legacy effects

legacy effects

SMB01 Variation in soil respiration and bacterial community due to species-specific plant-soil history at konza prairie

Abstract: 

We conducted a “home vs. away” plant-soil feedback greenhouse experiment using two C3 grass species (Bromus inermis and Pascopyrum smithii) grown in soil collected from Konza Prairie. We used a closed-circuit CO2 trapping method and isotopic analysis to differentiate between root-derived and SOM-derived CO2 production. We investigated how soil chemistry and soil bacterial communities differed in soils with a history of B. inermis vs soils with a history of P. smithii.

Data set ID: 

151

Core Areas: 

Short name: 

SMB01

Methods: 

Location of Sampling: HQ

Frequency of Sampling: One sampling event

Variables Measured: aboveground biomass, belowground biomass, total soil carbon, total soil nitrogen, NH4, NO3, microbial biomass C, total soil respiration, SOM-derived CO2, root-derived CO2, bacterial community richness, bacterial community evenness

Field Methods: All soil used in the greenhouse study was collected in 2015 from the upper 15 cm of an area near the HQ of the Konza Prairie Biological Station, Manhattan, Kansas, USA. The soil was a silty clay loam (fine, mixed mesic Pachic Argiustoll) classified by the USDA Soil Survey as part of the Dwight-Irwin complex. After collection, all soil was passed through a 6 mm mesh sieve, coarsely hand-picked to remove roots and stored air-dried in barrels until the greenhouse experiment began the following year.

Greenhouse Methods: In June 2016, the stored soil was distributed into 180 pots (10 cm diameter x 25 cm deep) constructed from PVC pipe with airtight bottom caps. To allow better drainage and water accumulation below the soil, a 0.5 kg nylon sandbag (~5 cm depth) was placed at the bottom of each pot. To inoculate the stored soil with a fresh microbial community, a small amount of freshly collected soil from the field site was mixed into each pot (3% fresh soil in each pot). Commercially available seeds of the native C3 grass Pascopyrum smithii and the invasive C3 grass Bromus inermis (Stock Seed Farms, Murdock, NE, USA) were germinated in potting soil in the greenhouse. One week after germination, individual seedlings were transplanted into each PVC pot so that half of the soils would be conditioned by P. smithii and half of the soils would be conditioned by B. inermis (Figure 1). After ten weeks of growth, the plants were harvested, and coarse root biomass was removed. Fine root biomass was picked from the soil and removed as much as possible.

Soils conditioned by the same plant species were pooled, homogenized, and redistributed into new pots. Newly germinated seedlings of P. smithii and B. inermis were transplanted into pots with soil that had been conditioned by the same species for the second round of soil conditioning. After ten weeks, the aboveground and belowground biomass of the plants was harvested. Fine root biomass was removed from the soil as much as possible.

For the experimental portion of the greenhouse study, the 180 pots were split into two ‘Plant Legacy’ treatments based on the conditioning phase described above: 1) soil conditioned by B. inermis or 2) soil conditioned by P. smithii. Each pot was also assigned one of the three ‘Current Plant’ treatments: 1) one B. inermis seedling or 2) one P. smithii seedling, as well as 3) a no plant control.

Thirty pots, 5 of each Plant Legacy x Current Plant treatment, were destructively sampled each month over a 3‑month growing period, so that after 12 weeks, 90 of the pots were sampled. For the remaining 90 pots, aboveground and belowground biomass was harvested at the end of the first round of growth, fine roots were removed from the soil as much as possible, and soils belonging to the same treatment were pooled, homogenized, and redistributed in preparation for a second round of growth and sampling. A new seedling of either P. smithii or B. inermis was transplanted into each pot in the same distribution as the first round of the greenhouse experimental phase and allowed to grow for a second 12-week period. Throughout the conditioning and experimental phases of the greenhouse study, soils were kept at 60% water-filled pore space. Pots were watered with DI-H2O via a 50cc syringe attached to a ~15 cm perforated tube inserted into the soil at the time the pots were filled. Additionally, to prevent anoxia, the soils were aerated for ~1 hour every day via a vacuum pump connected to each pot to draw air through the soil. Pots also were rotated within the greenhouse every 2 weeks to avoid potential artefacts of location.

