## Methods
### GCM-Simulated Forest Productivity Estimates  
Besides commonly used projections of temperature and precipitation, GCMs provide a number of carbon-related outputs. Photosynthetic carbon assimilation is expressed as gross primary production (GPP) and this assimilated carbon is used as a source of energy for trees to grow [23]. Plant biomass accumulation is represented by NPP, which is calculated as GPP minus carbon losses through respiration from live plant components or autotrophic respiration [23; 24]. The net accumulation of carbon by an ecosystem is represented by NEP, which is the difference between NPP and carbon loss through decomposition of dead organic matter or heterotrophic respiration [20]. NEP is often used to estimate carbon sequestration for a given area and time period, assuming disturbance or dissolved organic carbon related losses are negligible. Note that these carbon-related GCM outputs incorporate the projected impact of increased levels of atmospheric carbon (i.e., CO\({}_{2}\) fertilization) on plant growth and respiration.  
As previously noted, estimates of NPP and NEP were downloaded for three GCMs (i.e., CanESM2, MIROC, and MPI-ESM). (i) The Canadian Earth System Model (CanESM2) includes a fourth generation atmospheric general circulation model (CanCM4), a physical ocean component (OGCM4), the Canadian Model of Ocean Carbon (CMOC) and a process-based dynamic vegetation model, known as the Canada Terrestrial Ecosystem Model (CTEM) [25; 26]. Model simulations were performed at a rather  
Figure 1: Location of study are in North America and the Province of Ontario in Canada. Grid sizes are based on the resolution of global climate model outputs for (**a**) CanESM2 and MIROC (\(\sim\)2.8\({}^{\circ}\)) and (**b**) MPI-ESM (\(\sim\)2.5\({}^{\circ}\)).  
coarse resolution of 2.8\({}^{\circ}\)\(\times\) 2.8\({}^{\circ}\) (Figure 1a); (ii) The Japanese Model for Interdisciplinary Research on Climate (MIROC) consists of an atmospheric general circulation model (MIROC-AGCM), an aerosol component (SPRINTARS v5), an ocean GCM with sea-ice components (COCO v3.4), and a land surface model (MATSIRO) [27]. MIROC shares the same spatial resolution as CanESM2 (Figure 1a); (iii) The German Max-Planck-Institute-Earth System Model (MPI-ESM) consists of an atmospheric general circulation model (ECHAM6), an ocean model (MPIOM), marine geochemistry model (HAMOCC5), and a dynamic vegetation model describing physical and biogeochemical aspects of soil and vegetation (JSBACH) [28; 29]. The spatial resolution of the MPI outputs is 2.5\({}^{\circ}\)\(\times\) 2.5\({}^{\circ}\) (Figure 1b).  
Simulations performed by all three models used a common experimental protocol prepared for CMIP5 participating models [30]. This protocol included carbon fluxes from natural vegetation and soil as well as some measure of disturbance such as land use change. Performance of these models in simulating carbon fluxes and related components for historical (1850-2005) and future (2006-2100) time periods has been evaluated previously using a moderate greenhouse gas emission scenario, i.e., Representative Concentration Pathway 4.5 (RCP 4.5) [31]. Here, we employ a high emission scenario, RCP 8.5, as emissions are currently tracking at or above this level [32].