Based on daily minimum, maximum, and mean surface air temperatures (T_min, T_max, T_mean) from the European Centre for Medium-Range Weather Forecast's reanalysis from 1979 onwards (ERA Interim), the accuracy of daily T_min and T_max reanalysis is assessed against in situ observations from four automatic weather stations (Zhongshan, EAGLE, LGB69, and Dome A) in East Antarctica from 2005 to 2008. ERA Interim generally shows a warm bias for T_min and a cool bias for T_max, with an underestimation of the diurnal temperature range. The reanalysis explains more than 84% of the daily and annual variance, and the replicating ability decreases gradually from the coast to the interior, with annual root mean square errors of 2.4 °C, 2.6 °C, 3.0 °C, and 4.3 °C for daily T_min, and 2.2 °C, 3.1 °C, 3.4 °C, and 4.9 °C for daily T_max at Zhongshan, LGB69, Eagle, and Dome A, respectively. ERA Interim shows little seasonal variability, although it performs a little better in the austral spring and worse in winter and autumn at Dome A. An analysis on spatial distribution of temperature and wind field indicates that ERA Interim has successfully replicated the progress of temperature extremes developing, occurring, and disappearing. In addition, weather events extracted from ERA Interim mainly occur on the same day as observations, with high cross-correlation coefficients (R ≧ 0.287, N ≧ 1131, P < 0.001). ERA Interim has, despite its regional limitations and deficiencies, proved to be a powerful tool for weather and climate studies in the Antarctic region.

Upscaling of sample data on indicators of decomposition to the landscape scale is often necessary for extensive ecological assessments. The amount of such data is mostly scarce even with high sampling efforts. Moreover, environmental conditions are very heterogeneous in high mountain regions. Therefore, the aim was to find a suitable technique for spatial modeling under these circumstances.

A method combining decision tree analysis and the construction of fuzzy membership functions is introduced for a GIS-based mapping of decomposition indicating parameters. It is compared with an approach solely based on decision trees. Within a case study in the Italian Alps the spatial distribution of humus forms, classified by the occurrence of an OH (humified residues) horizon, is examined. There appears to be a strong relationship with elevation and a minor correlation with slope exposition.

The fuzzy logic-based approach proves to be suitable for modeling the spatial distribution of indicators of decomposition. Mapping fuzzy values allows for the representation of small-scale variability and uncertainty of data due to a relatively low sample size in a very heterogeneous environment.

Despite its wide geographic distribution and important role in boreal forest fire regimes, little is known about the climate-growth relationships of black spruce (Picea mariana [Mill.] B.S.P.). We used site- and tree-level analyses to evaluate the radial growth responses to climate of black spruce growing on a north-facing toposequence in interior Alaska for the period A.D. 1949–2010. At the site level, correlations between growth and climate were negative for temperature and positive for precipitation. The signs and strengths of these correlations varied seasonally and over time. These site-level differences probably arise from tree interactions with non-climatic factors that vary with topography and include active layer thickness, soil temperature, solar radiation, microsite, and tree architecture. We infer that black spruce suffers from drought stress during warm, dry summers and that the causes of this moisture stress relate to topography and the seasonality of drought. Tree-level analyses reveal that divergent inter-tree growth responses among individual trees at the same site also occur, with the lower slope positions having the greatest frequency of mixed responses. The overall complexity of black spruce's climate-growth relationships reflects the plastic growth strategy that enables this species to tolerate harsh, high-latitude conditions across a transcontinental range.

In this study, we quantified the spatiotemporal variability and trends in observations of multiple snow characteristics in High Arctic Zackenberg in Northeast Greenland through 18 years. Annual premelt snow-depth observations collected in 2005–2014 along an elevation gradient showed significant differences in snow depth between vegetation types. The seasonal snow cover was characterized by strong interannual variability in the Zackenberg region. Particularly the timing of snow-cover onset and melt, and the annual maximum accumulation, varied up to an order of magnitude between years. Hence, apart from the snow-cover fraction registered annually on 10 June, which exhibits a significant trend of -2.3% per year over the 18-year period, we found little evidence of significant trends in the observed snow-cover characteristics. Moreover, SnowModel results for the Zackenberg region confirmed that the pronounced interannual variability in snow precipitations has persisted in this High Arctic setting since 1979 and may have masked potential temporal trends. In exception, a significant difference in interannual variability of snow-cover onset timing was observed through the period 1997–2014, which in the recent period since 2006 was 7.3 times more variable.