A closed-circuit CO2 trapping method (Cheng et al., 2003) was used to collect belowground CO2 efflux after 4, 8, and 12 weeks of growth during each round of the experimental phase. Thirty pots were randomly selected for measurement on each trapping date (2 Plant Legacy x 3 Current Plant x 5 replicates). Briefly, liquid silicone rubber (Silicones-Inc., High Point, NC, USA) was spread over the surface soil of each pot to form an airtight seal separating aboveground and belowground portions of the pots and plants, which allowed sampling of CO2 released from soil and intact plant roots. After allowing the silicone rubber to cure for 16-18 h, each pot was connected to a soda lime column and the soil atmosphere was scrubbed for 40 minutes with the closed-circuit system to ensure that we were only trapping CO2 produced during the measurement period. For 24 hours, all the CO2 produced belowground in each pot was trapped by bubbling air via air stones in the trapping circuit through bottles containing 300 ml of 0.25M NaOH. After trapping was completed, the silicone rubber was removed, and the pots and plants were destructively sampled. Two subsamples of soil were collected from each pot. One subsample was stored at 4°C for subsequent nutrient and microbial biomass analysis, and the other (collected from the rhizosphere) was stored at -20°C for subsequent microbial community analysis. In pots that contained plants, aboveground and belowground biomass was collected. After rinsing the belowground biomass with DI-H2O, all plant biomass was dried at 60°C for 48 hours and weighed.

Laboratory Methods: Soil microbial biomass C (MBC) was determined using a fumigation-extraction method (Jenkinson and Powlson, 1976) and calculated as the difference between fumigated and unfumigated samples. For each unfumigated sample, ~15 g of moist soil was extracted with 75 ml of 0.5M K2SO4 on a shaker table at 200 rpm for 1 hour. Extracts were passed through a 0.4 µm polycarbonate filter and stored at -20°C. Another set of soil samples was placed into a vacuum desiccator and fumigated with chloroform under a vacuum for 48 hours. Following fumigation, the beaker of chloroform was removed, and residual chloroform was removed from soil samples by repeatedly applying a vacuum and opening the chambers. Total organic C in the extracts was measured with a Shimadzu TOC-L dissolved carbon analyzer (Shimadzu, Kyoto, Japan).

We measured total %C and total %N of soil using a coupled combustion-gas chromatography Flash EA 1112 C/N autoanalyzer. Also, approximately 12 g of moist soil was extracted with 50 ml of 2N KCl on a shaker table at 200 rpm for 1 hour. Extracts were passed through a 0.4 µm polycarbonate filter and frozen for later analysis. Extractable inorganic nitrogen (NH4+ and NO3-) was determined colorimetrically at the Soil Testing Lab at Kansas State University (Manhattan, KS, USA).

Total CO2 respired from soil and plant roots was determined from the inorganic C content of the NaOH traps, measured on a Shimadzu TOC-L dissolved carbon analyzer (Shimadzu, Kyoto, Japan). To determineδ13C of the respired C, trapped CO2 was precipitated as SrCO3 by adding excess 1 M SrCl2 to a subsample of the NaOH traps. The precipitate was rinsed with DI-H2O once every 24 hours for 7 days to neutralize pH, and then dried at 105°C for 24 hours. The δ13C of the SrCO3 was measured using a PDZ Europa 20-20 isotope ratio mass spectrometer (Sercon Ltd., Chesire, UK) at the UC Davis Stable Isotope Facility (Davis, CA, USA). The proportion of CO2 derived from SOM was calculated according to the following isotope mixing model equation: %SOMco2 = (δtδP)/ (δs δP) ∗100, this equation δt represents the δ13C value of the trapped CO2. The δP represents the δ13C value of the plants. In this study, we used a value of -27.5‰ for δP. The δs represents the δ13C value of the soil. We used a value of -16.24‰ for δs based on analysis of the collected bulk soil.

