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1. Arctic greening associated with lengthening growing seasons in Northern Alaska

   https://doi.org/10.1088/1748-9326/ab5e26  

   Arndt, Kyle A. ; Santos, Maria J. ; Ustin, Susan ; Davidson, Scott J. ; Stow, Doug ; Oechel, Walter C. ; Tran, Thao T. P. ; Graybill, Brian ; Zona, Donatella ( December 2019 , Environmental Research Letters)

   Many studies have reported that the Arctic is greening; however, we lack an understanding of the detailed patterns and processes that are leading to this observed greening. The normalized difference vegetation index (NDVI) is used to quantify greening, which has had largely positive trends over the last few decades using low spatial resolution satellite imagery such as AVHRR or MODIS over the pan-Arctic region. However, substantial fine scale spatial heterogeneity in the Arctic makes this large-scale investigation hard to interpret in terms of vegetation and other environmental changes. Here we focus on one area of the northern Alaskan Arctic using high spatial resolution (4 m) multispectral satellite imagery from DigitalGlobe^™to analyze the greening trend near Utqiaġvik (formerly known as Barrow) over 14 years from 2002 to 2016. We found that tundra vegetation has been greening (τ = 0.65,p = 0.01, NDVI increase of 0.01 yr⁻¹) despite no overall change in vegetation community composition. The greening is most closely correlated to the number of thawing degree days (R² = 0.77,F = 21.5,p < 0.001) which increased in a similar linear trend over the 14 year study period (1.79 ± 0.50 days per year,p < 0.01,τ = −0.56). This suggests that in this Arctic ecosystem, greening is occurring due to a lengthening growing season that appears tomore »stimulate plant productivity without any significant change in vegetation communities. We found that vegetation communities in wetter locations greened about twice as fast as those found in drier conditions supporting the hypothesis that these communities respond more strongly to warming. We suggest that in Arctic environments, vegetation productivity may continue to rise, particularly in wet areas.

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2. Tundra greenness

   https://doi.org/10.1175/BAMS-D-20-0086.  

   Frost, G. V. ( December 2020 , Bulletin of the American Meteorological Society)

   J. Richter-Menge, M. L. (Ed.)

   Highlights•In North America, tundra productivity for the 2019 growing season (the most recent data available) rebounded strongly from the previous year, in tandem with record summer warmth following the cold summer of 2018.•Since 2016, greenness trends have diverged strongly by continent; peak summer greenness has declined sharply in North America but has remained above the long-term mean in Eurasia.•The long-term satellite record (1982-2019) indicates "greening" across most of the Arctic but some regions exhibit "browning," underscoring the dynamic linkages that exist between tundra ecosystems and other elements of a changing Arctic system.
3. Positive response of tree productivity to warming is reversed by increased tree density at the Arctic tundra-taiga ecotone

   https://doi.org/10.1139/cjfr-2020-0466  

   Walker, Xanthe ; Alexander, Heather D. ; Berner, Logan ; Boyd, Melissa A ; Loranty, Michael M. ; Natali, Sue ; Mack, Michelle C. ( January 2021 , Canadian Journal of Forest Research)

   The transition zone between the northern boreal forest and the arctic tundra, known as the tundra-taiga ecotone (TTE) has undergone rapid warming in recent decades. In response to this warming, tree density, growth, and stand productivity are expected to increase. Increases in tree density have the potential to negate the positive impacts of warming on tree growth through a reduction in the active layer and an increase in competitive interactions. We assessed the effects of tree density on tree growth and climate-growth responses of Cajander larch (Larix cajanderi) and on trends in the normalized difference vegetation index (NDVI) in the TTE of Northeast Siberia. We examined 19 mature forest stands that all established after a fire in 1940 and ranged in tree density from 300 to 37,000 stems ha-1. High density stands with shallow active layers had lower tree growth, higher stand productivity, and more negative growth responses to growing season temperatures compared to low density stands with deep active layers. Variation in stand productivity across the density gradient was not captured by Landsat derived NDVI, but NDVI did capture annual variations in stand productivity. Our results suggest that the expected increases in tree density following fires at the TTEmore »may effectively limit tree growth and that NDVI is unlikely to capture increasing productivity associated with changes in tree density.« less
4. Thermal modeling of three lakes within the continuous permafrost zone in Alaska using the LAKE 2.0 model

   https://doi.org/10.5194/gmd-15-7421-2022  

   Clark, Jason A. ; Jafarov, Elchin E. ; Tape, Ken D. ; Jones, Benjamin M. ; Stepanenko, Victor ( January 2022 , Geoscientific Model Development)

