Search

Climate change in the Arctic is leading to shifts in vegetation communities, permafrost degradation and alteration of tundra surface–atmosphere energy and carbon (C) fluxes, among other changes. However, year-round C and energy flux measurements at high-latitude sites remain rare. This poses a challenge for evaluating the impacts of climate change on Arctic tundra ecosystems and for developing and evaluating process-based models, which may be used to predict regional and global energy and C feedbacks to the climate system. Our study used 14 years of seasonal eddy covariance (EC) measurements of carbon dioxide (CO 2), water and energy fluxes, and winter soil chamber CO 2 flux measurements at a dwarf-shrub tundra site underlain by continuous permafrost in Canada's Southern Arctic ecozone to evaluate the incorporation of shrub plant functional types (PFTs) in the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC), the land surface component of the Canadian Earth System Model. In addition to new PFTs, a modification of the efficiency with which water evaporates from the ground surface was applied. This modification addressed a high ground evaporation bias that reduced model performance when soils became very dry, limited heat flow into the ground, and reduced plant productivity through water stress effects. Compared to the grass and tree PFTs previously used by CLASSIC to represent the vegetation in Arctic permafrost-affected regions, simulations with the new shrub PFTs better capture the physical and biogeochemical impact of shrubs on the magnitude and seasonality of energy and CO 2 fluxes at the dwarf-shrub tundra evaluation site. The revised model, however, tends to overestimate gross primary productivity, particularly in spring, and overestimated late-winter CO 2 emissions. On average, annual net ecosystem CO 2 exchange was positive for all simulations, suggesting this site was a net CO 2 source of 18 ± 4 g C m -2 yr -1 using shrub PFTs, 15 ± 6 g C m -2 yr -1 using grass PFTs, and 25 ± 5 g C m -2 yr -1 using tree PFTs. These results highlight the importance of using appropriate PFTs in process-based models to simulate current and future Arctic surface–atmosphere interactions. [ABSTRACT FROM AUTHOR]

Small farm reservoirs are abundant in many agricultural regions across the globe and have the potential to be large contributing sources of carbon dioxide (CO2) and methane (CH4) to agricultural landscapes. Compared to natural ponds, these artificial waterbodies remain overlooked in both agricultural greenhouse gas (GHG) inventories and inland water global carbon (C) budgets. Improved understanding of the environmental controls of C emissions from farm reservoirs is required to address and manage their potential importance in agricultural GHG budgets. Here, we conducted a regional-scale survey (∼ 235 000 km 2) to measure CO2 and CH4 surface concentrations and diffusive fluxes across 101 small farm reservoirs in Canada's largest agricultural area. A combination of abiotic, biotic, hydromorphologic, and landscape variables were modelled using generalized additive models (GAMs) to identify regulatory mechanisms. We found that CO2 concentration was estimated by a combination of internal metabolism and groundwater-derived alkalinity (66.5 % deviance explained), while multiple lines of evidence support a positive association between eutrophication and CH4 production (74.1 % deviance explained). Fluxes ranged from -21 to 466 and 0.14 to 92 mmol m -2 d -1 for CO2 and CH4 , respectively, with CH4 contributing an average of 74 % of CO2 -equivalent (CO2 -e) emissions based on a 100-year radiative forcing. Approximately 8 % of farm reservoirs were found to be net CO2 -e sinks. From our models, we show that the GHG impact of farm reservoirs can be greatly minimized with overall improvements in water quality and consideration to position and hydrology within the landscape. [ABSTRACT FROM AUTHOR]