Improved assessment of gross and net primary productivity of Canada's landmass

Abstract

[1] We assess Canada's gross primary productivity (GPP) and net primary productivity (NPP) using boreal ecosystem productivity simulator (BEPS) at 250 m spatial resolution with improved input parameter and driver fields and phenology and nutrient release parameterization schemes. BEPS is a process-based two-leaf enzyme kinetic terrestrial ecosystem model designed to simulate energy, water, and carbon (C) fluxes using spatial data sets of meteorology, remotely sensed land surface variables, soil properties, and photosynthesis and respiration rate parameters. Two improved key land surface variables, leaf area index (LAI) and land cover type, are derived at 250 m from Moderate Resolution Imaging Spectroradiometer sensor. For diagnostic error assessment, we use nine forest flux tower sites where all measured C flux, meteorology, and ancillary data sets are available. The errors due to input drivers and parameters are then independently corrected for Canada-wide GPP and NPP simulations. The optimized LAI use, for example, reduced the absolute bias in GPP from 20.7% to 1.1% for hourly BEPS simulations. Following the error diagnostics and corrections, daily GPP and NPP are simulated over Canada at 250 m spatial resolution, the highest resolution simulation yet for the country or any other comparable region. Total NPP (GPP) for Canada's land area was 1.27 (2.68) Pg C for 2008, with forests contributing 1.02 (2.2) Pg C. The annual comparisons between measured and simulated GPP show that the mean differences are not statistically significant ( p > 0.05, paired t test). The main BEPS simulation error sources are from the driver fields.

Implementation of a Marauding Insect Module (MIM, version 1.0) in the Integrated BIosphere Simulator (IBIS, version 2.6b4) dynamic vegetation–land surface model

“…Finally, although assessing IBIS was not the point of this study and has already been done elsewhere (Foley et al, 1996;Delire and Foley, 1999;Kucharik et al, 2000Kucharik et al, , 2006Lenters et al, 2000;El Maayar et al, 2001, the results obtained for the three grid cells compared favourably to recent studies, with a small underestimation of biomass (Beaudoin et al, 2014) and NPP (Gonsamo et al, 2013). Obtaining reliable data on soil carbon is notoriously difficult; when compared to the Harmonized World Soil Database (down to a depth of 1 m) as provided by Exbrayat et al (2014), IBIS apparently overestimated soil carbon (down to a depth of 4 m), at least in the southern grid cell, even when accounting for the fact that a substantial fraction of soil carbon is found at a depth greater than 1 m (Jobbágy and Jackson, 2000).…”

Data-driven diagnostics of terrestrial carbon dynamics over North America

“…Our GPP estimate for Canada's landmass is 45.6% higher than a recent estimate (2.68 Pg C yr −1 ) based on an ecosystem model (Gonsamo et al, 2013). Evergreen forests had the highest contribution to Canada's annual GPP, ER, and NEP; mixed forests, shrublands, and croplands had intermediate contributions; deciduous forests, savannas, and grasslands had the lowest values (Fig.…”

Comparison of Big‐Leaf, Two‐Big‐Leaf, and Two‐Leaf Upscaling Schemes for Evapotranspiration Estimation Using Coupled Carbon‐Water Modeling

“…Several intermodel comparisons and site‐level validations have shown that BEPS can produce reasonable GPP and ET estimates (Amthor et al, ; Grant et al, ; Liu et al, ; Potter et al, ). Its usage has expanded from boreal ecosystems to other plant functional types in the past decade (Chen et al, ; Gonsamo et al, ; Wang et al, ), and BEPS has been updated to support simulations at hourly and half‐hourly steps (Chen et al, ).…”