Accurately projecting the global carbon cycle requires Earth System Models (ESMs) to represent plant nutrient acquisition and associated carbon costs. However, most ESMs either neglect or oversimplify the role of mycorrhizal fungi, despite their key function in mediating plant-soil nutrient exchanges. Here, we integrate global satellite and field-based datasets on mycorrhizal distributions, soil nitrogen content, and carbon allocation to fungi to constrain nutrient acquisition costs in a land surface model, the Community Land Model (CLM). Incorporating these spatially explicit mycorrhizal costs reduces projected global carbon uptake by 15% over the 21st century. We find that mycorrhizal efficiency varies strongly by biome, with especially high carbon costs in boreal and semi-arid ecosystems. Model performance also improves by 5% in reproducing observed energy, water, and carbon fluxes. These results highlight the critical role of mycorrhizal symbioses in shaping ecosystem carbon balance and underscore the need to integrate fine-scale belowground data together with remote sensing into ESM frameworks for more accurate climate projections.