DOI: 10.5061/dryad.280gb5mv6
title: Fertilization can accelerate the pace of soil microbial community response to rest-grazing duration in the Three-river Source Region of China

description: Objectives Overgrazing leads to grassland degradation and productivity
 decline. Rest-grazing during the regreen-up period can quickly restore
 grassland and fertilization is a common restoration measure. Meanwhile,
 soil microorganisms are more sensitive indicators. Therefore, the
 experiment of rest-grazing time and fertilization was carried out to
 explore the response of soil microorganisms to rest-grazing time and
 fertilization measures. Methods A field control experiment with
 rest-grazing time and fertilization as factors was conducted from the time
 when grass returned to green till the livestock moved to the summer
 pasture in Dawu Town of Maqin County. The primary treatment we established
 was the five rest-grazing times, including rest-grazing times of 20 days,
 30 days, 40 days, 50 days, and traditional grazing was used as a check
 group. At the same time, the secondary treatment was nitrogen addition of
 300 kg·hm-2 in each primary treatment. Results The results showed that:
 the total phospholipid fatty acid (total PLFA), actinomyces (Act) and
 arbuscular mycorrhizal fungi (AMF) showed an ever-increasing
 biomass with the increase of rest-grazing time and the highest was at 50
 days of rest-grazing, and they were all significantly higher than CK. In
 addition, soil microbial biomass carbon-nitrogen ratio (MBC/MBN) had a
 great influence on the change of microbial community. Applying nitrogen
 fertilizer can increase the maximum value of biomass of all PLFA groups
 and the biomass of all PLFA groups changed in an “inverted V” shape with
 the increase of rest-grazing time. Besides, instead of MBC/MBN,
 NO3--N was positively affected by the biomass of all PLFA groups, which
 actively regulated the trend of microbial functions. Conclusions The
 longer rest-grazing time is more conducive to the biomass of all PLFA
 groups. However, applying nitrogen fertilizer could break this pattern,
 namely, the 30d rest-grazing would be beneficial to the biomass of all
 PLFA groups. These findings provide key information that rest-grazing
 during the regreen-up period is beneficial to all PLFA groups
 and fertilization could change the response of microorganisms to
 rest-grazing, which provides reference measures for the restoration of
 degraded alpine meadows.
description: Soil samples were obtained in
 August 2017, when the grass was growing vigorously. In each subplot, three
 soil samples were collected to reduce spatial heterogeneity, and five soil
 cores (3.5cm diameter) were taken at a depth of 0 to 15 cm regarding each
 one as one soil sample.
  After the soil samples
 were measured, the data of three soil samples from each subplot were
 averaged to obtain one value. Therefore, only one value was obtained for each subplot. In
 total, three independent
 samples were obtained from each treatment of three replicate blocks (A, B and C).
 In order
 to avoid the influence of
 livestock waste on soil characteristics, we absolutely avoid livestock
 waste and the traces of livestock waste when sampling. A total of 90 soil
 samples (three soil samples ×ten subplots × three replicate blocks) were
 collected in this study. Then, three cutting ring soil samples were
 collected from 0–15 cm depths in each plot to determine the soil moisture
 content (SM). In addition,
 when collecting soil samples, we remove debris such as plant litter, stone
 particles and livestock excreta. Each soil sample was sieved through a 2 mm mesh
 and then divided into two parts when the soil samples were taken back to
 the laboratory (Joshi et
 al., 2023).
 One part of the fresh soil from the
 field was stored at 4°C for microbial biomass (carbon and nitrogen) for
 inorganic N (NH<sub>4</sub><sup>+</sup>−N and
 NO<sub>3</sub><sup>－</sup>−N ) and available phosphorus (AP) analyses, and
 the other part was air-dried indoors and used to determine indicators such
 as soil physicochemical properties (Zhao et al., 2018).In order to
 reveal the effects of rest-grazing and fertilization during the regreen-up
 period on the structure of soil microbial community. Soil microbial PLFA
 was determined based on the method of Bossio and Scow (1998)
 (Bossi et al.,
 1998).
