Methane (CH4) emissions from Arctic tundra are an important feedback to global climate. Currently, modelling and predicting CH4 fluxes at broader scales are limited by the challenge of upscaling plot-scale measurements in spatially heterogeneous landscapes, and by uncertainties regarding key controls of CH4 emissions. In this study, CH4 and CO2 fluxes were measured together with a range of environmental variables and detailed vegetation analysis at four sites spanning 300 km latitude from Barrow to Ivotuk (Alaska). We used multiple regression modelling to identify drivers of CH4 flux, and to examine relationships between gross primary productivity (GPP), dissolved organic carbon (DOC) and CH4 fluxes. We found that a highly simplified vegetation classification consisting of just three vegetation types (wet sedge, tussock sedge and other) explained 54% of the variation in CH4 fluxes across the entire transect, performing almost as well as a more complex model including water table, sedge height and soil moisture (explaining 58% of the variation in CH4 fluxes). Substantial CH4 emissions were recorded from tussock sedges in locations even when the water table was lower than 40 cm below the surface, demonstrating the importance of plant-mediated transport. We also found no relationship between instantaneous GPP and CH4 fluxes, suggesting that models should be cautious in assuming a direct relationship between primary production and CH4 emissions. Our findings demonstrate the importance of vegetation as an integrator of processes controlling CH4 emissions in Arctic ecosystems, and provide a simplified framework for upscaling plot scale CH4 flux measurements from Arctic ecosystems.
Abstract The Western Boreal Plain (WBP) comprises a diverse array of wetland types; however, swamps are understudied in the WBP relative to other wetlands, despite their ubiquity. We apply an ecohydrological and GIS‐based research approach at a fen–swamp complex in the WBP to characterize the ecohydrological properties of the varying wetland types and relate these interactions to the hydrologic function of the watershed. In this study, we evaluate 3 years of hydrological monitoring data, with additional hydrochemical, vegetation and remote sensing data. In our analyses, we identified five land types: fen, flat peat swamp and peat margin swamp (peatlands), mineral swamp and upland. Flat peat swamp was distinguished from fen using Ducks Unlimited criteria, stating fens cannot have trees >10 m in height. Little difference in water table variability, groundwater connectivity, vegetation composition and water chemistry were found between flat peat swamp and fen, suggesting that for all practical purposes, they can be considered a single unit and tree height alone cannot be used to differentiate these peatland types. In contrast, peat margin swamps exhibited lower and more variable water tables and consistent downward hydraulic gradients and comprised a mixture of peatland and upland vegetation. Peat margin swamps, however, exhibited similar porewater pH, electrical conductivity and base cation concentrations as upland, flat peat swamp and fen, suggesting that they are well connected hydrologically. Peat margin swamps were also found to modulate subsurface water movement between fen and upland (via reduced transmissivity from lower water tables) and therefore act as distinct ecohydrological units.
Abstract Observing the environment in the vast regions of Earth through remote sensing platforms provides the tools to measure ecological dynamics. The Arctic tundra biome, one of the largest inaccessible terrestrial biomes on Earth, requires remote sensing across multiple spatial and temporal scales, from towers to satellites, particularly those equipped for imaging spectroscopy (IS). We describe a rationale for using IS derived from advances in our understanding of Arctic tundra vegetation communities and their interaction with the environment. To best leverage ongoing and forthcoming IS resources, including National Aeronautics and Space Administration’s Surface Biology and Geology mission, we identify a series of opportunities and challenges based on intrinsic spectral dimensionality analysis and a review of current data and literature that illustrates the unique attributes of the Arctic tundra biome. These opportunities and challenges include thematic vegetation mapping, complicated by low‐stature plants and very fine‐scale surface composition heterogeneity; development of scalable algorithms for retrieval of canopy and leaf traits; nuanced variation in vegetation growth and composition that complicates detection of long‐term trends; and rapid phenological changes across brief growing seasons that may go undetected due to low revisit frequency or be obscured by snow cover and clouds. We recommend improvements to future field campaigns and satellite missions, advocating for research that combines multi‐scale spectroscopy, from lab studies to satellites that enable frequent and continuous long‐term monitoring, to inform statistical and biophysical approaches to model vegetation dynamics.
