Straw ditch burial reshapes microbial communities and enhances yield and net ecosystem carbon balance in tropical pineapple system
Description
This dataset supports a three-year field experiment examining whether deep pineapple-straw burial improves productivity, carbon balance, soil carbon distribution, and microbial communities compared with conventional rotary straw incorporation in a tropical pineapple system. We hypothesized that burying straw at approximately 30 cm depth, combined with ridge planting and plastic film mulching, would improve root growth and photosynthetic carbon assimilation, alter the subsoil microbiome, and increase carbon retention in deeper soil layers. The dataset includes crop growth, root traits, photosynthetic parameters, fruit yield, CO₂, CH₄ and N₂O emissions, global warming potential, net ecosystem carbon balance (NECB), soil organic carbon (SOC), and subsoil microbial community data collected over two growing seasons. Greenhouse-gas fluxes were measured using static chambers. SOC was determined in the 0–100 cm soil layers. Microbial communities were characterized by high-throughput sequencing and analyzed for composition, predicted functions, ecological strategies, co-occurrence networks, and relationships with yield and SOC. Compared with rotary straw incorporation, ditch burial increased pineapple yield by 30.24%, cumulative CO₂ emissions by 24.39%, and NECB by 22.99%. After three years, SOC decreased by 42.37% in the 0–20 cm layer but increased by 6.39% in the 20–40 cm layer, indicating vertical SOC redistribution rather than confirmed whole-profile carbon sequestration. Deep straw burial also shifted the subsoil microbiome toward a K-strategy-dominated community, strengthened positive microbial associations, and increased predicted functions related to carbon degradation and ammonia oxidation. Pullulanibacillus, Haliangium, and Tumebacillus were positively associated with yield and SOC, although these relationships should not be interpreted as direct evidence of causality. The dataset can be used for residue-management comparisons, meta-analyses, carbon-balance modelling, and evaluation of climate-smart practices in tropical croplands. Users should consider treatment duration, soil depth, seasonal variation, experimental design, and measurement units when interpreting or reusing the data.
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Steps to reproduce
The dataset was generated from a three-year field experiment in a tropical pineapple cropping system using a randomized block design with replicated plots. Pineapple straw was applied at approximately 31 Mg ha⁻¹. The FSD treatment involved burying straw in 30-cm-deep ditches, followed by ridge planting and plastic-film mulching. In the FSR treatment, straw was incorporated into the surface soil by rotary tillage, with the same ridge planting and mulching practices. No-straw treatments were also included, while other field management practices were kept consistent. Crop growth, root traits, leaf photosynthesis and fruit yield were measured over two growing seasons. Yield was calculated from fruit mass harvested from each plot. CO₂, CH₄ and N₂O fluxes were measured using static closed chambers and gas chromatography. Cumulative emissions were obtained by integrating fluxes over time, and global warming potential was calculated as CO₂ equivalents. Net ecosystem carbon balance was estimated from the main carbon inputs and outputs within the defined field boundary. After three years, composite soil samples were collected from the 0–100 cm layers. Air-dried samples were used for soil physicochemical analyses, including soil organic carbon, while fresh subsoil samples were stored at low temperature for microbial analysis. Microbial DNA was extracted from subsoil, and bacterial communities were characterized by 16S rRNA gene amplicon sequencing. Sequence data were quality-filtered, taxonomically classified and used to assess diversity and community composition. Microbial functions were predicted from marker-gene data and should be interpreted as potential rather than directly measured activity. Co-occurrence networks were constructed from statistically supported relationships among abundant taxa to identify modules and core microorganisms. Treatment effects were assessed using the field plot as the experimental unit, mainly through analysis of variance, correlation, ordination and network analyses. Users should consider treatment, replicate, season, sampling date, soil depth and measurement unit when reusing the data.
Institutions
- Hainan UniversityHainan, Haikou
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Funders
- Natural Science Foundation of Hainan ProvinceGrant ID: 323RC424
- Key Research and Development Projects in Hainan ProvinceGrant ID: ZDYF2025XDNY064
- Collaborative Innovation Center Research Program of Hainan UniversityGrant ID: XTCX2022NYC18