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Abstract Arctic permafrost soils store vast amounts of carbon (C)‐rich organic matter that has accumulated due to low temperatures that suppress microbial decomposition. As Arctic warming intensifies, soil microbes become increasingly active, even while plant growth remains dormant. Seasonal decoupling between plant and microbial decomposer growth can accelerate carbon dioxide (CO₂) release from soils, however, most Earth system models underestimate cold‐season C emissions and do not accurately represent the freeze–thaw transitions that govern microbial access to substrates during these critical periods. These model–data mismatches often stem from empirical formulations, such as using a fixed Q₁₀functions to represent microbial respiration, an oversimplification of a complex interplay of temperature, moisture, and substrate diffusion. To address this, we incorporated explicit, temperature‐dependent diffusional constraints on microbial activity, (the Dual Arrhenius Michaelis–Menten (DAMM) model), into the Stoichiometrically Coupled Acclimating Microbe–Plant–Soil (SCAMPS) model which uses the Q₁₀function to represent microbial respiration. We used this enhanced model (SCAMPS_DAMM) to simulate Arctic ecosystem responses to a 50‐year winter warming scenario and compared outcomes to the original SCAMPS framework. While both models predicted overall soil C losses under warming, SCAMPS_DAMM produced more constrained increases in microbial respiration and plant productivity. These differences led to similar total ecosystem C declines but divergent patterns of C and N allocation between plant and soil pools. Thus, incorporating mechanistic constraints on microbial access to substrates through explicit representation of temperature and moisture controls altered model projections of Arctic biogeochemical responses to climate change.