Harvard Forest

Data Archive

HF451

Effects of Long-Term Soil Warming on Microbial Yield, Acquisition, and Stress Traits at Harvard Forest 2014

Related Publications

Data

• hf451-01: soil microbial traits (preview)

Overview

• Lead: Kristen DeAngelis
• Investigators: Melissa Shinfuku
• Contact: Information Manager
• Start date: 2014
• End date: 2014
• Status: complete
• Location: Prospect Hill Tract (Harvard Forest)
• Latitude: +42.54 degrees
• Longitude: -72.18 degrees
• Elevation: 365 meter
• Datum: WGS84
• Taxa:
• Release date: 2024
• Language: English
• EML file: knb-lter-hfr.451.1
• DOI: digital object identifier
• EDI: data package
• DataONE: data package
• Related links:
• Study type: short-term measurement
• Research topic: biodiversity studies; large experiments and permanent plot studies
• LTER core area: population studies
• Keywords: climate change, genetics, microbes, microbial biomass, soil warming
• Abstract:

  Soil microbial traits drive ecosystem functions. This relationship can explain why microbial functional diversity is typically positively correlated with ecosystem function. However, microbial adaptation to climate change related warming stress can shift microbial traits with direct implications for carbon cycling in the soil. Here, we investigated how long-term warming affects the relationship between microbial trait diversity and ecosystem function. Soils were sampled after 24 years of +5\degree C warming alongside unheated control soils from the Harvard Forest Long-Term Ecological Research site. Ecosystem function was estimated from six different enzyme activities and microbial biomass. This data was coupled with metatranscriptomics sequencing, where reads were assigned to yield, acquisition, or stress trait categories. We found that in organic horizon soils, warming decreased the richness of acquisition-related traits. In the mineral soils, we observed that heated soils exhibited a negative relationship with the richness of acquisition related traits. These results suggest that the microbial communities exposed to long-term warming is shifting away from a resource acquisition life history strategy.

• Methods:

  Functional diversity was calculated from previously published data accessed through the NCBI Short Read Archive (Roy Chowdhury et al. 2021). Raw reads were quality checked using FASTQC before reads were merged using FLASh (Magoč and Salzberg 2011). Merged reads were quality filtered using Trimmomatic (Bolger et al. 2014), and ribosomal RNA sequences removed using sortmerna (v 4.3.6) (Kopylova et al. 2012). Reads were aligned against the NCBI non-redundant (nr) protein database in DIAMOND (v 2.1.8) (Buchfink et al. 2021). Hits from the nr protein database were translated into different reading frames in EMBOSS (v 6.6.0) (Rice et al. 2000), then assigned KEGG Orthology (KO) in MEGAN Ultimate Edition (v 6.25.5) (Huson et al. 2007) as well as queried in HMMER (v 3.3.2) against the CAZyme database, retrieved from dbCAN3 (Zheng et al. 2023). Reads were classified along the Yield Acquisition Stress (YAS) framework (Malik et al. 2020) based on KEGG pathways. We also included any glycoside hydrolases identified in the CAZy database as belonging to the acquisition category (Malik et al. 2020). We calculated Shannon's diversity, Chao1 estimated richness, and Pielou's evenness for the KEGG Orthologs and the yield, acquisition, and stress trait categories following a repeated rarefying approach (Schloss 2024).

• Organization: Harvard Forest. 324 North Main Street, Petersham, MA 01366, USA. Phone (978) 724-3302. Fax (978) 724-3595.

• Project: The Harvard Forest Long-Term Ecological Research (LTER) program examines ecological dynamics in the New England region resulting from natural disturbances, environmental change, and human impacts. (ROR).

• Funding: National Science Foundation LTER grants: DEB-8811764, DEB-9411975, DEB-0080592, DEB-0620443, DEB-1237491, DEB-1832210.

• Use: This dataset is released to the public under Creative Commons CC0 1.0 (No Rights Reserved). Please keep the dataset creators informed of any plans to use the dataset. Consultation with the original investigators is strongly encouraged. Publications and data products that make use of the dataset should include proper acknowledgement.

• License: Creative Commons Zero v1.0 Universal (CC0-1.0)

• Citation: DeAngelis K. 2024. Effects of Long-Term Soil Warming on Microbial Yield, Acquisition, and Stress Traits at Harvard Forest 2014. Harvard Forest Data Archive: HF451 (v.1). Environmental Data Initiative: https://doi.org/10.6073/pasta/11899f666964f50b74fad0c356c4edbc.

Detailed Metadata

hf451-01: soil microbial traits

1. sample_id: sample ID
2. timepoint: sampling timepoint
   • T2: 3 June 2014
   • T6: 28 October 2014
3. warming: warming treatment
   • C: control treatment
   • H: heated treatment
4. plot: plot number that sample originated from
5. soil_type: soil type that sample originated from
   • Mineral: mineral soils
   • Organic: organic horizon
6. water_content: gravimetric soil water content (unit: dimensionless / missing value: NA)
7. doy: day of year of sampling (unit: dimensionless / missing value: NA)
8. date: date of sampling
9. Y_shannon_avg: Shannon's diversity of yield associated traits averaged across 1000 rarefactions (unit: dimensionless / missing value: NA)
10. Y_chao_avg: Chao1 estimated richness of yield associated traits averaged across 1000 rarefactions (unit: dimensionless / missing value: NA)
11. Y_pielou_avg: Pielou's evenness of yield associated traits averaged across 1000 rarefactions (unit: dimensionless / missing value: NA)
12. A_shannon_avg: Shannon's diversity of acquisition associated traits averaged across 1000 rarefactions (unit: dimensionless / missing value: NA)
13. A_chao_avg: Chao1 estimated richness of acquisition associated traits averaged across 1000 rarefactions (unit: dimensionless / missing value: NA)
14. A_pielou_avg: Pielou's evenness of acquisition associated traits averaged across 1000 rarefactions (unit: dimensionless / missing value: NA)
15. S_shannon_avg: Shannon's diversity of stress associated traits averaged across 1000 rarefactions (unit: dimensionless / missing value: NA)
16. S_chao_avg: Chao1 estimated richness of stress associated traits averaged across 1000 rarefactions (unit: dimensionless / missing value: NA)
17. S_pielou_avg: Pielou's evenness of stress associated traits averaged across 1000 rarefactions (unit: dimensionless / missing value: NA)
18. YAS_proportion_NMDS1: NMDS axis 1 of yield, acquisition, and stress traits (unit: dimensionless / missing value: NA)
19. YAS_proportion_NMDS2: NMDS axis 2 of yield, acquisition, and stress traits (unit: dimensionless / missing value: NA)