Genomic DNA (gDNA) was extracted from soils using a MoBio PowerSoil Extraction kit (QIAGEN, Carlsbad, CA, USA) according to the manufacturer’s instructions. Successful gDNA extraction was confirmed using a NanoDrop spectrophotometer (ThermoFisher Scientific, Waltham, MA, USA). The bacterial and archaeal 16S rRNA gene was targeted using universal bacterial primers (515F/806R) and amplified using PCR according to Earth Microbiome Project protocols (Caporaso et al., 2012) with a few exceptions. First, we added 2 µl of 1% Bovine Serum Albumin, 0.25 µl of MgCl2 and double the amount of gDNA to each reaction well. Additionally, PCR was only run for 25 cycles instead of 35. Each sample was amplified in triplicate, and amplification was confirmed using gel electrophoresis. Each sample was normalized by DNA concentration and combined into a single amplicon library. The combined library was cleaned using a QIAquick Gel Extraction Kit (QIAGEN, Carlsbad, CA, USA) according to included instructions. The library was sequenced using a 2 x 150 paired-end Illumina MiSeq run, with v2 reagents and a 10% PhiX spike, in the Integrated Genomics Facility at Kansas State University (Manhattan, KS, USA). Raw sequence data were initially processed with the QIIME1 software (Caporaso et al., 2010b). Sequences were quality filtered, joined and demultiplexed, and assigned to operational taxonomic units (OTUs) at 97% sequence similarity. OTUs were aligned to the GreenGenes v. 12_10 16S rRNA gene reference database, and taxonomy was assigned using the RDP classifier (Caporaso et al., 2010a; DeSantis et al., 2006; McDonald et al., 2012; Wang et al., 2007). Chimeras were identified with CHIMERASLAYER and removed from further analysis (Haas et al., 2011). From this point forward, the data were exported for further processing using the phyloseq package within the R statistical software (McMurdie and Holmes, 2013). After ensuring that the DNA extraction and PCR blanks contained a low OTU richness, the decontam package (Davis et al., 2017) identified and removed 168 likely contaminant sequences using a Χ2 analysis. Any sample that retained fewer than 15,000 reads at this point was removed from further analysis. Next, we filtered the taxa so that the data only included OTUs from the kingdom Bacteria. Additionally, we excluded any OTUs associated with mitochondria or chloroplasts. Finally, we removed rare OTUs (<10% relative abundance). Alpha diversity, evenness, and phylum-level response to soil conditioning were estimated using these data. OTU richness and evenness were estimated by rarefying each sample to have the same number of reads as the sample with the least number of reads (14,462 reads). The final dataset included 11,017,633 reads in 140 total samples that were affiliated with 14,307 unique OTUs.

Sequence Data Availability: Raw sequence data are available from the NCBI GenBank SRA at accession number PRJNA674621.

References:  Caporaso, J., Bittinger, K., Bushman, F., DeSantis, T., Andersen, G., R., K., 2010. PyNAST: a flexible tool for aligning sequences to a template alignment. Bioinformatics 26, 266–277. doi:10.1093/bioinformatics/btp636

Caporaso, J.G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F.D., Costello, E.K., Fierer, N., Pẽa, A.G., Goodrich, J.K., Gordon, J.I., Huttley, G.A., Kelley, S.T., Knights, D., Koenig, J.E., Ley, R.E., Lozupone, C.A., McDonald, D., Muegge, B.D., Pirrung, M., Reeder, J., Sevinsky, J.R., Turnbaugh, P.J., Walters, W.A., Widmann, J., Yatsunenko, T., Zaneveld, J., Knight, R., 2010b. QIIME allows analysis of high-throughput community sequencing data. Nature Methods. doi:10.1038/nmeth.f.303

Caporaso, J.G., Lauber, C.L., Walters, W.A., Berg-Lyons, D., Huntley, J., Fierer, N., Owens, S.M., Betley, J., Fraser, L., Bauer, M., Gormley, N., Gilbert, J.A., Smith, G., Knight, R., 2012. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. The ISME Journal 6, 1621–1624. doi:10.1038/ismej.2012.8

Cheng, W., Johnson, D.W., Fu, S., 2003. Rhizosphere effects on decomposition: Controls of plant species, phenology, and fertilization. Soil Science Society of America Journal 67, 1418–1427. doi:10.1016/j.snb.2017.03.014

Davis, N.M., Proctor, D., Holmes, S.P., Relman, D.A., Callahan, B.J., 2017. Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. BioRxiv 221499. doi:10.1101/221499

DeSantis, T.Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E.L., Keller, K., Huber, T., Dalevi, D., Hu, P., Andersen, G.L., 2006. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Applied and Environmental Microbiology 72, 5069–5072. doi:10.1128/AEM.03006-05

Haas, B.J., Gevers, D., Earl, A.M., Feldgarden, M., Ward, D. V., Giannoukos, G., Ciulla, D., Tabbaa, D., Highlander, S.K., Sodergren, E., Methé, B., DeSantis, T.Z., Petrosino, J.F., Knight, R., Birren, B.W., 2011. Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons. Genome Research 21, 494–504. doi:10.1101/gr.112730.110

Jenkinson, D.S., Powlson, D.S., 1976. The effects of biocidal treatments on metabolism in soil—I. Fumigation with chloroform. Soil Biology and Biochemistry 8, 167–177. doi:10.1016/0038-0717(76)90001-8

McDonald, D., Price, M.N., Goodrich, J., Nawrocki, E.P., Desantis, T.Z., Probst, A., Andersen, G.L., Knight, R., Hugenholtz, P., 2012. An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME Journal 6, 610–618. doi:10.1038/ismej.2011.139

McMurdie, P.J., Holmes, S., 2013. phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8, e61217. doi:10.1371/journal.pone.0061217

Wang, Q., Garrity, G.M., Tiedje, J.M., Cole, J.R., 2007. Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Applied and Environmental Microbiology 73, 5261–5267. doi:10.1128/AEM.00062-07

Data sources: 

Maintenance: 

complete

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