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Studies in recent decades have shown strong evidence of physical and biological changes in the Arctic tundra, largely in response to rapid rates of warming. Given the important implications of these changes for ecosystem services, hydrology, surface energy balance, carbon budgets, and climate feedbacks, research on the trends and patterns of these changes is becoming increasingly important and can help better constrain estimates of local, regional, and global impacts as well as inform mitigation and adaptation strategies. Despite this great need, scientific understanding of tundra ecology and change remains limited, largely due to the inaccessibility of this region and less intensive studies compared to other terrestrial biomes. A synthesis of existing datasets from past field studies can make field data more accessible and open up possibilities for collaborative research as well as for investigating and informing future studies. Here, we synthesize field datasets of vegetation and active-layer properties from the Alaskan tundra, one of the most well-studied tundra regions. Given the potentially increasing intensive fire regimes in the tundra, fire history and severity attributes have been added to data points where available. The resulting database is a resource that future investigators can employ to analyze spatial and temporal patterns in soil, vegetation, and fire disturbance-related environmental variables across the Alaskan tundra. This database, titled the Synthesized Alaskan Tundra Field Database (SATFiD), can be accessed at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) for Biogeochemical Dynamics (Chen et al., 2023: 10.3334/ORNLDAAC/2177). [ABSTRACT FROM AUTHOR]

Arctic tundra largely in response to exceptionally rapid rates of warming. Given the important implications of these changes on ecosystem services, hydrology, surface energy balance, carbon budgets, and climate feedbacks, research on the trends and patterns of these changes is becoming increasingly important and can help better constrain estimates of local, regional, and global impacts as well as inform mitigation and adaptation strategies. Despite this high need, scientific understanding of tundra ecology and change remains limited largely due to the inaccessibility of this region and less intensive study compared to other terrestrial biomes. A synthesis of existing datasets from past field studies can make field data more accessible and open up possibilities for collaborative research as well as for investigating and informing future studies. Here, we synthesize field datasets of vegetation, and active layer properties from the Alaskan tundra, one of the most well-studied tundra regions. Given the potential increasingly intensive fire regimes in the tundra, fire history and severity attributes have been added to data points where available. The resulting database is a resource that future investigators can employ to analyze spatial and temporal patterns in soil, vegetation, and fire disturbance-related environmental variables across the Alaskan tundra. This database, titled Synthesized Alaskan Tundra Field Database (SATFiD), can be accessed at the Oak Ridge National Laboratory Distributed Active Archive Center (ORNL DAAC) for Biogeochemical Dynamics (Chen et al., 2023: https://doi.org/10.3334/ORNLDAAC/2177). [ABSTRACT FROM AUTHOR]

Boreal peatlands represent a globally important store of carbon, and disturbances such as wildfire can have a negative feedback to the climate. Understanding how carbon exchange and greenhouse gas (GHG) dynamics are impacted after a wildfire is important, especially as boreal peatlands may be vulnerable to changes in wildfire regime under a rapidly changing climate. Yet, given this vulnerability, there is very little in the literature on the impact such fires have on methane (CH4) emissions. This study investigated the effect of wildfire on CH4 emissions at a boreal fen near Fort McMurray, AB, Canada, that was partially burned by the Horse River Wildfire in 2016. We measured CH4 emissions and environmental variables (2017-2018) and CH4 production potential (2018) in two different microform types (hummocks and hollows) across a burn severity gradient (unburned (UB), moderately burned (MB) and severely burned (SB)). Results indicated a switch in the typical understanding of boreal peatland CH4 emissions. For example, emissions were much lower in the MB and SB hollows in both years compared to UB hollows. Interestingly, across the burned sites, hummocks had higher fluxes in 2017 than hollows at the MB and SB sites. We found typically higher emissions at the UB site where the water table was close to the surface. However, at the burned sites, no relationship was found between CH4 emissions and water table, even under similar hydrological conditions. This further strengthens the argument on the overriding influence of fire. There was also significantly higher CH4 production potential from the UB site than the burned sites. The reduction in CH4 emissions and production in the hollows at burned sites highlights the sensitivity of hollows to fire, removing labile organic material for potential methanogenesis. The previously demonstrated resistance of hummocks to fire also results in limited impact to CH4 emissions and likely faster recovery to pre-fire rates. Given the potential initial net cooling effect resulting from a reduction in CH4 emissions, it is important that the radiative effect of all GHG following wildfire across peatlands is taken into account. [ABSTRACT FROM AUTHOR]

Arctic tundra ecosystems are a major source of methane (CH4), 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 CH4 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 the ∼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 CH4 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 CH4 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 CH4 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. [ABSTRACT FROM AUTHOR]

