Characterizing tundra snow sub-pixel variability to improve brightness temperature estimation in satellite SWE retrievals

Topography and vegetation play a major role in sub-pixel variability of Arctic snowpack properties but are not considered in current passive microwave (PMW) satellite SWE retrievals. Simulation of sub-pixel variability of snow properties is also problematic when downscaling snow and climate models. In this study, we simplified observed variability of snowpack properties (depth, density, microstructure) in a two-layer model with mean values and distributions of two multi-year tundra dataset so they could be incorporated in SWE retrieval schemes. Spatial variation of snow depth was parameterized by a log-normal distribution with mean (μsd) values and coefficients of variation (CVsd). Snow depth variability (CVsd) was found to increase as a function of the area measured by a remotely piloted aircraft system (RPAS). Distributions of snow specific surface area (SSA) and density were found for the wind slab (WS) and depth hoar (DH) layers. The mean depth hoar fraction (DHF) was found to be higher in Trail Valley Creek (TVC) than in Cambridge Bay (CB), where TVC is at a lower latitude with a subarctic shrub tundra compared to CB, which is a graminoid tundra. DHFs were fitted with a Gaussian process and predicted from snow depth. Simulations of brightness temperatures using the Snow Microwave Radiative Transfer (SMRT) model incorporating snow depth and DHF variation were evaluated with measurements from the Special Sensor Microwave/Imager and Sounder (SSMIS) sensor. Variation in snow depth (CVsd) is proposed as an effective parameter to account for sub-pixel variability in PMW emission, improving simulation by 8 K. SMRT simulations using a CVsd of 0.9 best matched CVsd observations from spatial datasets for areas > 3 km2, which is comparable to the 3.125 km pixel size of the Equal-Area Scalable Earth (EASE)-Grid 2.0 enhanced resolution at 37 GHz.

Late Pleistocene shrub expansion preceded megafauna turnover and extinctions in eastern Beringia

The collapse of the steppe-tundra biome (mammoth steppe) at the end of the Pleistocene is used as an important example of top-down ecosystem cascades, where human hunting of keystone species led to profound changes in vegetation across high latitudes in the Northern Hemisphere. Alternatively, it is argued that this biome transformation occurred through a bottom-up process, where climate-driven expansion of shrub tundra (Betula, Salix spp.) replaced the steppe-tundra vegetation that grazing megafauna taxa relied on. In eastern Beringia, these differing hypotheses remain largely untested, in part because the precise timing and spatial pattern of Late Pleistocene shrub expansion remains poorly resolved. This uncertainty is caused by chronological ambiguity in many lake sediment records, which typically rely on radiocarbon (14C) dates from bulk sediment or aquatic macrofossils—materials that are known to overestimate the age of sediment layers. Here, we reexamine Late Pleistocene pollen records for which 14C dating of terrestrial macrofossils is available and augment these data with 14C dates from arctic ground-squirrel middens and plant macrofossils. Comparing these paleovegetation data with a database of published 14C dates from megafauna remains, we find the postglacial expansion of shrub tundra preceded the regional extinctions of horse (Equus spp.) and mammoth (Mammuthus primigenius) and began during a period when the frequency of 14C dates indicates large grazers were abundant. These results are not consistent with a model of top-down ecosystem cascades and support the hypothesis that climate-driven habitat loss preceded and contributed to turnover in mammal communities.

Dispersal and fire limit Arctic shrub expansion

Arctic shrub expansion has been widely reported in recent decades, with large impacts on carbon budgets, albedo, and warming rates in high latitudes. However, predicting shrub expansion across regions remains challenging because the underlying controls remain unclear. Observational studies and models typically use relationships between observed shrub presence and current environmental suitability (climate and topography) to predict shrub expansion, but such approaches omit potentially important biotic-abiotic interactions and non-stationary relationships. Here, we use long-term high-resolution satellite imagery across Alaska and western Canada to show that observed shrub expansion has not been controlled by environmental suitability during 1984-2014, but rather can only be explained by accounting for seed dispersal and fire. These findings provide the impetus for better observations of recruitment and for incorporating currently underrepresented processes of seed dispersal and fire in land models to project shrub expansion and future climate feedbacks. Integrating these dynamic processes with projected fire extent and climate, we estimate that shrubs will expand into 25% of the non-shrub tundra by 2100, in contrast to 39% predicted using a relationship with increasing suitability alone. Thus, using environmental suitability alone likely overestimates and misrepresents the spatial pattern of shrub expansion and its associated carbon sink.

