To map net primary productivity (NPP) over the Canadian landmass at 1-km resolution.
A simulation model, the Boreal Ecosystem Productivity Simulator
(BEPS), has been developed. The model uses a sunlit and shaded leaf separation strategy and a daily integration scheme in order to implement an instantaneous leaf-level photosynthesis model over large areas. Two key driving variables, leaf area index
(every 10 days) and land cover type (annual), are derived from satellite measurements of the Advanced Very High Resolution Radiometer (AVHRR). Other spatially explicit input data are also prepared, including daily meteorological data (radiation,
precipitation, temperature, and humidity), available soil water holding capacity (AWC) and forest biomass. The model outputs are compared with ground plot data to ensure that no significant systematic biases are created.
simulation results show that Canada's annual net primary production was 1.22 Gt C year-1 in 1994, 78% attributed to forests, mainly the boreal forest, without considering the contribution of the understorey. The NPP averaged over the entire landmass
was ~140 g C m-2 year-1 in 1994. Geographically, NPP varied greatly among ecozones and provinces/territories. The seasonality of NPP is characterized by strong summer photosynthesis capacities and a short growing season in
Conclusions This study is the first attempt to simulate Canada-wide NPP with a process-based model at 1-km resolution and using a daily step. The statistics of NPP are therefore expected to be more accurate than
previous analyses at coarser spatial or temporal resolutions. The use of remote sensing data makes such simulations possible. BEPS is capable of integrating the effects of climate, vegetation, and soil on plant growth at a regional scale. BEPS and
its parameterization scheme and products can be a basis for future studies of the carbon cycle in mid-high latitude ecosystems.
Biogeochemical processes, boreal forest, Canada, ecological modelling, net primary productivity, remote
sensing, terrestrial carbon.