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1. The role of land cover change in Arctic-Boreal greening and browning trends

   https://doi.org/10.1088/1748-9326/ab5429  

   Wang, Jonathan A. ; Friedl, Mark A. ( December 2019 , Environmental Research Letters)

   Many studies have used time series of satellite-derived vegetation indices to identify so-called greening and browning trends across the northern high-latitudes and to suggest that the productivity of Arctic-Boreal ecosystems is changing in response to climate forcing at local and continental scales. However, disturbances that alter land cover are prevalent in Arctic-Boreal ecosystems, and changes in Arctic-Boreal land cover, which complicate interpretation of trends in vegetation indices, have mostly been ignored in previous studies. Here we use a new land cover change dataset derived from Landsat imagery to explore the extent to which land cover and land cover change influence trends in the normalized difference vegetation index (NDVI) over a large (3.76 M km²) area of NASA’s Arctic Boreal Vulnerability Experiment, which spans much of northwestern Canada and Alaska. Between 1984 and 2012, 21.2% of the study domain experienced land cover change and 42.7% had significant NDVI trends. Land cover change occurred in 27.6% of locations with significant NDVI trends during this period and resulted in greening and browning rates 48%–128% higher than in areas of stable land cover. While the majority of land cover change areas experienced significant NDVI trends, more than half of areas with stable landmore »cover did not. Further, the extent and magnitude of browning and greening trends varied substantially as a function of land cover class and land cover change type. Forest disturbance from fire and timber harvest drove over one third of statistically significant NDVI trends and created complex mosaics of recent forest loss (as browning) and post-disturbance recovery (as greening) at both landscape and continental scale. Our results demonstrate the importance of land cover changes in highly disturbed high-latitude ecosystems for interpreting trends of NDVI and productivity across multiple spatial scales.

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2. Recent warming reverses forty-year decline in catastrophic lake drainage and hastens gradual lake drainage across northern Alaska

   https://doi.org/10.1088/1748-9326/ac3602  

   Lara, Mark J. ; Chen, Yaping ; Jones, Benjamin M. ( November 2021 , Environmental Research Letters)

   Lakes represent as much as ∼25% of the total land surface area in lowland permafrost regions. Though decreasing lake area has become a widespread phenomenon in permafrost regions, our ability to forecast future patterns of lake drainage spanning gradients of space and time remain limited. Here, we modeled the drivers of gradual (steady declining lake area) and catastrophic (temporally abrupt decrease in lake area) lake drainage using 45 years of Landsat observations (i.e. 1975–2019) across 32 690 lakes spanning climate and environmental gradients across northern Alaska. We mapped lake area using supervised support vector machine classifiers and object based image analyses using five-year Landsat image composites spanning 388 968 km². Drivers of lake drainage were determined with boosted regression tree models, using both static (e.g. lake morphology, proximity to drainage gradient) and dynamic predictor variables (e.g. temperature, precipitation, wildfire). Over the past 45 years, gradual drainage decreased lake area between 10% and 16%, but rates varied over time as the 1990s recorded the highest rates of gradual lake area losses associated with warm periods. Interestingly, the number of catastrophically drained lakes progressively decreased at a rate of ∼37% decade⁻¹from 1975–1979 (102–273 lakes draining year⁻¹) to 2010–2014 (3–8 lakes drainingmore »year⁻¹). However this 40 year negative trend was reversed during the most recent time-period (2015–2019), with observations of catastrophic drainage among the highest on record (i.e. 100–250 lakes draining year⁻¹), the majority of which occurred in northwestern Alaska. Gradual drainage processes were driven by lake morphology, summer air and lake temperature, snow cover, active layer depth, and the thermokarst lake settlement index (R²_adj= 0.42, CV = 0.35,p< 0.0001), whereas, catastrophic drainage was driven by the thawing season length, total precipitation, permafrost thickness, and lake temperature (R²_adj= 0.75, CV = 0.67,p< 0.0001). Models forecast a continued decline in lake area across northern Alaska by 15%–21% by 2050. However these estimates are conservative, as the anticipated amplitude of future climate change were well-beyond historical variability and thus insufficient to forecast abrupt ‘catastrophic’ drainage processes. Results highlight the urgency to understand the potential ecological responses and feedbacks linked with ongoing Arctic landscape reorganization.

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3. Upscaling surface energy fluxes over the North Slope of Alaska using airborne eddy-covariance measurements and environmental response functions

   https://doi.org/10.5194/acp-18-10007-2018  

   Serafimovich, Andrei ; Metzger, Stefan ; Hartmann, Jörg ; Kohnert, Katrin ; Zona, Donatella ; Sachs, Torsten ( January 2018 , Atmospheric Chemistry and Physics)

   Abstract. The objective of this study was to upscale airborne flux measurements ofsensible heat and latent heat and to develop high-resolution flux maps. Inorder to support the evaluation of coupled atmospheric–land-surface models weinvestigated spatial patterns of energy fluxes in relation to land-surfaceproperties. We used airborne eddy-covariance measurements acquired by the Polar 5research aircraft in June–July 2012 to analyze surface fluxes.Footprint-weighted surface properties were then related to 21 529 sensibleheat flux observations and 25 608 latent heat flux observations using bothremote sensing and modeled data. A boosted regression tree technique wasused to estimate environmental response functions between spatially andtemporally resolved flux observations and corresponding biophysical andmeteorological drivers. In order to improve the spatial coverage and spatialrepresentativeness of energy fluxes we used relationships extracted acrossheterogeneous Arctic landscapes to infer high-resolution surface energy fluxmaps, thus directly upscaling the observational data. These maps of projectedsensible heat and latent heat fluxes were used to assess energy partitioningin northern ecosystems and to determine the dominant energy exchangeprocesses in permafrost areas. This allowed us to estimate energy fluxes forspecific types of land cover, taking into account meteorological conditions.Airborne and modeled fluxes were then compared with measurements from aneddy-covariance tower near Atqasuk. Our results are an important contribution for themore »advanced, scale-dependentquantification of surface energy fluxes and they provide new insights into theprocesses affecting these fluxes for the main vegetation types inhigh-latitude permafrost areas.« less
4. Repeated Permafrost Formation and Degradation in Boreal Peatland Ecosystems in Relation to Climate Extremes, Fire, Ecological Shifts, and a Geomorphic Legacy