Plant Sedimentary Ancient DNA From Far East Russia Covering the Last 28,000 Years Reveals Different Assembly Rules in Cold and Warm Climates

Woody plants are expanding into the Arctic in response to the warming climate. The impact on arctic plant communities is not well understood due to the limited knowledge about plant assembly rules. Records of past plant diversity over long time series are rare. Here, we applied sedimentary ancient DNA metabarcoding targeting the P6 loop of the chloroplast trnL gene to a sediment record from Lake Ilirney (central Chukotka, Far Eastern Russia) covering the last 28 thousand years. Our results show that forb-rich steppe-tundra and dwarf-shrub tundra dominated during the cold climate before 14 ka, while deciduous erect-shrub tundra was abundant during the warm period since 14 ka. Larix invasion during the late Holocene substantially lagged behind the likely warmest period between 10 and 6 ka, where the vegetation biomass could be highest. We reveal highest richness during 28–23 ka and a second richness peak during 13–9 ka, with both periods being accompanied by low relative abundance of shrubs. During the cold period before 14 ka, rich plant assemblages were phylogenetically clustered, suggesting low genetic divergence in the assemblages despite the great number of species. This probably originates from environmental filtering along with niche differentiation due to limited resources under harsh environmental conditions. In contrast, during the warmer period after 14 ka, rich plant assemblages were phylogenetically overdispersed. This results from a high number of species which were found to harbor high genetic divergence, likely originating from an erratic recruitment process in the course of warming. Some of our evidence may be of relevance for inferring future arctic plant assembly rules and diversity changes. By analogy to the past, we expect a lagged response of tree invasion. Plant richness might overshoot in the short term; in the long-term, however, the ongoing expansion of deciduous shrubs will eventually result in a phylogenetically more diverse community.

Central Yamal vegetation monitoring based on Sentinel-2 and Sentinel-1 imagery

In this study fusion of optical (Sentinel-2) and radar (Sentinel-1) imagery is presented for vegetation cover classification in polar Arctic environment of the Western Siberia. Sentinel-1 and Sentinel-2 images were analyzed using parametric rule classification. Results showed significantly improved land cover classification results based on contextual analysis. Synergy of Sentinel-2 bands 4 and 3 and Sentinel-1 dual polarization VV and VH images increased the classification accuracy significantly. Specifically, classification accuracy increased for two classes — Erect dwarf-shrub tundra with 6% and Fresh Water with 10%. The classification accuracy as well test sites were analyzed using in situ data collected during three fieldwork campaigns in August-September (2016–2018) in the surrounding of Bovanenkovo settlement.

Thermal Bridging Through Branches of Snow-Covered Shrubs Cool Down Permafrost in Winter

Warming-induced shrub expansion on Arctic tundra (Arctic greening) is thought to warm up permafrost by several degrees, as shrubs trap blowing snow and increase snowpack thermal insulation, limiting permafrost winter cooling and facilitating its thaw. At Bylot Island, (Canadian high Arctic, 73°N) we monitored permafrost temperature at nearby unmanipulated herb tundra and shrub tundra sites and unexpectedly observed that low shrubs cool permafrost by 1.21°C over the November-February period. This is despite a snowpack twice as insulating in shrubs. Using heat transfer models and finite-element simulations, we show that this winter cooling is caused by thermal bridging through frozen shrub branches. This effect largely compensates the warming effect induced by the more insulating snow in shrubs. The cooling is partly canceled in spring when shrub branches under snow absorb solar radiation and accelerate permafrost warming. The overall effect is expected to depend on snow and shrub characteristics and terrain aspect. These significant perturbations of the permafrost thermal regime by shrub branches should be considered in projections of permafrost thawing, nutrient recycling and greenhouse gas emissions.

