Salsola passerina shrub in degraded steppe desert in Northwestern China

Xiong‐zhong Ma, Xin‐ping Wang

Open publisher page 26 citations

Abstract

Abstract Knowledge of the biomass allometry and partitioning is essential for understanding shrub adaptive strategies to degraded habitats as well as for estimating organic carbon storage. We studied biomass accumulation, allocation patterns, and allometric models of Salsola passerina shrub in the Alxa Desert steppe, Northwestern China. We measured aboveground and belowground biomass accumulation across different ages (0–50 years) by destructive sampling. The biomass allocation patterns between aboveground biomass, leaves, branches, and roots were studied by fitting allometric functions for both pooled and age‐classed data. Allometric biomass models were developed by regressing on single‐input variable of basal diameter, crown area, height, and age alone or on the pairwise variables of above four parameters. Biomass accumulation increased with age, aboveground components represented 86–89% of the total biomass, root to shoot biomass ratios increased with shrub age. Allometry patterns of S. passerina were relatively constant, and the growth rate of root was faster than that of aboveground components. Allometric models with two‐input variables were obviously better than single variable models. Crown area and basal diameter were the best predictors for biomass of S. passerina shrub.

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Abstract Knowledge of the biomass allometry and partitioning is essential for understanding shrub adaptive strategies to degraded habitats as well as for estimating organic carbon storage. We studied biomass accumulation, allocation patterns, and allometric models of Salsola passerina shrub in the Alxa Desert steppe, Northwestern China. We measured aboveground and belowground biomass accumulation across different ages (0–50 years) by destructive sampling. The biomass allocation patterns between aboveground biomass, leaves, branches, and roots were studied by fitting allometric functions for both pooled and age‐classed data. Allometric biomass models were developed by regressing on single‐input variable of basal diameter, crown area, height, and age alone or on the pairwise variables of above four parameters. Biomass accumulation increased with age, aboveground components represented 86–89% of the total biomass, root to shoot biomass ratios increased with shrub age. Allometry patterns of S. passerina were relatively constant, and the growth rate of root was faster than that of aboveground components. Allometric models with two‐input variables were obviously better than single variable models. Crown area and basal diameter were the best predictors for biomass of S. passerina shrub.

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Available abstract

Abstract Knowledge of the biomass allometry and partitioning is essential for understanding shrub adaptive strategies to degraded habitats as well as for estimating organic carbon storage. We studied biomass accumulation, allocation patterns, and allometric models of Salsola passerina shrub in the Alxa Desert steppe, Northwestern China. We measured aboveground and belowground biomass accumulation across different ages (0–50 years) by destructive sampling. The biomass allocation patterns between aboveground biomass, leaves, branches, and roots were studied by fitting allometric functions for both pooled and age‐classed data. Allometric biomass models were developed by regressing on single‐input variable of basal diameter, crown area, height, and age alone or on the pairwise variables of above four parameters. Biomass accumulation increased with age, aboveground components represented 86–89% of the total biomass, root to shoot biomass ratios increased with shrub age. Allometry patterns of S. passerina were relatively constant, and the growth rate of root was faster than that of aboveground components. Allometric models with two‐input variables were obviously better than single variable models. Crown area and basal diameter were the best predictors for biomass of S. passerina shrub.

Key concepts: Allometry, Shrub, Biomass (ecology), Tree allometry, Basal area, Biology, Crown (dentistry), Steppe

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