   https://doi.org/10.3390/atmos13081170  

   Jorgenson, Mark Torre ; Kanevskiy, Mikhail ; Roland, Carl ; Hill, Kenneth ; Schirokauer, David ; Stehn, Sarah ; Schroeder, Britta ; Shur, Yuri ( August 2022 , Atmosphere)

   Permafrost formation and degradation creates a highly patchy mosaic of boreal peatland ecosystems in Alaska driven by climate, fire, and ecological changes. To assess the biophysical factors affecting permafrost dynamics, we monitored permafrost and ecological conditions in central Alaska from 2005 to 2021 by measuring weather, land cover, topography, thaw depths, hydrology, soil properties, soil thermal regimes, and vegetation cover between burned (1990 fire) and unburned terrain. Climate data show large variations among years with occasional, extremely warm–wet summers and cold–snowless winters that affect permafrost stability. Microtopography and thaw depth surveys revealed both permafrost degradation and aggradation. Thaw depths were deeper in post-fire scrub compared to unburned black spruce and increased moderately during the last year, but analysis of historical imagery (1954–2019) revealed no increase in thermokarst rates due to fire. Recent permafrost formation was observed in older bogs due to an extremely cold–snowless winter in 2007. Soil sampling found peat extended to depths of 1.5–2.8 m with basal radiocarbon dates of ~5–7 ka bp, newly accumulating post-thermokarst peat, and evidence of repeated episodes of permafrost formation and degradation. Soil surface temperatures in post-fire scrub bogs were ~1 °C warmer than in undisturbed black spruce bogs, and thermokarst bogs andmore »lakes were 3–5 °C warmer than black spruce bogs. Vegetation showed modest change after fire and large transformations after thermokarst. We conclude that extreme seasonal weather, ecological succession, fire, and a legacy of earlier geomorphic processes all affect the repeated formation and degradation of permafrost, and thus create a highly patchy mosaic of ecotypes resulting from widely varying ecological trajectories within boreal peatland ecosystems.« less
5. Upscaling Methane Flux From Plot Level to Eddy Covariance Tower Domains in Five Alaskan Tundra Ecosystems

   https://doi.org/10.3389/fenvs.2022.939238  

   Wang, Yihui ; Yuan, Fengming ; Arndt, Kyle A. ; Liu, Jianzhao ; He, Liyuan ; Zuo, Yunjiang ; Zona, Donatella ; Lipson, David A. ; Oechel, Walter C. ; Ricciuto, Daniel M. ; et al ( July 2022 , Frontiers in Environmental Science)

   Spatial heterogeneity in methane (CH 4 ) flux requires a reliable upscaling approach to reach accurate regional CH 4 budgets in the Arctic tundra. In this study, we combined the CLM-Microbe model with three footprint algorithms to scale up CH 4 flux from a plot level to eddy covariance (EC) tower domains (200 m × 200 m) in the Alaska North Slope, for three sites in Utqiaġvik (US-Beo, US-Bes, and US-Brw), one in Atqasuk (US-Atq) and one in Ivotuk (US-Ivo), for a period of 2013–2015. Three footprint algorithms were the homogenous footprint (HF) that assumes even contribution of all grid cells, the gradient footprint (GF) that assumes gradually declining contribution from center grid cells to edges, and the dynamic footprint (DF) that considers the impacts of wind and heterogeneity of land surface. Simulated annual CH 4 flux was highly consistent with the EC measurements at US-Beo and US-Bes. In contrast, flux was overestimated at US-Brw, US-Atq, and US-Ivo due to the higher simulated CH 4 flux in early growing seasons. The simulated monthly CH 4 flux was consistent with EC measurements but with different accuracies among footprint algorithms. At US-Bes in September 2013, RMSE and NNSE were 0.002 μmol m −2  s −1 andmore »0.782 using the DF algorithm, but 0.007 μmol m −2  s −1 and 0.758 using HF and 0.007 μmol m −2  s −1 and 0.765 using GF, respectively. DF algorithm performed better than the HF and GF algorithms in capturing the temporal variation in daily CH 4 flux each month, while the model accuracy was similar among the three algorithms due to flat landscapes. Temporal variations in CH 4 flux during 2013–2015 were predominately explained by air temperature (67–74%), followed by precipitation (22–36%). Spatial heterogeneities in vegetation fraction and elevation dominated the spatial variations in CH 4 flux for all five tower domains despite relatively weak differences in simulated CH 4 flux among three footprint algorithms. The CLM-Microbe model can simulate CH 4 flux at both plot and landscape scales at a high temporal resolution, which should be applied to other landscapes. Integrating land surface models with an appropriate algorithm provides a powerful tool for upscaling CH 4 flux in terrestrial ecosystems.« less