Tropical forest degradation from logging, fire, and fragmentation not only alters carbon stocks and carbon fluxes, but also impacts physical land-surface properties such as albedo and roughness length. Such impacts are poorly quantified to date due to difficulties in accessing and maintaining observational infrastructures, and the lack of proper modeling tools for capturing the interactions among biophysical properties, ecosystem demography, and biogeochemical cycling in tropical forests. As a first step to address these limitations, we implemented a selective logging module into the Functional Assembled Terrestrial Ecosystem Simulator (FATES) and parameterized the model to reproduce the selective logging experiment at the Tapajos National Forest in Brazil. The model was spun up until it reached the steady state, and simulations with and without logging were compared with the eddy covariance flux towers located at the logged and intact sites. The sensitivity of simulated water, energy, and carbon fluxes to key plant functional traits (e.g. Vcmax and leaf longevity) were quantified by perturbing their values within their documented ranges. Our results suggest that the model can reproduce water and carbon fluxes in intact forests, although sensible heat fluxes were overestimated. The effects of logging intensity and techniques on fluxes were assessed by specifying different disturbance parameters in the models (e.g., size-dependent mortality rates associated with timber harvest, collateral damage, and mechanical damage for infrastructure construction). The model projections suggest that even though the degraded forests rapidly recover water and energy fluxes compared with old-growth forests, the recovery times for carbon stocks, forest structure and composition are much longer. In addition, the simulated recovery trajectories are highly dependent on choices of values for functional traits. Our study highlights the advantages of an Earth system modeling approach, constrained by observations, to quantify the complex interactions among forest degradation, ecosystem recovery, climate, and environmental factors. Our results also show the urgent need to improve the representations of key mechanisms and traits to better capture forest degradation dynamics in Earth System Models.