Paleo-Ecology of the Yedoma Ice Complex on Sobo-Sise Island (EasternLena Delta, Siberian Arctic)

Late Pleistocene permafrost of the Yedoma type constitutes a valuable paleo-environmental archive due to the presence of numerous and well-preserved floral and faunal fossils. The study of the fossil Yedoma inventory allows for qualitative and quantitative reconstructions of past ecosystem and climate conditions and variations over time. Here, we present the results of combined paleo-proxy studies including pollen, chironomid, diatom and mammal fossil analyses from a prominent Yedoma cliff on Sobo-Sise Island in the eastern Lena Delta, NE Siberia to complement previous and ongoing paleo-ecological research in western Beringia. The Yedoma Ice Complex (IC) cliff on Sobo-Sise Island (up to 28 m high, 1.7 km long) was continuously sampled at 0.5 m resolution. The entire sequence covers the last about 52 cal kyr BP, but is not continuous as it shows substantial hiatuses at 36–29 cal kyr BP, at 20–17 cal kyr BP and at 15–7 cal kyr BP. The Marine Isotope Stage (MIS) 3 Yedoma IC (52–28 cal kyr BP) pollen spectra show typical features of tundra–steppe vegetation. Green algae remains indicate freshwater conditions. The chironomid assemblages vary considerably in abundance and diversity. Chironomid-based TJuly reconstructions during MIS 3 reveal warmer-than-today TJuly at about 51 cal kyr BP, 46-44 and 41 cal kyr BP. The MIS 2 Yedoma IC (28–15 cal kyr BP) pollen spectra represent tundra-steppe vegetation as during MIS 3, but higher abundance of Artemisia and lower abundances of algae remains indicate drier summer conditions. The chironomid records are poor. The MIS 1 (7–0 cal kyr BP) pollen spectra indicate shrub-tundra vegetation. The chironomid fauna is sparse and not diverse. The chironomid-based TJuly reconstruction supports similar-as-today temperatures at 6.4–4.4 cal kyr BP. Diatoms were recorded only after about 6.4 cal kyr BP. The Sobo-Sise Yedoma record preserves traces of the West Beringian tundra-steppe that maintained the Mammoth fauna including rare evidence for woolly rhinoceros’ presence. Chironomid-based TJuly reconstructions complement previous plant-macrofossil based TJuly of regional MIS 3 records. Our study from the eastern Lena Delta fits into and extends previous paleo-ecological Yedoma studies to characterize Beringian paleo-environments in the Laptev Sea coastal region.

Simulating shrubs and their energy and carbon dioxide fluxes in Canada's Low Arctic with the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC)

Climate change in the Arctic is leading to shifts in vegetation communities, permafrost degradation and alteration of tundra surface–atmosphere energy and carbon (C) fluxes, among other changes. However, year-round C and energy flux measurements at high-latitude sites remain rare. This poses a challenge for evaluating the impacts of climate change on Arctic tundra ecosystems and for developing and evaluating process-based models, which may be used to predict regional and global energy and C feedbacks to the climate system. Our study used 14 years of seasonal eddy covariance (EC) measurements of carbon dioxide (CO2), water and energy fluxes, and winter soil chamber CO2 flux measurements at a dwarf-shrub tundra site underlain by continuous permafrost in Canada’s Southern Arctic ecozone to evaluate the incorporation of shrub plant functional types (PFTs) in the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC), the land surface component of the Canadian Earth System Model. In addition to new PFTs, a modification of the efficiency with which water evaporates from the ground surface was applied. This modification addressed a high ground evaporation bias that reduced model performance when soils became very dry, limited heat flow into the ground, and reduced plant productivity through water stress effects. Compared to the grass and tree PFTs previously used by CLASSIC to represent the vegetation in Arctic permafrost-affected regions, simulations with the new shrub PFTs better capture the physical and biogeochemical impact of shrubs on the magnitude and seasonality of energy and CO2 fluxes at the dwarf-shrub tundra evaluation site. The revised model, however, tends to overestimate gross primary productivity, particularly in spring, and overestimated late-winter CO2 emissions. On average, annual net ecosystem CO2 exchange was positive for all simulations, suggesting this site was a net CO2 source of 18 ± 4 g C m−2 yr−1 using shrub PFTs, 15 ± 6 g C m−2 yr−1 using grass PFTs, and 25 ± 5 g C m−2 yr−1 using tree PFTs. These results highlight the importance of using appropriate PFTs in process-based models to simulate current and future Arctic surface–atmosphere interactions.