Near-surface air temperature variation with altitude (Tlr) is important for several applications including hydrology, ecology, climate, and biodiversity. To calculate Tlr accurately, a dense monitoring network over an altitudinal gradient is needed. Typically, meteorological monitoring in mountain regions is scarce and not adequate to calculate Tlr correctly. To overcome this problem in our region, we monitored temperature over a gradient ranging 2600–4200 m a.s.l. during an 18 month period. Using these data, we calculated Tlr for the first time at this altitude in the Andes and tested the impact of using the standard Tlr values instead of the observed ones to map temperature by means of the MTCLIM model. We found that annual lapse rate values (6.9 °C km^-1 for Tmean, 5.5 °C km^-1 for Tmin, and 8.8 °C km^-1 for Tmax) differ significantly from the MTCLIM default values and that temperature maps improved vastly when measured Tlr was entered, especially for Tmax and Tmin. Our results may be representative of the broader area, as Tlr in our study period is not affected by microclimatic conditions generated by differences in topography and land cover between our monitoring sites; moreover, observed temperature during our study period was found to be representative of the longer-term annual climatology of the region.

Mounting evidence suggests that Earth's cryosphere harbors diverse and active microbial communities. However, our understanding of microbial composition and diversity in seasonal snowpack of montane ecosystems remains limited. We sequenced the 16S rRNA gene to determine microbial structure (composition and diversity) of snow at two depths (0–15 and 15–30 cm) of a subalpine site in the Southern Sierra Critical Zone Observatory, California, U.S.A. Proteobacteria dominated both depths (~72% of sequences), and this phylum was composed mostly of bacteria within the Rhodospirillales order. Cyanobacteria were almost exclusively present in the upper snow layer, while Actinobacteria and Firmicutes were more abundant in the deep snow layer. Many of the most abundant phylotypes were Acetobacteraceae. Phylotype NCR4874, which comprised 22%–32% of the sequences, was most closely related to the N₂-fixing bacteria Asaia siamensis, suggesting that N₂ fixation may be an important process within the Sierra snowpack. In addition, just under half (45%) of the numerically dominant phylotypes shared >98% similarity with sequences recovered from other cold environments. Our results suggest that microbial communities of subalpine Sierra Nevada snowpack are diverse, with both snow depths harboring distinct but overlapping communities consisting largely of cold-adapted bacteria.

Documenting and predicting patterns of vegetation change over time are challenging due to a lack of sufficiently detailed historical data for comparison. Montane plant communities are expected to respond to anthropogenic disturbance, including climate change, in complex ways dependent on component species' responses to changing abiotic and biotic conditions. To investigate the patterns and possible causes of temporal changes in montane plant communities, we resampled 121 transects surveyed by Jean Langenheim from 1948 to 1952 in the East River Basin near Crested Butte, Colorado, U.S.A. Langenheim quantified the composition of the four predominant community types (sagebrush, spruce-fir, upland-herbaceous, and alpine) at sites ranging from 2600 to 4100 m in elevation. Our resurvey of the same sites 65 years later revealed that all four communities currently have much higher levels of heterogeneity among sites and have experienced significant changes in species composition and dominance. Compositional changes include significant increases in bare ground, graminoid and shrub abundance, and loss of forbs, at higher elevations. Species' mean elevations shifted upward 41 m, and many species expanded their ranges into new communities. Elevation shifts were most pronounced from lower elevation communities, while many alpine species shifted their ranges into lower subalpine meadow communities.