 The data for each subplot was expressed as the
 mean of three soil
 samples, so data analysis was carried out on the data duplicate value
 (n=3),
 and the data analysis was
 performed according to the following steps. Firstly, one-way analysis of variance (ANOVA)
 and least significant difference (LSD) tests were used to examine the
 differences of soil physicochemical properties and microbial
 community structure among the different rest-grazing treatments. Then the
 independent sample T-tests were used to examine the response of soil
 physicochemical properties and microbial community structure to
 fertilization treatment. Secondly, the correlation analysis was used to
 test the relationship between soil physicochemical properties and
 microbial community structure. Finally, the redundancy analysis method
 (RDA) was used to evaluate the associations between soil physicochemical
 properties and community microorganisms. The above analysis used Microsoft Excel 2013 to
 organize and summarize the original data, and used SPSS25.0 statistical
 software to conduct statistical analysis on the data. Histogram of
 microbial community compositions and percentage increase of fertilization
 to the maximum value of all PLFA groups were drawn with Origin 2021. The
 graphs of correlation analysis were performed using the “ggplot2” and
 “ggthemes” packages in R 4.2.2 and RDA employed CANOCO 5 to complete
 (Lu et al., 2023). P＜0.05 was considered statistically
 significant. Bossio, D. A., & Scow, K. M. (1998).
 Impacts of carbon and flooding on soil microbial communities: phospholipid
 fatty acid profiles and substrate utilization patterns. Microbial ecology,
 35, 265-278. Joshi, R. K.,
 & Garkoti, S. C. (2023). Influence of vegetation types on soil
 physical and chemical properties, microbial biomass and stoichiometry in
 the central Himalaya. Catena, 222, 106835. https://doi.or.1016/j.catena.2022.106835g/10 Lu, J., Feng, S., Wang, S., Zhang, B., Ning, Z., Wang, R., ... & Zhao, X. (2023). Patterns and driving mechanism of soil organic carbon, nitrogen, and phosphorus stoichiometry across northern China’s desert-grassland transition zone. Catena, 220, 106695. https://doi.org/10.1016/j.catena.2022.106695 Zhao, R., Hui, R., Liu, L., Xie, M., & An, L. (2018). Effects of snowfall depth on soil physical–chemical properties and soil microbial biomass in moss–dominated crusts in the Gurbantunggut Desert, Northern China. Catena, 169, 175-182. https://doi.org/10.1016/j.catena.2018.05.042
description: This README file was generated on 2023-11-14 by Xuanbo Zhou. GENERAL
 INFORMATION 1. Title of Dataset: Fertilization can Accelerate the Pace of
 Soil Microbial Community Response to Rest-grazing Duration in the
 Three-river Source Region of China 2. Author Information A. Principal
 Investigator Contact Information Name: Xuanbo Zhou Institution: Qinghai
 University Address: Xining,Qinghai, OR China Email: 15500533873@163.com
 <br> B. Corresponding author Contact Information Name:Xiaoli Wang
 Institution: Qinghai University Address: Xining,Qinghai, OR China Email:
 wxl.yu@163.com 3. Date of data collection (single date, range, approximate
 date): July 2017 - August 2017 4. Geographic location of data collection:
 Yongbao Animal Husbandry Committee, Dawu Town, Guoluo Tibetan Autonomous
 Prefecture 5. Information about funding sources that supported the
 collection of the data: National Natural Science Foundation of China
 (32260327 ,32230068 & U21A20183) and the “Western Light” Young
 Scholars Program of the Chinese Academy of Sciences. SHARING/ACCESS
 INFORMATION 1. Licenses/restrictions placed on the data: CC0 1.0 Universal
 (CC0 1.0) Public Domain 2. Links to publications that cite or use the
 data: Xuanbo Zhou, Xiaoli Wang, Yushou ma...& Lele Xie.(2023).
 Fertilization can Accelerate the Pace of Soil Microbial Community Response
 to Rest-grazing Duration in the Three-river Source Region of China 3.
 Links to other publicly accessible locations of the data: None 4.
 Links/relationships to ancillary data sets: None 5. Was data derived from
 another source? No A. If yes, list source(s): NA 6. Recommended citation
 for this dataset: Xuanbo Zhou, Xiaoli Wang, Yushou ma...& Lele
 Xie.(2023). . Data from: Fertilization can Accelerate the Pace of Soil
 Microbial Community Response to Rest-grazing Duration in the Three-river
 Source Region of China. Dryad Digital
 Repository.https://doi.org/10.5061/dryad.280gb5mv6 DATA & FILE
 OVERVIEW 1. File List: A) Soil original datas with non fertilization.csv
 B) Soil original datas with fertilization.csv C) PLFA original datas with
 non fertilization.csv D) PLFA original datas with fertilization.csv E)
 Correlation cofficient datas with non fertilization.csv F) Correlation
 cofficient datas with fertilization.csv G) P value with non
 fertilization.csv H) P value with fertilization.csv 2. Relationship
 between files, if important: None 3. Additional related data collected
 that was not included in the current data package: None 4. Are there
 multiple versions of the dataset? No A. If yes, name of file(s) that was
 updated: NA i. Why was the file updated? NA ii. When was the file updated?