The Alaska Arctic Vegetation Archive (AVA-AK, GIVD-ID: NA-US-014) is a free, publically available database archive of vegetation-plot data from the Arctic tundra region of northern Alaska.The archive currently contains 24 datasets with 3,026 non-overlapping plots.Of these, 74% have geolocation data with 25-m or better precision.Species cover data and header data are stored in a Turboveg database.A standardized Pan Arctic Species List provides a consistent nomenclature for vascular plants, bryophytes, and lichens in the archive.A web-based online Alaska Arctic Geoecological Atlas (AGA-AK) allows viewing and downloading the species data in a variety of formats, and provides access to a wide variety of ancillary data.We conducted a preliminary cluster analysis of the first 16 datasets (1,613 plots) to examine how the spectrum of derived clusters is related to the suite of datasets, habitat types, and environmental gradients.We present the contents of the archive, assess its strengths and weaknesses, and provide three supplementary files that include the data dictionary, a list of habitat types, an overview of the datasets, and details of the cluster analysis.
Abstract Ecosystems in the North American Arctic-Boreal Zone (ABZ) experience a diverse set of disturbances associated with wildfire, permafrost dynamics, geomorphic processes, insect outbreaks and pathogens, extreme weather events, and human activity. Climate warming in the ABZ is occurring at over twice the rate of the global average, and as a result the extent, frequency, and severity of these disturbances are increasing rapidly. Disturbances in the ABZ span a wide gradient of spatiotemporal scales and have varying impacts on ecosystem properties and function. However, many ABZ disturbances are relatively understudied and have different sensitivities to climate and trajectories of recovery, resulting in considerable uncertainty in the impacts of climate warming and human land use on ABZ vegetation dynamics and in the interactions between disturbance types. Here we review the current knowledge of ABZ disturbances and their precursors, ecosystem impacts, temporal frequencies, spatial extents, and severity. We also summarize current knowledge of interactions and feedbacks among ABZ disturbances and characterize typical trajectories of vegetation loss and recovery in response to ecosystem disturbance using satellite time-series. We conclude with a summary of critical data and knowledge gaps and identify priorities for future study.
Industrial activities for resource extraction have led to a network of seismic lines across Canada's boreal regions where peatlands often make up over 50% of the landscape. These clearings can have a significant influence on ecosystem functioning through vegetation removal, flattening of microtopography, altering hydrological pathways and impacting biogeochemical processes. Recently, there has been a concerted effort to restore seismic lines to bring back the localized microtopography and encourage ecosystem recovery. A common restoration approach on seismic lines is mounding, which involves using machinery to recreate natural microtopography. Research is scarce on the impact on soil properties following both these disturbances and subsequent restoration on organic soils. The objectives of this study were to 1) identify differences in soil physical and chemical characteristics between areas disturbed by seismic lines and adjacent natural areas, and 2) to determine changes to soil physical and chemical properties following the mounding restoration technique. Research was undertaken at two contrasting boreal ecosites (a poor mesic and a treed fen) near Fort McMurray, Alberta, Canada. In July 2018, we collected soil samples at 34 seismic line locations, both on the line and 20 m into the adjacent undisturbed area. Samples were analyzed for bulk density, volumetric water content (VWC), organic matter content (OM), C:N ratios and δ13C/δ15N isotope analysis. Seismic line disturbances had a significant impact on soil properties, with increased bulk density and VWC on the line at both ecosites. We found an almost 40% reduction in OM on the line compared to natural areas at the poor mesic site, implying changes to carbon cycling, increased mineralization rates and carbon loss from the system. There was also δ13C/δ15N enrichment and narrower C:N ratios on the line, indicating increased decomposition. We found evidence of increased decomposition on the mounds created after restoration at the treed fen. Our results highlight a trade-off between restoration activities that may encourage recovery but also cause increased carbon losses from the system. This research is a first step in gaining a better understanding of these impacts in light of current restoration practices to ensure best management practices for improving ecosystem functioning.
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