Microbial strategy shifts drive seasonal reversal of litter decomposition in drylands across hydrothermal thresholds

Litter decomposition in arid regions is driven by seasonal microbial carbon (C) allocation trade‑offs and enzymatic stoichiometric strategies, yet synergistic regulation by precipitation and phosphorus (P) remains unclear. This 720-day study revealed the microbial mechanisms linking hydrothermal thresholds to seasonal decomposition asynchrony. Mass loss (31.07%–57.06%) depended strongly on the brief summer hydrothermal window. In summer, opportunistic taxa (e.g., Firmicutes , Bacillus ) were rapidly enriched, but structural equation modeling (SEM) revealed that the true functional hubs driving increases in β ‑1,4‑glucosidase (BG), leucine aminopeptidase (LAP), and C use efficiency (CUE) were Proteobacteria and bacterial Shannon diversity. These taxa adopted a "get‑then‑grow" strategy, accelerating decomposition and indicating a decoupling of community abundance from functional contribution. In winter, low temperature coupled with physiological drought triggered a widespread regulatory constraint. Dominant taxa shifted to stress‑tolerant groups, including Actinobacteria , Basidiomycota (e.g., Coprinellus , Schizophyllum ), and Psychrophilic yeasts (e.g., Mrakia , Filobasidium ). Actinobacteria became the functional hub driving a recalcitrant C mining strategy centered on polyphenol oxidase (PPO), with CUE turning negative and assimilated C shifting to intracellular storage. Compared to single-species litter, mixed-species litter decomposition exhibited a significant seasonal reversal. In summer, stoichiometric complementarity produced a synergistic effect (relative mixture effect (RME) > 8%). In winter, mixed-species litter sustained functional redundancy via enrichment of specific taxa (e.g., Ornithinimicrobium , Balneimonas ), yet high lignin content created a metabolic bottleneck. The WMP and WHP treatments shifted to significant antagonism (RME = − 12.48% and − 7.75%, respectively). Parameterizing arid‑region C cycling requires incorporating seasonal CUE, enzyme trade‑offs, and functional assembly into biogeochemical models.