Shrubs covered by snow in the high Arctic cool down permafrost in winter by thermal bridging through frozen branches

<p>Warming-induced shrub expansion on Arctic tundra is generally thought to warm up permafrost, as shrubs trap blowing snow and increase the thermal insulation effect of snow, limiting permafrost winter cooling. We have monitored the thermal regime of permafrost on Bylot Island, 73°N in the Canadian high Arctic at nearby herb tundra and shrub tundra sites. Once adjusted for differences in air temperature, we find that shrubs actually cool permafrost by 0.6°C over November-March 2019, despite a snowpack twice as insulating in shrubs. By simulating the rate of propagation of thermal perturbations and using finite element calculations, we show that heat conduction through frozen shrub branches have a winter cooling effect of 1.5°C which compensates the warming effect induced by the more insulating snow in shrubs. In spring shrub branches under snow absorb solar radiation and accelerate permafrost warming. Over the whole snow season, simulations indicate that heat and radiation transfer through shrub branches result in a 0.3°C cooling effect. This is contrary to many previous studies, which concluded to a warming effect, sometimes based on environmental manipulations that may perturb the natural environment. The impact of shrubs on the permafrost thermal regime may need to be re-evaluated.</p>

Simulating shrubs and their energy and carbon dioxide fluxes in Canada's Low Arctic with the Canadian Land Surface Scheme Including biogeochemical Cycles (CLASSIC)

The Arctic is warming more rapidly than other regions of the world leading to ecosystem change including shifts in vegetation communities, permafrost degradation and alteration of tundra surface-atmosphere energy and carbon (C) fluxes, among others. However, year-round C and energy flux measurements at high-latitude sites remain rare. This poses a challenge for evaluating the impacts of climate change on Arctic tundra ecosystems and for developing and evaluating process-based models, which may be used to predict regional and global energy and C feedbacks to the climate system. Our study used 14 years of seasonal eddy covariance (EC) measurements of carbon dioxide (CO2), water and energy fluxes and winter soil chamber CO2 flux measurements at a dwarf-shrub tundra site underlain by continuous permafrost in Canada's Southern Arctic ecozone to evaluate the incorporation of shrub plant functional types (PFTs) in the Canadian Land Surface Scheme Including biogeochemical Cycles (CLASSIC), the land surface component of the Canadian Earth System Model. In addition to new PFTs, a modification of the efficiency with which water evaporates from the ground surface was applied. This modification addressed a high ground evaporation bias that reduced model performance when soils became very dry, limited heat flow into the ground and reduced plant productivity through water stress effects. Compared to the grass and tree PFTs previously used by CLASSIC to represent the vegetation in Arctic permafrost-affected regions, simulations with the new shrub PFTs better capture the physical and biogeochemical impact of shrubs on the magnitude and seasonality of energy and CO2 fluxes at the dwarf-shrub tundra evaluation site. The revised model, however, tends to overestimate gross primary productivity, particularly in spring, and overestimated late winter CO2 emissions. On average, annual net ecosystem CO2 exchange was positive for all simulations, suggesting this site was a net CO2 source of 18 ± 4 g C m−2 year−1 using shrub PFTs, 15 ± 6 g C m−2 year−1 using grass PFTs, and 25 ± 5 g C m−2 year−1 using tree PFTs. These results highlight the importance of using appropriate PFTs in process-based models to simulate current and future Arctic surface-atmosphere interactions.