 NA
 #########################################################################
 DATA-SPECIFIC INFORMATION FOR: Soil original datas with non
 fertilization.csv 1. Number of variables: 14 2. Number of cases/rows: 16
 3. Variable List: * Name: A1,A2orA3(i.e., three independent replicate
 blocks); all treatments CK, 20d, 30d, 40or 50d ( i.e., times of
 rest-grazing). * SM(%): soil moisture content * pH: soil potential of
 hydrogen * SOC(g/kg): soil organic carbon * TN(g/kg): total nitrogen *
 soil C:N:soil carbon-nitrogen ratio * NH4+(mg/g) and NO3-(mg/g): inorganic
 N * TP(g/kg): total phosphorus * AP(mg/g):vailable phosphorus *
 TK(g/kg):total potassium * MBC(mg/g):soil microbial biomass carbon *
 MBN(mg/g):soil microbial biomass nitrogen * MBC:MBN:soil microbial biomass
 carbon-nitrogen ratio 4. Missing data codes: None 5. Specialized formats
 or other abbreviations used: None
 #########################################################################
 DATA-SPECIFIC INFORMATION FOR: Soil original datas with fertilization.csv
 1. Number of variables: 14 2. Number of cases/rows: 16 3. Variable List: *
 Name: A1,A2orA3(i.e., three independent replicate blocks); all treatments
 CK, 20d, 30d, 40or 50d ( i.e., times of rest-grazing); N：representing this
 group is fertilization treatment. * SM(%): soil moisture content * pH:
 soil potential of hydrogen * SOC(g/kg): soil organic carbon * TN(g/kg):
 total nitrogen * soil C:N:soil carbon-nitrogen ratio * NH4+(mg/g) and
 NO3-(mg/g): inorganic N * TP(g/kg): total phosphorus * AP(mg/g):vailable
 phosphorus * TK(g/kg):total potassium * MBC(mg/g):soil microbial biomass
 carbon * MBN(mg/g):soil microbial biomass nitrogen * MBC:MBN:soil
 microbial biomass carbon-nitrogen ratio 4. Missing data codes: NA (data
 not available) 5. Specialized formats or other abbreviations used: None
 #########################################################################
 DATA-SPECIFIC INFORMATION FOR: PLFA original datas with non
 fertilization.csv 1. Number of variables: 10 2. Number of cases/rows: 16
 3. Variable List: * Name: A1,A2orA3(i.e., three independent replicate
 blocks); all treatments CK, 20d, 30d, 40or 50d ( i.e., times of
 rest-grazing). * AMF(nmol/g): arbuscular mycorrhizal fungi * Act(nmol/g):
 actinomyces * B(nmol/g): bacterial biomarkers * G-(nmol/g): gram-negative
 bacterial PLFA biomarkers * G+:(nmol/g)gram-positive bacterial PLFA
 biomarkers * F(nmol/g): fungal PLFA biomarkers * F:B: bacterial PLFA
 biomarker biomass ratios * G+:G-: the ratio of gram-positive bacterial
 PLFA biomass to gram-negative bacterial PLFA biomass * total PLFA(nmol/g):
 the total phospholipid fatty acid 4. Missing data codes: NA (data not
 applicable) 5. Specialized formats or other abbreviations used: None
 #########################################################################
 DATA-SPECIFIC INFORMATION FOR: PLFA original datas with fertilization.csv
 1. Number of variables: 10 2. Number of cases/rows: 16 3. Variable List: *
 Name: A1,A2orA3(i.e., three independent replicate blocks); all treatments
 CK, 20d, 30d, 40or 50d ( i.e., times of rest-grazing); N：representing this
 group is fertilization treatment. * AMF(nmol/g): arbuscular mycorrhizal
 fungi * Act(nmol/g): actinomyces * B(nmol/g): bacterial biomarkers *
 G-(nmol/g): gram-negative bacterial PLFA biomarkers *
 G+(nmol/g):gram-positive bacterial PLFA biomarkers * F(nmol/g): fungal
 PLFA biomarkers * F:B: bacterial PLFA biomarker biomass ratios * G+:G-:
 the ratio of gram-positive bacterial PLFA biomass to gram-negative
 bacterial PLFA biomass * total PLFA(nmol/g): the total phospholipid fatty
 acid 4. Missing data codes: None 5. Specialized formats or other
 abbreviations used: None
 #########################################################################
 DATA-SPECIFIC INFORMATION FOR: Correlation cofficient datas with non
 fertilization.csv These are the data used to indicate the correlation
 absolute value between soil physicchemical properties and soil microbial
 community. 1. Number of variables: 10 2. Number of cases/rows: 14 3.
