While most land models developed for use with climate models represent vegetation as discrete biomes, this is, at least for mixed life-form biomes, inconsistent with the leaf-level and whole-plant physiological parameterizations needed to couple these biogeophysical models with biogeochemical and ecosystem dynamics models. In this paper, we present simulations with the National Center for Atmospheric Research land surface model (NCAR LSM) that examined the effect of representing vegetation as patches of plant functional types (PFTs) that coexist within a model grid cell. This approach is consistent with ecological theory and models and allows for unified treatment of vegetation in climate and ecosystem models. In the standard NCAR LSM the PFT composition and leaf area for each grid cell are obtained by classifying grid cells as 1 of 28 possible biomes. Here, we develop a data set from 1-km satellite data that provides each model grid cell a unique PFT composition and leaf area for each PFT. Global simulations at 3° × 3° spatial resolution showed that ground temperature, ground evaporation, and northern high-latitude winter albedo exhibited direct responses to these landscape changes, which led to indirect effects such as in soil moisture and sensible and latent heat fluxes. Additional simulations at 2° × 2° and 1° × 1° spatial resolution showed that low-resolution simulations masked landscape heterogeneity in both approaches but the satellite-based, continuous representation of vegetation reduced model sensitivity to resolution. It is argued that the use of spatially continuous distributions of coexisting PFTs is a necessary step to link climate and ecosystem models.