Trade-Offs and Driving Factors of Microbial Carbon and Nitrogen Use Efficiency in Typical Forest Ecosystems of Funiu Mountain

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

Soil microbial carbon use efficiency (CUE) and nitrogen use efficiency (NUE) are fundamental parameters governing organic matter turnover in terrestrial ecosystems, yet how forest type-driven variation in litter quality propagates through the litter–soil–microbe continuum to regulate these efficiencies remains poorly resolved. Across three forest types in the Funiu Mountains, central China—a Larix gmelinii (LG) plantation, a Quercus aliena var. acuteserrata (QA) secondary forest, and a mixed Quercus aliena var. acutiserrata and Pinus armandii (QP) forest—we quantified litter chemistry, soil physicochemical properties, microbial biomass, extracellular enzyme activities, and microbial nutrient use efficiencies (MUE: NUE, and phosphorus use efficiency, PUE) derived from a modified saturation kinetics model. Principal coordinate analysis revealed significant multivariate differentiation among forest types across litter, soil, microbial biomass, and enzyme modules (Adonis R2 = 0.198–0.427; all p < 0.05). Compared with LG and QA, QP exhibited a pronounced stoichiometric imbalance: it supported the highest litter organic carbon and total nitrogen, the lowest lignin-to-cellulose ratio, the largest soil C and N pools (SOC and STN), and the greatest microbial biomass carbon (MBC). However, despite this resource-rich environment, microbial biomass C:N:P ratios exhibited constrained variation, while soil C:P (SCP) and N:P ratios (SNP) in QP reached extreme values (112.3 and 7.25, respectively), generating severe stoichiometric imbalance. Vector analysis indicated that all forests were under relative nitrogen limitation (vector angle < 45°), with QP showing the strongest limitation (41.6 ± 0.4°). Critically, QP exhibited the highest NUE (0.47 ± 0.03) but the lowest CUE (0.95 ± 0.01), and CUE and NUE were nearly perfectly negatively correlated across all sites (R = −0.98, p < 0.001). Random forest analysis identified extracellular enzyme stoichiometry as the dominant proximate predictor of MUE. Partial least squares structural equation modeling (GOF = 0.673–0.674; R2 = 0.592–0.603) revealed that litter and soil properties had no significant direct effects on CUE or NUE; instead, soil nutrients exerted strong indirect association through a cascade—soil → microbial biomass → enzyme activity—with opposite total effects on CUE (−0.731, p < 0.001) versus NUE (+0.755, p < 0.001). These findings reveal that the same soil nutrient enrichment that accompanies mixed-species afforestation drives divergent microbial metabolic responses—suppressing CUE while promoting NUE—through a shared cascading structure, with implications for predicting soil carbon and nutrient retention under shifting forest compositions.

• openalex https://doi.org/10.3390/microorganisms14071580first seen 2026-07-22 04:57:40