68 research outputs found
Brief communication: Identification of tundra topsoil frozen/thawed state from SMAP and GCOM-W1 radiometer measurements using the spectral gradient method
From 2015 to 2020, using the spectral gradient
radiometric method, the possibility of the frozen/thawed (FT) state
identification of tundra soil was investigated based on Soil Moisture Active Passive (SMAP) and Global Change Observation Mission â Water Satellite 1 (GCOM-W1) satellite observations of 10 test sites located in the Arctic regions of
Canada, Finland, Russia, and the USA. It is shown that the spectral
gradients of brightness temperature and reflectivity (measured in the
frequency range from 1.4 to 36.5âGHz with horizontal polarization, a
determination coefficient from 0.775 to 0.834, a root-mean-square error from
6.6 to 10.7âd and a bias from â3.4 to +6.5âd) make it
possible to identify the FT state of the tundra topsoil. The spectral gradient
method has a higher accuracy with respect to the identification of the FT state of
tundra soils than single-frequency methods based on the
calculation of polarization index.</p
Range shifts in a foundation sedge potentially induce large Arctic ecosystem carbon losses and gains
Variability in above- and belowground Carbon Stocks in a Siberian Larch Watershed
Permafrost soils store between 1330 and 1580Pg carbon (C), which is 3 times the amount of C in global vegetation, almost twice the amount of C in the atmosphere, and half of the global soil organic C pool. Despite the massive amount of C in permafrost, estimates of soil C storage in the high-latitude permafrost region are highly uncertain, primarily due to undersampling at all spatial scales; circumpolar soil C estimates lack sufficient continental spatial diversity, regional intensity, and replication at the field-site level. Siberian forests are particularly undersampled, yet the larch forests that dominate this region may store more than twice as much soil C as all other boreal forest types in the continuous permafrost zone combined. Here we present above- and belowground C stocks from 20 sites representing a gradient of stand age and structure in a larch watershed of the Kolyma River, near Chersky, Sakha Republic, Russia. We found that the majority of C stored in the top 1m of the watershed was stored belowground (92%), with 19% in the top 10cm of soil and 40% in the top 30cm. Carbon was more variable in surface soils (10cm; coefficient of variation (CV)â=â0.35 between stands) than in the top 30cm (CVâ=â0.14) or soil profile to 1m (CVâ=â0.20). Combined active-layer and deep frozen deposits (surface â 15m) contained 205kgCmâ2 (yedoma, non-ice wedge) and 331kgCmâ2 (alas), which, even when accounting for landscape-level ice content, is an order of magnitude more C than that stored in the top meter of soil and 2 orders of magnitude more C than in aboveground biomass. Aboveground biomass was composed of primarily larch (53%) but also included understory vegetation (30%), woody debris (11%) and snag (6%) biomass. While aboveground biomass contained relatively little (8%) of the C stocks in the watershed, aboveground processes were linked to thaw depth and belowground C storage. Thaw depth was negatively related to stand age, and soil C density (top 10cm) was positively related to soil moisture and negatively related to moss and lichen cover. These results suggest that, as the climate warms, changes in stand age and structure may be as important as direct climate effects on belowground environmental conditions and permafrost C vulnerability
Summer warming explains widespread but not uniform greening in the Arctic tundra biome
Arctic warming can influence tundra ecosystem function with consequences for climate feedbacks, wildlife and human communities. Yet ecological change across the Arctic tundra biome remains poorly quantified due to field measurement limitations and reliance on coarse-resolution satellite data. Here, we assess decadal changes in Arctic tundra greenness using time series from the 30âm resolution Landsat satellites. From 1985 to 2016 tundra greenness increased (greening) at ~37.3% of sampling sites and decreased (browning) at ~4.7% of sampling sites. Greening occurred most often at warm sampling sites with increased summer air temperature, soil temperature, and soil moisture, while browning occurred most often at cold sampling sites that cooled and dried. Tundra greenness was positively correlated with graminoid, shrub, and ecosystem productivity measured at field sites. Our results support the hypothesis that summer warming stimulated plant productivity across much, but not all, of the Arctic tundra biome during recent decades
Surface Energy Budgets of Arctic Tundra During Growing Season