The Arctic is currently undergoing intense changes in climate; vegetation composition and productivity are expected to respond to such changes. To understand the impacts of climate change on the function of Arctic tundra ecosystems within the global carbon cycle, it is crucial to improve the understanding of vegetation distribution and heterogeneity at multiple scales. Information detailing the fine-scale spatial distribution of tundra communities provided by high resolution vegetation mapping, is needed to understand the relative contributions of and relationships between single vegetation community measurements of greenhouse gas fluxes (e.g., ∼1 m chamber flux) and those encompassing multiple vegetation communities (e.g., ∼300 m eddy covariance measurements). The objectives of this study were: (1) to determine whether dominant Arctic tundra vegetation communities found in different locations are spectrally distinct and distinguishable using field spectroscopy methods; and (2) to test which combination of raw reflectance and vegetation indices retrieved from field and satellite data resulted in accurate vegetation maps and whether these were transferable across locations to develop a systematic method to map dominant vegetation communities within larger eddy covariance tower footprints distributed along a 300 km transect in northern Alaska. We showed vegetation community separability primarily in the 450-510 nm, 630-690 nm and 705-745 nm regions of the spectrum with the field spectroscopy data. This is line with the different traits of these arctic tundra communities, with the drier, often non-vascular plant dominated communities having much higher reflectance in the 450-510 nm and 630-690 nm regions due to the lack of photosynthetic material, whereas the low reflectance values of the vascular plant dominated communities highlight the strong light absorption found here. High classification accuracies of 92% to 96% were achieved using linear discriminant analysis with raw and rescaled spectroscopy reflectance data and derived vegetation indices. However, lower classification accuracies (∼70%) resulted when using the coarser 2.0 m WorldView-2 data inputs. The results from this study suggest that tundra vegetation communities are separable using plot-level spectroscopy with hand-held sensors. These results also show that tundra vegetation mapping can be scaled from the plot level (<1 m) to patch level (<500 m) using spectroscopy data rescaled to match the wavebands of the multispectral satellite remote sensing. We find that developing a consistent method for classification of vegetation communities across the flux tower sites is a challenging process, given the spatial variability in vegetation communities and the need for detailed vegetation survey data for training and validating classification algorithms. This study highlights the benefits of using fine-scale field spectroscopy measurements to obtain tundra vegetation classifications for landscape analyses and use in carbon flux scaling studies. Improved understanding of tundra vegetation distributions will also provide necessary insight into the ecological processes driving plant community assemblages in Arctic environments. [ABSTRACT FROM AUTHOR]

Boreal peatlands represent a globally important store of carbon, and disturbances such aswildfire can have a significant positive feedback to the climate. Understanding how carboncycling and greenhouse gas (GHG) dynamics are impacted after a wildfire is important,especially as boreal peatlands may be vulnerable to changes in wildfire regime under arapidly changing climate. Yet given this vulnerability, there is very little in the literature onthe impact such fires have on methane (CH4) emissions. This study investigated the effect of wildfire on CH4 emissions at a boreal fen near FortMcMurray, AB, Canada, partially burned by the Horse River Wildfire in 2016. We measuredCH4 emissions and environmental variables (2017-2018) and CH4 production potential(2018) in two different microform types (hummocks and hollows) across a burnseverity gradient (unburned (UB), moderately burned (MB) and severely burned(SB)). The average CH4 flux at the UB hollows was 96.5 and 66.6 mg CH4 m−2 d−1in 2017 and2018, respectively. Methane emissions were much lower in the MB and SB hollows in bothyears, with the average flux being 0.25 and 0.06 mg CH4 m−2d−1 in 2017 and 1.93 and 1.38mg CH4m−2 d−1, respectively. Interestingly, across the burned sites, hummocks had higherfluxes in 2017 than hollows with the average flux being 1.82 and 5.83 mg CH4m−2 d−1 at theMB and SB sites, respectively. Results of a linear mixed effects model (LMM) illustrate thereis a significant effect of burn severity on CH4 flux, although no significant difference betweenmicroform or year. Another LMM found a significant interaction between burnseverity and both soil temperature at 30 cm depth and water table. There was alsosignificantly higher CH4 production potential from the UB site than the burnedsites. The reduction in CH4 emissions and production in the hollows at burned sites highlightsthe sensitivity of hollows to fire, removing labile organic material for potentialmethanogenesis. The previously demonstrated resilience of hummocks to fire also results inlimited impact to methane emissions and likely faster recovery to pre-fire rates. [ABSTRACT FROM AUTHOR]