 Variable List: * r value: soil physicchemical properties( Abbreviations
 are shown in “Soil original datas with non fertilization.csv”) *
 AMF(nmol/g): arbuscular mycorrhizal fungi * Act(nmol/g): actinomyces *
 B(nmol/g): bacterial biomarkers * G-(nmol/g): gram-negative bacterial PLFA
 biomarkers * G+(nmol/g):gram-positive bacterial PLFA biomarkers *
 F(nmol/g): fungal PLFA biomarkers * F:B: bacterial PLFA biomarker biomass
 ratios * G+:G-: the ratio of gram-positive bacterial PLFA biomass to
 gram-negative bacterial PLFA biomass * total PLFA(nmol/g): the total
 phospholipid fatty acid 4. Missing data codes: NA (data not available) 5.
 Specialized formats or other abbreviations used: None
 #########################################################################
 DATA-SPECIFIC INFORMATION FOR: Correlation cofficient datas with
 fertilization.csv These are the data used to indicate the correlation
 absolute value between soil physicchemical properties and soil microbial
 community of fertilization treatment. 1. Number of variables: 10 2. Number
 of cases/rows: 14 3. Variable List: * r value: soil physicchemical
 properties( Abbreviations are shown in “Soil original datas with non
 fertilization.csv”) * AMF(nmol/g): arbuscular mycorrhizal fungi *
 Act(nmol/g): actinomyces * B(nmol/g): bacterial biomarkers * G-(nmol/g):
 gram-negative bacterial PLFA biomarkers * G+(nmol/g):gram-positive
 bacterial PLFA biomarkers * F(nmol/g): fungal PLFA biomarkers * F:B:
 bacterial PLFA biomarker biomass ratios * G+:G-: the ratio of
 gram-positive bacterial PLFA biomass to gram-negative bacterial PLFA
 biomass * total PLFA(nmol/g): the total phospholipid fatty acid 4. Missing
 data codes: None 5. Specialized formats or other abbreviations used: None
 #########################################################################
 DATA-SPECIFIC INFORMATION FOR: P value with non fertilization.csv These
 are the data used to indicate the P value between soil physicchemical
 properties and soil microbial community. 1. Number of variables: 10 2.
 Number of cases/rows: 14 3. Variable List: * P-value: soil physicchemical
 properties( Abbreviations are shown in “Soil original datas with non
 fertilization.csv”) * AMF(nmol/g): arbuscular mycorrhizal fungi *
 Act(nmol/g): actinomyces * B(nmol/g): bacterial biomarkers * G-(nmol/g):
 gram-negative bacterial PLFA biomarkers * G+(nmol/g):gram-positive
 bacterial PLFA biomarkers * F(nmol/g): fungal PLFA biomarkers * F:B:
 bacterial PLFA biomarker biomass ratios * G+:G-: the ratio of
 gram-positive bacterial PLFA biomass to gram-negative bacterial PLFA
 biomass * total PLFA(nmol/g): the total phospholipid fatty acid 4. Missing
 data codes: None 5. Specialized formats or other abbreviations used: None
 #########################################################################
 DATA-SPECIFIC INFORMATION FOR: P value with fertilization.csv These are
 the data used to indicate the P value between soil physicchemical
 properties and soil microbial community of fertilization treatment.. 1.
 Number of variables: 10 2. Number of cases/rows: 14 3. Variable List: *
 P-value: soil physicchemical properties( Abbreviations are shown in “Soil
 original datas with non fertilization.csv”) * AMF(nmol/g): arbuscular
 mycorrhizal fungi * Act(nmol/g): actinomyces * B(nmol/g): bacterial
 biomarkers * G-(nmol/g): gram-negative bacterial PLFA biomarkers *
 G+(nmol/g):gram-positive bacterial PLFA biomarkers * F(nmol/g): fungal
 PLFA biomarkers * F:B: bacterial PLFA biomarker biomass ratios * G+:G-:
 the ratio of gram-positive bacterial PLFA biomass to gram-negative
 bacterial PLFA biomass * total PLFA(nmol/g): the total phospholipid fatty
 acid 4. Missing data codes: None 5. Specialized formats or other
 abbreviations used: None