Terrestrial photosynthesis is the largest flux of carbon between the atmosphere and the Earth’s surface and is 10 times greater than carbon emissions from fossil fuel burning and land use change combined. Photosynthesis also connects the carbon cycle to water and nutrient cycles. As such, it is important to reliably simulate photosynthetic processes to accurately project future global change. Photosynthesis in land surface models (LSMs) is dependent on photosynthetic capacity, which is closely coupled to the enzymatic content of plant leaves. Most LSMs parameterize photosynthetic capacity using plant functional type-specific parameters, while others simulate it using soil nutrient-dependent values of leaf nutrient content. However, recent theoretical developments suggest that photosynthetic capacity acclimates to optimize photosynthesis primarily to aboveground climate. A key tenet of this optimization is that photosynthesis is maximized at the lowest possible nutrient use to build photosynthetic enzymes, such as Rubisco. Quantifications of this theory offer a simpler, yet more dynamic formulation for LSMs. Here, we integrated this optimization theory into the E3SM LSM (ELM) and simulated future photosynthesis under the RCP 8.5 climate scenario. In our simulation, we found that optimal acclimation resulted in an increase in global photosynthesis in 2100 as compared to present day, primarily as a result of CO₂ fertilization. Interestingly, we also simulated a decrease in Rubisco-based nitrogen, which occurred in response to both elevated CO₂ and elevated temperature. While the increase in photosynthesis is commonly observed in other LSM simulations, the reduction in leaf nitrogen is not. This effect is likely to alter simulated carbon-nitrogen interactions, possibly even reducing simulated nitrogen limitation of future productivity.