Title

Microbial necromass carbon accumulation coefficients (NAC) dataset

Author

Bingbing Han, Yanzhong Yao, Yini Wang, Xiaoxuan Su, Lihua Ma, Xinping Chen, Zhaolei Li *

Corresponding author: Zhaolei Li, Professor

E-mail: lizhaolei@swu.edu.cn

Correspondence address: College of Resources and Environment, and Academy of Agricultural Sciences, Southwest University, Chongqing 400715, China

Data abstract

The accumulation of microbial necromass carbon has drawn mounting attention due to the slow decomposition. However, it remains unclear what determines the microbial necromass carbon accumulation via reiterated community turnover on large spatial scales. This study aimed to explore the characteristics of soil necromass carbon accumulation in terrestrial ecosystems. A dataset was compiled with 993 observations on the coefficient of microbial carbon accumulation in the equilibrium from 82 peer-reviewed papers. The linear mixed-effect models and structural equation models were used to ascertain the controlling factors of NAC on a global scale. The average NAC was higher in croplands (28.2) and forests (26.8) than that in grasslands (21.1). Although the edaphic factors seemingly affect the NAC whereby the NAC lowered in soils with high levels of pH and clay content on a global scale, the biotic factors, particularly for the living microorganism abundance and microbial biomass nitrogen content, were the pivotal drivers of NAC that accounted for approximately 42.5% of the geographic variances in NAC. More organic carbon was likely to be preserved in soil with a higher NAC regardless of ecosystem types. Novel findings on the overriding controls from the living microorganism abundance and microbial biomass nitrogen in driving NAC raise an urgent need for viable strategies in manipulating microbial characteristics for carbon sequestrations.

Data collect

The NACs dataset was compiled from peer-reviewed papers. These peer-reviewed papers were obtained by means of two platforms: the Web of Science (http://apps.webofkonwledge.com) and the China National Knowledge Infrastructure Database (http://www.cnki.net). At the same time, the papers were supplemented by Google Scholar. The keywords used to search papers are soil microbial biomass AND microbial necromass AND microbial residue* AND amino sugar* AND PLFAs. The publishing date for the peer-reviewed paper was up to January 20, 2023. The eligible peer-reviewed papers matched the following criteria: (1) Soil microbial necromass was measured using amino sugars as markers; (2) The living microorganisms were determined by phospholipid fatty acid (PLFAs). Finally, the NAC dataset was constructed based on the 82 peer-reviewed papers.

The details of the experimental site were also extracted from papers, including the geographic information of the experiment site (i.e., latitude and longitude), climate conditions (i.e., mean annual temperature and mean annual precipitation), and ecosystem types (i.e., grasslands, forests, and croplands). Additionally, soil physicochemical properties [soil pH, the ratio of carbon to nitrogen (soil C: N), total nitrogen (TN), bulk density (BD), clay content, and ammonium content (NH4+)] and the number of replicates were also extracted from the articles. Additionally, in the NAC dataset, the empty cells are representing the data scarcity (i.e., NA values). You should know that not every article will contain all the metrics.

Data analysis

The content of fungal and bacterial necromass carbon was calculated based on the concentrations of amino sugar in microbial cell walls: glucosamine and muramic acid. The bacterial necromass carbon and fungal necromass carbon were calculated using equations (1) and (2).

where, MurA is muramic acid and GlcN is glucosamine. In equation (1), 45 is the conversion factor from MurA to bacterial necromass carbon; in equation (2), 9 is the conversion factor from GlcN to fungal necromass carbon; while 179.17 and 251.23 are the molecule weights of GlcN and MurA, respectively. Total microbial necromass carbon was the sum of fungal necromass carbon and bacterial necromass carbon. For the absence of microbial biomass carbon (MBC) in some experimental sites.

The NAC functions as the ratio of the microbial necromass carbon to microbial biomass carbon:

where MBC is soil microbial biomass carbon.

The linear mixed-effect models were used to test the bivariate relationship between the NAC and environmental factor by means of lme4 packages in R (version 4.2.2., R Core Team). The equation (4) was:

where NAC refers to the microbial necromass carbon accumulation coefficient, lnX is the logarithm of each edaphic and climatic factor (except for soil pH and fungi: bacteria ratio), refers to the intercept of this model, refers to the slope value, refers to the random effect of study, refers to the sampling error.

Document Type

We will upload it in data_NAC_2023.csv format to the Dryad database. The main variables collected in the data form were muramic acid (MurA) and glucosamine (GlcN). We perform the calculation of NAC based on equations 1, 2, and 3 above. Total biomass represents the abundance of living microorganisms. Fungal biomass represents the abundance of fungi. Bacterial biomass represents the abundance of bacteria. MBC is microbial biomass nitrogen. SOC is soil organic carbon.

Data processing software

We processed the entire set of data by utilizing the R language, version 4.2.2., R Core Team.

Contact Information

Corresponding author: Zhaolei Li, Professor

E-mail: lizhaolei@swu.edu.cn

ORCID: https://orcid.org/0000-0001-8767-1277