Impacts of Wetland Plants on Microbial Community and Methane Metabolisms

Aims Microbial activity in the soil of wetlands is responsible for the emission of more methane to the atmosphere than all other natural sources combined. This microbial activity is heavily impacted by plant roots, which influence the microbial community by exuding organic compounds and by leaking oxygen into an otherwise anoxic environment. This study compared the microbial communities of planted and unplanted wetland soil from an Alaskan bog to elucidate how plant growth influences populations and metabolisms of methanogens and methanotrophs. Methods A common boreal wetland sedge, Carex aquatilis, was grown in the laboratory and DNA samples were sequenced from the rhizosphere, unplanted bulk soil, and a simulated rhizosphere with oxygen input but no organic carbon. Results The abundance of both methanogens and methanotrophs were positively correlated with methane emissions. Among the methanotrophs, both aerobic and anaerobic methane oxidizing microbes were more common in the rhizosphere of mature plants than in unplanted soil, while facultative methanotrophs capable of utilizing either methane or other molecules became relatively less common. Conclusions These trends indicate that roots create an environment which favors highly specialized microbial metabolisms over generalist approaches. One aspect of this specialized microbiome is the presence of both aerobic and anaerobic metabolisms, which indicates that oxygen is present but is a limiting resource controlling competition.

Low methane emissions from a boreal wetland constructed on oil sand mine tailings

A 58 ha mixed upland and lowland boreal plains watershed called the Sandhill Fen Watershed was constructed between 2008 and 2012. In the years following wetting in 2013, methane emissions were measured using manual chambers. The presence of vegetation with aerenchymous tissues and saturated soils were important factors influencing the spatial variability of methane emissions across the constructed watershed. Nevertheless, median methane emissions were equal to or less than 0.51 mg CH4 m−2 h−1 even from the saturated organic soils in the lowlands. Although overall methane emissions remained low, observations of methane ebullition increased over the 3 study years. Ebullition events occurred in 10 % of measurements in 2013, increasing to 21 % and 27 % of measurements in 2014 and 2015, respectively, at the plots with saturated soils. Increasing metal ion availability and decreasing sulfur availability was measured using buried ion exchange resins at both seasonal and annual timescales potentially as a result of microbial reduction of these ions. Using principle component analysis, methane fluxes had a significant positive correlation to the leading principle component which was associated with increasing ammonium, iron, and manganese and decreasing sulfur availability (r=0.31, p<0.001). These results suggest that an abundance of alternative inorganic electron acceptors may be limiting methanogenesis at this time.

Low methane emissions from a boreal wetland constructed on oil sand mine tailings

A 58 hectare mixed upland and lowland boreal plains watershed called the Sandhill Fen Watershed was constructed between 2008 and 2012. In the years following wetting in 2013, methane emissions were measured using manual, static, non-steady state chambers. The presence of vegetation with aerenchymous tissues and saturated soils were important factors influencing the spatial variability of methane emissions across the constructed watershed. Nevertheless, median methane emissions were equal to or less than 0.51 mg CH4 m−2 h−1 even from the saturated organic soils in the lowlands. Although overall methane emissions remained low, observations of methane ebullition increased over the three study years. As a ratio to the total number of measurements, the number of ebullition events increased from 10 % in 2013 to 21 % and 27 % in 2014 and 2015, respectively at the plots with saturated soils. Increasing metal ion availability and decreasing sulphur availability was measured using buried ion exchange resins at both seasonal and annual timescales potentially as a result of microbial reduction of these ions. Methane fluxes significantly correlated with the leading Principal Component of ammonium, iron, manganese and sulphur availability (r = 0.31, p

SAR and Lidar Temporal Data Fusion Approaches to Boreal Wetland Ecosystem Monitoring

The objective of this study was to develop a decision-based methodology, focused on data fusion for wetland classification based on surface water hydroperiod and associated riparian (transitional area between aquatic and upland zones) vegetation community attributes. Multi-temporal, multi-mode data were examined from airborne Lidar (Teledyne Optech, Inc., Toronto, ON, Canada, Titan), synthetic aperture radar (Radarsat-2, single and quad polarization), and optical (SPOT) sensors with near-coincident acquisition dates. Results were compared with 31 field measurement points for six wetlands at riparian transition zones and surface water extents in the Utikuma Regional Study Area (URSA). The methodology was repeated in the Peace-Athabasca Delta (PAD) to determine the transferability of the methods to other boreal environments. Water mask frequency analysis showed accuracies of 93% to 97%, and kappa values of 0.8–0.9 when compared to optical data. Concordance results comparing the semi-permanent/permanent hydroperiod between 2015 and 2016 were found to be 98% similar, suggesting little change in wetland surface water extent between these two years. The results illustrate that the decision-based methodology and data fusion could be applied to a wide range of boreal wetland types and, so far, is not geographically limited. This provides a platform for land use permitting, reclamation monitoring, and wetland regulation in a region of rapid development and uncertainty due to climate change. The methodology offers an innovative time series-based boreal wetland classification approach using data fusion of multiple remote sensing data sources.