This thesis presents the first modeling study on long-term carbon dynamics for the University of Guelph Elora Agricultural Research Station and the Environment Canada Borden Forest Research Station at the daily and half-hourly time-step. The daily version of the CENTURY (DayCENT) model and the Carbon- and Nitrogen-coupled Canadian Land Surface Scheme (CN-CLASS) model were validated for quantifying the effects of agricultural management and component respiration on the carbon budget. DayCENT indicated that conventional tillage (CT) enhanced the annual heterotrophic respiration relative to no-till (NT) by 38.4, 93.7 and 64.2 g C m-2 yr-1 for corn, soybean and winter wheat, respectively. The seasonal variation of total soil organic carbon (SOC) pool was greater in CT than NT due to tillage effects on carbon transfer from the active surface SOC pool to the active soil SOC pool at a rate of 50-100 g C m-2 yr-1. NT accounted for a 10.7 g C m-2 yr-1 increase in the slow SOC pool (20-year turnover time) at a site in Elora, Ontario, Canada. I found that the plant phenology algorithms used in CN-CLASS were not constructed and validated for crop growth, resulting in a high degree of uncertainty in the simulations. Therefore, I designed and tested a new agricultural module for CN-CLASS. The regression analysis indicated that the new crop module improved the net ecosystem productivity (NEP) simulation for a cornfield, with the coefficient of determination (r2) of annual NEP increasing from 0.51 in the original CN-CLASS to 0.78 in the modified version of the model. I verified CN-CLASS to simulate the dynamics of component respiration for tracing the contributions from litterfall, SOC and root respiration in a deciduous mixedwood forest in Borden, Ontario, Canada. The model estimated that the annual ecosystem CO2 respiration was 1366 g C m-2 yr-1, contributed by heterotrophic respiration (57%), maintenance respiration (37%) and growth respiration (6%). The annual accumulated soil respiration was estimated at 782 g C m-2 yr-1, which was dominated by CO2 emissions from soil organic matter (60%). The base respiration rates required further verification based on field measurements. Based on the verified modeling approach in this thesis, the modeling core of DayCENT can be constructed as an integral platform for Agriculture and Agri-Food Canada National Carbon and Greenhouse Gas Accounting and Verification System. The crop phenological module in CN-CLASS allows us to conduct further agricultural studies concerning global carbon budget and environmental change. The validated respiration algorithms in CN-CLASS would be helpful in developing global biological CO2 transport model for tracing emission sources. / Natural Science and Engineering Research Council of Canada