Abstract:Arctic tundra ecosystems are a major source of methane (CH 4 ), the variability of which is affected by local environmental and climatic factors, such as water table depth, microtopography, and the spatial heterogeneity of the vegetation communities present. There is a disconnect between the measurement scales for CH 4 fluxes, which can be measured with chambers at one-meter resolution and eddy covariance towers at 100-1000 m, whereas model estimates are typically made at thẽ 100 km scale. Therefore, it is critical to upscale site level measurements to the larger scale for model comparison. As vegetation has a critical role in explaining the variability of CH 4 fluxes across the tundra landscape, we tested whether remotely-sensed maps of vegetation could be used to upscale fluxes to larger scales. The objectives of this study are to compare four different methods for mapping and two methods for upscaling plot-level CH 4 emissions to the measurements from EC towers. We show that linear discriminant analysis (LDA) provides the most accurate representation of the tundra vegetation within the EC tower footprints (classification accuracies of between 65% and 88%). The upscaled CH 4 emissions using the areal fraction of the vegetation communities showed a positive correlation (between 0.57 and 0.81) with EC tower measurements, irrespective of the mapping method. The area-weighted footprint model outperformed the simple area-weighted method, achieving a correlation of 0.88 when using the vegetation map produced with the LDA classifier. These results suggest that the high spatial heterogeneity of the tundra vegetation has a strong impact on the flux, and variation indicates the potential impact of environmental or climatic parameters on the fluxes. Nonetheless, assimilating remotely-sensed vegetation maps of tundra in a footprint model was successful in upscaling fluxes across scales.

The Arctic is warming at twice the rate of the global mean. This warming could further stimulate methane (CH 4 ) emissions from northern wetlands and enhance the greenhouse impact of this region. Arctic wetlands are extremely heterogeneous in terms of geochemistry, vegetation, microtopography, and hydrology, and therefore CH 4 fluxes can differ dramatically within the metre scale. Eddy covariance (EC) is one of the most useful methods for estimating CH 4 fluxes in remote areas over long periods of time. However, when the areas sampled by these EC towers (i.e. tower footprints) are by definition very heterogeneous, due to encompassing a variety of environmental conditions and vegetation types, modelling environmental controls of CH 4 emissions becomes even more challenging, confounding efforts to reduce uncertainty in baseline CH 4 emissions from these landscapes. In this study, we evaluated the effect of footprint variability on CH 4 fluxes from two EC towers located in wetlands on the North Slope of Alaska. The local domain of each of these sites contains well developed polygonal tundra as well as a drained thermokarst lake basin. We found that the spatiotemporal variability of the footprint, has a significant influence on the observed CH 4 fluxes, contributing between 3% and 33% of the variance, depending on site, time period, and modelling method. Multiple indices were used to define spatial heterogeneity, and their explanatory power varied depending on site and season. Overall, the normalised difference water index had the most consistent explanatory power on CH 4 fluxes, though generally only when used in concert with at least one other spatial index. The spatial bias (defined here as the difference between the mean for the 0.36 km 2 domain around the tower and the footprint-weighted mean) was between |51|% and |18|% depending on the index. This study highlights the need for footprint modelling to infer the representativeness of the carbon fluxes measured by EC towers in these highly heterogeneous tundra ecosystems, and the need to evaluate spatial variability when upscaling EC site-level data to a larger domain.

Premise of research. In dioecious plant species, males and females often differ in physiology, and mycorrhizal fungal relationships are likely to influence these differences. However, few data are available on the potential role of mycorrhizal fungi in altering sex-specific physiology and population sex ratios of dioecious plant species. Methodology. In this study, we measured leaf gas exchange in a multifactorial greenhouse experiment with and without mycorrhizal fungal additions and under field conditions in Distichlis spicata, a dioecious C 4 salt marsh grass, displaying extreme spatial sex ratio variation. Pivotal results. We found a significant interaction between gas exchange, plant sex, and mycorrhizal fungal infection. Specifically, females but not males had significantly lower transpiration rates and higher water use efficiency (WUE) in treatments with increased mycorrhizal fungi. Additionally, field data showed similar WUE between plants at female-majority sites and male-majority sites, despite significantly lower rates of net assimilation and stomatal conductance in plants at female-majority sites. Conclusions. Our results suggest that the higher WUE associated with increased mycorrhizal fungi in female D. spicata plants may be an important physiological attribute enabling female success in the higher-stress saltwater environment contributing to the spatial segregation of the sexes observed in this dioecious species.