This study analyzed summer observations of diurnal and seasonal surface energy budgets across several monitoring sites within the Arctic tundra underlain by permafrost. In these areas, latent and sensible heat fluxes have comparable magnitudes, and ground heat flux enters the subsurface during short summer intervals of the growing period, leading to seasonal thaw. The maximum entropy production (MEP) model was tested as an input and parameter parsimonious model of surface heat fluxes for the simulation of energy budgets of these permafrostâunderlain environments. Using net radiation, surface temperature, and a single parameter characterizing the thermal inertia of the heat exchanging surface, the MEP model estimates latent, sensible, and ground heat fluxes that agree closely with observations at five sites for which detailed flux data are available. The MEP potential evapotranspiration model reproduces estimates of the PenmanâMonteith potential evapotranspiration model that requires at least five input meteorological variables (net radiation, ground heat flux, air temperature, air humidity, and wind speed) and empirical parameters of surface resistance. The potential and challenges of MEP model application in sparsely monitored areas of the Arctic are discussed, highlighting the need for accurate measurements and constraints of ground heat flux.Plain Language SummaryGrowing season latent and sensible heat fluxes are nearly equal over the Arctic permafrost tundra regions. Persistent ground heat flux into the subsurface layer leads to seasonal thaw of the top permafrost layer. The maximum energy production model accurately estimates the latent, sensible, and ground heat flux of the surface energy budget of the Arctic permafrost regions.Key PointThe MEP model is parsimonious and well suited to modeling surface energy budget in dataâsparse permafrost environmentsPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/150560/1/jgrd55584.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/150560/2/jgrd55584_am.pd
Fire as a fundamental ecological process: Research advances and frontiers
© 2020 The Authors. Journal of Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society Fire is a powerful ecological and evolutionary force that regulates organismal traits, population sizes, species interactions, community composition, carbon and nutrient cycling and ecosystem function. It also presents a rapidly growing societal challenge, due to both increasingly destructive wildfires and fire exclusion in fire-dependent ecosystems. As an ecological process, fire integrates complex feedbacks among biological, social and geophysical processes, requiring coordination across several fields and scales of study. Here, we describe the diversity of ways in which fire operates as a fundamental ecological and evolutionary process on Earth. We explore research priorities in six categories of fire ecology: (a) characteristics of fire regimes, (b) changing fire regimes, (c) fire effects on above-ground ecology, (d) fire effects on below-ground ecology, (e) fire behaviour and (f) fire ecology modelling. We identify three emergent themes: the need to study fire across temporal scales, to assess the mechanisms underlying a variety of ecological feedbacks involving fire and to improve representation of fire in a range of modelling contexts. Synthesis: As fire regimes and our relationships with fire continue to change, prioritizing these research areas will facilitate understanding of the ecological causes and consequences of future fires and rethinking fire management alternatives
Reviews and syntheses: Changing ecosystem influences on soil thermal regimes in northern high-latitude permafrost regions
Soils in Arctic and boreal ecosystems store twice as much carbon as the atmosphere, a portion of which may be released as high-latitude soils warm. Some of the uncertainty in the timing and magnitude of the permafrostâclimate feedback stems from complex interactions between ecosystem properties and soil thermal dynamics. Terrestrial ecosystems fundamentally regulate the response of permafrost to climate change by influencing surface energy partitioning and the thermal properties of soil itself. Here we review how Arctic and boreal ecosystem processes influence thermal dynamics in permafrost soil and how these linkages may evolve in response to climate change. While many of the ecosystem characteristics and processes affecting soil thermal dynamics have been examined individually (e.g., vegetation, soil moisture, and soil structure), interactions among these processes are less understood. Changes in ecosystem type and vegetation characteristics will alter spatial patterns of interactions between climate and permafrost. In addition to shrub expansion, other vegetation responses to changes in climate and rapidly changing disturbance regimes will affect ecosystem surface energy partitioning in ways that are important for permafrost. Lastly, changes in vegetation and ecosystem distribution will lead to regional and global biophysical and biogeochemical climate feedbacks that may compound or offset local impacts on permafrost soils. Consequently, accurate prediction of the permafrost carbon climate feedback will require detailed understanding of changes in terrestrial ecosystem distribution and function, which depend on the net effects of multiple feedback processes operating across scales in space and time
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