Land carbon sensitivity to atmospheric CO2 concentration (βL) and climate warming (γL) is a crucial part of carbon-climate feedbacks that affect the magnitude of future warming. Although these sensitivities can be estimated by earth system models, their dependence on model representation of land carbon dynamics and the inherent model assumptions has rarely been investigated. Using the widely used Community Land Model version 4 as an example, we examine how βL and γL vary with prescribed versus dynamic vegetation covers. Both sensitivities are found to be larger with dynamic compared to prescribed vegetation on decadal timescale in the late twentieth century, with a more robust difference in γL. The latter is a result of dynamic vegetation model deficiencies in representing the competitions between deciduous versus evergreen trees and tree versus grass over the tropics and subtropics. The biased vegetation cover changes the regional characteristics of carbon-nitrogen cycles such that plant productivity responds less strongly to the enhancement of nitrogen mineralization with warming, so more carbon is lost to the atmosphere with rising temperature. The result calls for systematic evaluations of land carbon sensitivities with varying assumptions for land cover representations to help prioritize development effort and constrain uncertainties in carbon-climate feedbacks.