DOI: 10.5061/dryad.nvx0k6f21
title: Reconciling plant and microbial ecological strategies to elucidate cover crop effects on soil carbon and nitrogen cycling

description: Plant economics, the way plants allocate and utilize resources, affect
 multiple soil processes through interactions with root and associated
 microbial communities. However, the interplay between plant economics and
 microbial ecological strategies remains poorly understood, which is
 crucial for integrated manipulation of plant- and microbe-mediated
 functions in mitigating climate change and sustaining soil health. We used
 a field experiment with 11 cover crop species grown monocultures in the
 same base soil to test whether microbial ecological strategies are
 associated with plant economic strategies and if their interactions are
 linked to soil functions. A principal component analysis (PCA) was
 performed on root and leaf traits to identify the loadings of cover crop
 species on the plant trait space. Metagenomic analysis of rhizosphere
 microbial communities was conducted to infer their ecological strategies
 based on genetically encoded community-aggregated traits. We found a
 synchronous relationship between the conservation gradient of plant
 economic strategies and the trade-offs in microbial ecological strategies.
 Conservative plant strategists, such as Lolium multiflorum,
 Triticum turgidum, and Brassica juncea, fostered microbial communities
 characterized by high growth yield potentials (Y-strategies). This
 included increased microbial carbon fixation pathways, citrate cycle,
 ribosome, and valine, leucine and isoleucine biosynthesis. As a result,
 microbial metabolic efficiency improved, shown by higher microbial biomass
 carbon content and a lower metabolic quotient (qCO2), led to enhanced soil
 organic carbon accumulation. In comparison, acquisitive plants like
 Astragalus sinicus, Vicia villosa, Trifolium incarnatum, and Medicago
 sativa stimulated microbial resource-acquisition strategies
 (A-strategies). This included enhanced bacterial chemotaxis, secretion
 systems, biotin metabolism, and cell motility pathways, which in turn
 increased soil exoenzyme activity and accelerated soil nitrogen
 mineralization. Consequently, these species enhanced soil nitrogen
 availability and had substantial feedbacks on subsequent main crop
 productivity. Synthesis. This study demonstrates how plant economic
 strategies influence the balance between different microbial ecological
 strategies, specifically the trade-offs in Y- and A-strategies. These
 interactions exert control over carbon and nitrogen dynamics in the soil
 ecosystem. Our findings provide the insights for implementing nature-based
 solutions to improve agroecosystem management practices.
description: # Reconciling plant and microbial ecological strategies to elucidate cover
 crop effects on soil carbon and nitrogen cycling
 [https://doi.org/10.5061/dryad.nvx0k6f21](https://doi.org/10.5061/dryad.nvx0k6f21) ## Description of the data and file structure ### Files and variables #### File: Plant\_species\_PCA\_scores.csv ##### Variables * Group: The identity of the plant species * Sample: The sample ID for each plant species * pc1: The first dimension of the plant trait space (PCA axis 1) * pc2: The second dimension of the plant trait space (PCA axis 2) #### File: Soil\_variables.csv ##### Variables * Group: The identity of the plant species * Sample: The sample ID for each plant species * NH4: Soil NH4+-N content (mg N kg−1 dry soil) * NO3: Soil NO3--N content (mg N kg−1 dry soil) * DOC: Soil dissolved organic carbon content (mg C kg−1 dry soil) * Nmin: Soil net N mineralization rates (mg N kg-1 dry soil h-1) * SWC: Soil water content (%) * MBC: Microbial biomass carbon content (mg C kg−1 dry soil) * BR: Soil basal respiration (mg CO2−C g−1 dry soil h−1) * qCO2: Microbial metabolic quotient (mg CO2-C mg-1 MBC h-1) * SOC: Soil organic carbon content (g C kg−1 dry soil) * MainCropYield: The yield of main crop maize (kg m-2) * AG: Soil α-1,4-glucosidase activity (nmol h−1 g−1 dry soil) * BG: Soil β-1,4-glucosidase activity (nmol h−1 g−1 dry soil) * CB: Soil cellobiohydrolase activity (nmol h−1 g−1 dry soil) * LAP: Soil leucine aminopeptidase activity (nmol h−1 g−1 dry soil) * NAG: Soil N-acetyl-β-D-glucosaminidase activity (nmol h−1 g−1 dry soil) * XYL: Soil β-xylosidase activity (nmol h−1 g−1 dry soil) #### File: plant\_traits.xlsx ##### Variables * Group: The identity of the plant species * Sample: The sample ID for each plant species * LDMC: Leaf dry matter content (mg mg-1) * SLA: Specific leaf area (mm2 mg-1) * LNC: leaf N content (mg g-1) * LeafCN: Leaf carbon to nitrogen ratio (%) * SRL: Specific root length (cm g-1) * RTD: Root tissue density (g cm-3) * RD: Mean root diameter (mm) * RNC: Root N content (mg g-1) * RDMC: Root dry matter content (mg mg-1) * RootCN: Root carbon to nitrogen ratio (%) * ExudationC: Root carbon exudation rates (nmol C g-1 root DW-1 h-1) * RBI: Root branching intensity (tips cm-1) #### File: Microbial\_strategies.csv ##### Variables * Group: The identity of the plant species * Sample: The sample ID for each plant species - Y: High growth yield strategy - A: Resource acquisition strategy - S: Stress tolerance strategy - A.Y: The ratio of A strategy to Y strategy #### File: Taxonomic\_composition.csv ##### Variables * Group: The identity of the plant species - Sample: The sample ID for each plant species #### File: Functional\_composition.csv ##### Variables * Group: The identity of the plant species - Sample: The sample ID for each plant species - KO: KEGG Orthology #### File: YAS\_kegg\_L3\_traits.csv ##### Variables * Group: The identity of the plant species - Sample: The sample ID for each plant species - Y_: Microbial high growth yield trait - A_: Microbial resource acquisition trait - S_: Microbial stress tolerance trait ###