The near-surface soil is an important interface in ground—atmosphere interactions. The near-surface soil freeze-thaw status is critical for energy, moisture, and carbon exchange between the ground and the atmosphere, plant growth, and the ecosystem as a whole. The main objective of this study is to investigate climatology of the timing and duration of the near-surface soil freeze-thaw status using data from 636 meteorological stations across China for the baseline period from July 1971 through June 2001. The long-term average first date of the near-surface soil freeze is 14 September (30 July–30 October), the last date is 15 May (8 April–21 June), the duration is 245 ± 85 days, and the actual number of the near-surface soil freeze days is 202 ± 90 days over China as a whole. On the Qinghai—Tibetan Plateau, the near-surface soil freeze can occur essentially in any month of a year. The spatial variations of the near-surface soil freeze-thaw status are strongly controlled by latitude in east China, and by elevation in west China. The long-term average 220-day and 260-day contours of the near-surface soil freeze coincide approximately with the southern boundary of high—latitude permafrost regions in northeastern China and the lower boundary of high—altitude permafrost regions in west China, respectively. The number of days and duration of the near-surface soil freeze decreased with increasing long-term mean annual air temperature (MAAT). Variation of the actual number of the near-surface soil freeze days presents nonlinear linkage to the length of the near-surface soil freeze duration and also to the MAAT climatology. The timing and duration of the near-surface soil freeze-thaw status are strongly nonlinearly related to air freezing index, but are nearly linearly related to air thawing index.

Plants are strongly influenced by their thermal environments, and this influence manifests itself in a variety of ways, such as altered ranges, growth, morphology, or physiology. However, plants also modify their local thermal environments through feedbacks related to properties and processes such as albedo and evapotranspiration. Here, we used leaf- and plot- level thermography on the north slope of the Brooks Range, Alaska, to explore interspecific differences in thermal properties among arctic tundra plants, and to determine if species differentially contribute to plot temperature. At the leaf-level, we found significant differences (p < 0.05) for in situ temperatures among the 13 study species. At the plot level, we found that the fractional cover of vascular plant species, lichen, litter, and moss had a significant effect on plot temperature (p < 0.05, R²= 0.61). A second model incorporating thermal leaf properties—in addition to the fraction of vascular plant and other dominant ground covers—also predicted plot temperature, but with lower explanatory power (p < 0.05, R²= 0.32). These results potentially have important implications for our understanding of how individual plant species influence canopy-level thermal properties and how temperature—dependent properties and processes may be impacted by climate change—induced shifts in species composition.

Trees at upper treelines are exposed to more extreme environmental conditions than those at lower elevations. Climate changes at the upper treeline facilitate the establishment or intensify the mortality of trees and, consequently, affect species distributions. The structure and density of individuals of Nothofagus pumilio above the upper treeline, together with their temporal patterns of establishment, were determined in three sites located along a west-east precipitation gradient across the Patagonian Andes. Patterns of tree establishment were compared to regional variations in temperature and precipitation, as well as to indexes of atmospheric circulation that modulate northern Patagonian climate. Mesic and dry sites along the moisture gradient have a lower density of newly established trees; however, individuals show larger basal diameters and greater annual growth rates, heights, and number of branches than those established in humid sites. In wet areas, the high density of individuals reflects the higher rates of N. pumilio establishment and survival. At drier treelines, low snow persistence, associated with longer growing seasons, appears to be related to the larger size of individuals. At all sites, patterns of tree establishment are characterized by an abrupt increase in recruitment starting in the mid-1970s and a marked decrease in the late 1990s. The onset of tree establishment above the treeline coincides with an increase in regional spring-summer temperature in the year 1977, concurrent with the negative-to-positive shift in the phase of the Pacific Decadal Oscillation (PDO). In contrast, the decrease in N. pumilio establishment since the late 1990s coincides with an opposite shift (positive to negative) in the PDO. This recent change in the PDO phase did not significantly modify the mean values but increased the interannual variability of the spring-summer temperatures in the region. Changes in the PDO, which encompasses complex variations in environmental conditions at the upper treeline, are more closely related to N. pumilio establishment than are variations in temperature or precipitation alone. In addition, the distinction between the effects of changes in mean values versus the effects of climate variability is crucial for properly predicting forest responses to climate changes.