   Abstract. Lakes in the Arctic are important reservoirs of heat withmuch lower albedo in summer and greater absorption of solar radiation thansurrounding tundra vegetation. In the winter, lakes that do not freeze totheir bed have a mean annual bed temperature >0 ∘C inan otherwise frozen landscape. Under climate warming scenarios, we expectArctic lakes to accelerate thawing of underlying permafrost due to warmingwater temperatures in the summer and winter. Previous studies of Arcticlakes have focused on ice cover and thickness, the ice decay process,catchment hydrology, lake water balance, and eddy covariance measurements,but little work has been done in the Arctic to model lake heat balance. Weapplied the LAKE 2.0 model to simulate water temperatures in three Arcticlakes in northern Alaska over several years and tested the sensitivity ofthe model to several perturbations of input meteorological variables(precipitation, shortwave radiation, and air temperature) and several modelparameters (water vertical resolution, sediment vertical resolution, depthof soil column, and temporal resolution). The LAKE 2.0 model is aone-dimensional model that explicitly solves vertical profiles of waterstate variables on a grid. We used a combination of meteorological data fromlocal and remote weather stations, as well as data derived from remotesensing, to drive the model. We validated modeled water temperatures withdatamore »of observed lake water temperatures at several depths over severalyears for each lake. Our validation of the LAKE 2.0 model is a necessarystep toward modeling changes in Arctic lake ice regimes, lake heat balance,and thermal interactions with permafrost. The sensitivity analysis shows usthat lake water temperature is not highly sensitive to small changes in airtemperature or precipitation, while changes in shortwave radiation and largechanges in precipitation produced larger effects. Snow depth and lake icestrongly affect water temperatures during the frozen season, which dominatesthe annual thermal regime of Arctic lakes. These findings suggest thatreductions in lake ice thickness and duration could lead to more heatstorage by lakes and enhanced permafrost degradation.« less
5. Greenness trends and carbon stocks of mangroves across Mexico

   https://doi.org/10.1088/1748-9326/ab246e  

   Vázquez-Lule, Alma ; Colditz, Rene ; Herrera-Silveira, Jorge ; Guevara, Mario ; Rodríguez-Zúñiga, María Teresa ; Cruz, Isabel ; Ressl, Rainer ; Vargas, Rodrigo ( July 2019 , Environmental Research Letters)

   Mangroves cover less than 0.1% of Earth’s surface, store large amounts of carbon per unit area, but are threatened by global environmental change. The capacity of mangroves productivity could be characterized by their canopy greenness, but this property has not been systematically tested across gradients of mangrove forests and national scales. Here, we analyzed time series of Normalized Difference Vegetation Index (NDVI), mean air temperature and total precipitation between 2001 and 2015 (14 years) to quantify greenness and climate variability trends for mangroves not directly influenced by land use/land cover change across Mexico. Between 2001 and 2015 persistent mangrove forests covered 432 800 ha, representing 57% of the total current mangrove area for Mexico. We found a temporal greenness increase between 0.003_{[0.001–0.004]}and 0.004_{[0.002–0.005]}yr⁻¹(NDVI values ± 95%CI) for mangroves located over the Gulf of California and the Pacific Coast, with many mangrove areas dominated byAvicennia germinans.Mangroves developed along the Gulf of Mexico and Caribbean Sea did not show significant greenness trends, but site-specific areas showed significant negative greenness trends. Mangroves with surface water input have above ground carbon stocks (AGC) between 37.7 and 221.9 Mg C ha⁻¹and soil organic carbon density at 30 cm depth (SOCD) between 92.4 and 127.3 Mg Cmore »ha⁻¹. Mangroves with groundwater water input have AGC of 12.7 Mg C ha⁻¹and SOCD of 219 Mg C ha⁻¹. Greenness and climate variability trends could not explain the spatial variability in carbon stocks for most mangrove forests across Mexico. Site-specific characteristics, including mangrove species dominance could have a major influence on greenness trends. Our findings provide a baseline for national-level monitoring programs, carbon accounting models, and insights for greenness trends that could be tested around the world.

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