Bioorganic fertilizer (BOF), which integrates organic carbon sources, beneficial microorganisms, and essential nutrients, represents a distinctive approach to grassland restoration that differs fundamentally from conventional fertilization practices. Ecoenzymatic stoichiometry theory (EEST) provides a powerful framework for evaluating microbial nutrient limitation and carbon use efficiency (CUE) via analysis of the metabolic activities of extracellular enzymes involved in nutrient acquisition, supporting research on their responses to carbon-rich amendments and informing the optimization of restoration strategies.

In this study, we investigated the responses of microbial metabolic limitations and CUE to different ecological restoration measures: bioorganic fertilizer (BOF), microbial fertilizer (MF), and super absorbent polymers (SAP), and a natural restoration control (CK). We quantified microbial metabolic limitation using three soil enzyme stoichiometry models (vector, vector-threshold (V-T), and threshold models), calculated microbial CUE across all treatments, and examined the regulatory effects of environmental factors on both microbial metabolic nutrient limitations and CUE.

Different restoration measures significantly affected soil physicochemical properties, microbial biomass, extracellular enzyme activities, and their stoichiometric characteristics. All three restoration measures altered stoichiometric imbalance: compared with CK, BOF, MF, and SAP treatments exhibited higher C:N imbalance but lower C:P and N:P imbalances. All three models consistently indicated the absence of soil microbial N limitation across all restoration measures, while confirming the presence of C and P limitations. Both vector and V-T models showed that BOF alleviated C limitations with no significant differences in P limitations among treatments, whereas the threshold model revealed that BOF relieved C limitations but exacerbated P limitations. Additionally, BOF improved CUE. Main factors that influenced C and P limitation were soil available resources. Meanwhile, soil microbial biomass was the main factor influencing CUE. This study demonstrates the utility of ecoenzymatic stoichiometry theory (EEST) in elucidating microbial resource ecology in degraded desert grasslands, providing a basis for targeted restoration measures in degraded ecosystems.