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Salinity effects on soil P cycling

Citation

Hu, Minjie et al. (2022), Salinity effects on soil P cycling, Dryad, Dataset, https://doi.org/10.5061/dryad.41ns1rnj0

Abstract

Accelerated sea-level rise is expected to cause the salinization of freshwater wetlands, but the responses to salinity of the availability of soil phosphorus (P) and of microbial genes involved in the cycling and transformation of P remain unexplored. Our results suggest that the P-cycling microbial community abundance and P availability respond positively to moderate increases in salinity by promoting the microbial solubilization and mineralization of soil P in brackish wetlands. Changes in microbial communities and microbially mediated P cycling may represent microbial strategies to adapt to moderate salinity levels, which in turn control soil function and nutrient balance.

Methods

The field experiments were conducted in the growing (July) and non-growing seasons (January) in both the freshwater and brackish C. malaccensis wetlands. Three 1 × 1 m quadrats (5 m apart) were randomly established at each site, and three soil cores (0–20 cm) were randomly collected in each quadrat and pooled into one sample. All samples were then stored in a portable refrigerator and immediately transported to the laboratory. The samples were homogenized and then split into two subsamples: one subsample was air-dried for the determination of P fractions and physicochemical parameters, and the other subsample was frozen at −80°C for DNA extraction. Plant biomasses were also collected during each season.

We used the Hedley scheme of sequential extraction to estimate the fractions and availabilities of soil P (Hedley et al., 1982), which can effectively distinguish between Pi and Po. Briefly, soil samples were successively extracted using an anion-exchange resin (resin-P), 0.5 M NaHCO3 (NaHCO3-Pi and NaHCO3-Po), 0.1 M NaOH (NaOH-Pi and NaOH-Po), 0.1 M NaOH with sonication (NaOHs-Pi and NaOHs-Po), and 1 M HCl (HCl-Pi). The residual soils were then digested with 4 mL of H2SO4 and 1 mL of HClO4 (residual-P). The concentration of P was measured using a spectrophotometer. The P was further classified as labile P (resin-P, NaHCO3-Pi, and NaHCO3-Po), moderately labile P (NaOH-Pi and NaOH-Po), and stable P (NaOHs-Pi, NaOHs-Po, HCl-P, and residual-P) based on its availability to plants and microbes (Rodrigues et al., 2016).

The salinity of the water was measured in situ using a salinometer (Oakton Instruments, Springfield, USA). Soil electric conductivity (EC) and pH were determined using a 2265FS EC meter (Spectrum Technologies Inc., Aurora, USA) and a pH meter (IQ Scientific Instruments, Carlsbad, USA), respectively. Soil moisture was evaluated by determining the amount of water lost at 105°C. Soil organic C (SOC) was analyzed using the dichromate oxidation method. Soil concentrations of total C (TC) and N (TN) were measured using an elemental analyzer (Elementar, Frankfurt, Germany). Soil concentrations of ammonium-N (NH4+-N) and nitrate-N (NO3−-N) were determined using flow-injection analysis (Skalar Analytical SAN++, Lachat, Netherland) and extraction with 2 M KCl. The soil texture was determined using a Mastersizer 2000 particle-size analyzer (Malvern Panalytical Ltd., Melvin, UK). Plant biomasses were measured by drying samples to constant weight at 70°C.

Soil microbial DNA was extracted using an OMEGA DNA Kit following the manufacturer’s instructions. The quality and quantity of the extracted DNA were determined using a NanoDrop ND-1000 spectrophotometer (Thermo Fisher Scientific, Waltham, USA) and agarose gel electrophoresis, respectively. The extracted microbial DNA was processed, and metagenomic shotgun sequencing libraries were constructed with insert sizes of 400 bp using an Illumina TruSeq Nano DNA LT Library Preparation Kit. Each library was sequenced on an Illumina HiSeq X-ten platform (Illumina, San Diego, USA) using the PE150 strategy at Personal Biotechnology Co., Ltd. (Shanghai, China). Please refer to the Supporting Information for more detailed descriptions (Appendix I). We obtained a total of 931 million qualified sequences from 12 metagenomes, ranging from 69 million to 88 million sequences per sample for downstream analyses (Table S1).

Usage Notes

The dataset can be opened using regular Office software.

Funding

National Natural Science Foundation of China

Natural Science Foundation of Fujian Province

Fundación Ramón Areces Project

Spanish Government

Catalan Government