Persistent Snow Research Articles

The phenology of the subnivium

The subnivium is a seasonal refuge that exists at the interface between the snowpack and the ground, and provides a haven for a diversity of species to survive extreme winter temperatures. Due to the fitness of many plants and animals being strongly influenced by winter conditions, much attention has been given to changes in the timing of snow cover extent and duration in seasonally snow-covered environments; however, these broad-scale characteristics do not capture the finer-scale dynamics of the subnivium. To study the factors associated with subnivium development, we quantified three critical phenophases of the subnivium: establishment, maintenance, and disintegration along a latitudinal and land cover gradient in the Great Lakes Region of North America. We hypothesized that subnivium phenophases would depend primarily on snow depth and air temperature, but that these would be mediated by latitude and land cover. We found that patterns in both establishment and disintegration were affected by latitude more than land cover, but that variability in the timing of early season snowfall events overrode the effects of both factors in subnivium establishment. In contrast, disintegration was predictably later in more northerly sites, regardless of interannual variation in weather patterns. We found that the subnivium was the result of a balance between ambient temperature, snow depth, and snow density, but that ambient temperatures constrained the system by contributing to the frequency of snowfall and inducing changes in snow depth and density. Areas in lake effect zones, characterized by high snow depths and persistent snow cover, may be the last refugia for subnivia-dependent species given the predicted shifting climate regimes of the 21st century.

How Does Snow Persistence Relate to Annual Streamflow in Mountain Watersheds of the Western U.S. With Wet Maritime and Dry Continental Climates?

AbstractWith climate warming, many regions are experiencing changes in snow accumulation and persistence. These changes are known to affect streamflow volume, but the magnitude of the effect varies between regions. This research evaluates whether variables derived from remotely sensed snow cover can be used to estimate annual streamflow at the small watershed scale across the western U.S., a region with a wide range of climate types. We compared snow cover variables derived from MODIS, snow persistence (SP), and snow season (SS), to more commonly utilized metrics, snow fraction (fraction of precipitation falling as snow, SF), and peak snow water equivalent (SWE). Each variable represents different information about snow, and this comparison assesses similarities and differences between the snow metrics. Next, we evaluated how two snow variables, SP and SWE, related to annual streamflow (Q) for 119 USGS reference watersheds and examined whether these relationships varied for wet/warm (precipitation surplus) and dry/cold (precipitation deficit) watersheds. Results showed high correlations between all snow variables, but the slopes of these relationships differed between climates, with wet/warm watersheds displaying lower SF and higher SWE for the same SP. In dry/cold watersheds, both SP and SNODAS SWE correlated with Q spatially across all watersheds and over time within individual watersheds. We conclude that SP can be used to map spatial patterns of annual streamflow generation in dry/cold parts of the region. Applying this approach to the Upper Colorado River Basin demonstrates that 50% of streamflow comes from areas >3,000 masl. If the relationship between SP and Q is similar in other dry/cold regions, this approach could be used to estimate annual streamflow in ungauged basins.

Changes in Andes snow cover from MODIS data, 2000–2016

Abstract. The Andes span a length of 7000 km and are important for sustaining regional water supplies. Snow variability across this region has not been studied in detail due to sparse and unevenly distributed instrumental climate data. We calculated snow persistence (SP) as the fraction of time with snow cover for each year between 2000 and 2016 from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite sensors (500 m, 8-day maximum snow cover extent). This analysis is conducted between 8 and 36∘ S due to high frequency of cloud (> 30 % of the time) south and north of this range. We ran Mann–Kendall and Theil–Sens analyses to identify areas with significant changes in SP and snowline (the line at lower elevation where SP = 20 %). We evaluated how these trends relate to temperature and precipitation from Modern-Era Retrospective Analysis for Research and Applications-2 (MERRA2) and University of Delaware datasets and climate indices as El Niño–Southern Oscillation (ENSO), Southern Annular Mode (SAM), and Pacific Decadal Oscillation (PDO). Areas north of 29∘ S have limited snow cover, and few trends in snow persistence were detected. A large area (34 370 km2) with persistent snow cover between 29 and 36∘ S experienced a significant loss of snow cover (2–5 fewer days of snow year−1). Snow loss was more pronounced (62 % of the area with significant trends) on the east side of the Andes. We also found a significant increase in the elevation of the snowline at 10–30 m year−1 south of 29–30∘ S. Decreasing SP correlates with decreasing precipitation and increasing temperature, and the magnitudes of these correlations vary with latitude and elevation. ENSO climate indices better predicted SP conditions north of 31∘ S, whereas the SAM better predicted SP south of 31∘ S.

The importance of snow in species distribution models of arctic vegetation

Snow cover is characteristic of high‐latitude and ‐altitude ecosystems where snowpack properties regulate many ecological patterns and processes. Nevertheless, snow information is only rarely used as a predictor in species distribution models (SDMs). Methodological difficulties have been limiting both the quality and quantity of available snow information in SDMs.Here, we test whether incorporating remotely sensed snow information in baseline SDMs (using five climate‐topography‐soil variables) improves the accuracy of species occurrence and community level predictions. We use vegetation data recorded in 1200 study sites spanning a wide range of environmental conditions characteristic of mountain systems at high‐latitudes. The data consist of 273 species from three ecologically different and evolutionarily distant taxonomical groups: vascular plants, mosses, and lichens.The inclusion of the snow persistence variable significantly improved the predictive performance of the distribution and community level predictions. The improvements were constant, irrespective of the evaluation metric used or the taxonomic group in question. Snow was the most influential predictor for 36% of the species and had, on average, the second highest variable importance scores of all the environmental variables considered. Consequently, models incorporating snow data produced markedly more refined distribution maps than simpler models. Snow information should not be neglected in the construction of species distribution models where ecosystems characterized by seasonal snow cover are concerned.

Winter and summer weather modulate the demography of wild turkeys at the northern edge of the species distribution

AbstractTemperate species occupying habitats at the northern limit of their geographical distribution are limited by weather and climatic conditions. Such conditions often directly affect population dynamics, and thus, influence shifts in distribution via changes in demographic parameters. We examined this question by following three distinct populations of wild turkeys inhabiting areas exposed to a gradient of meteorological conditions at the northern limit of the species distribution. Four years of radio‐telemetry on 181 birds and monitoring of 95 nests revealed that population demographics of wild turkeys were influenced by snow depth, winter temperature and summer rainfall. During winter, survival of turkeys decreased drastically when snow depth remained >30 cm for >10 days and also decreased as temperatures got colder. In the spring, snow persistence delayed nest initiation, whereas nest survival was negatively affected by rainfall. Our findings show that the effects of critical meteorological factors such as snow and temperature can be compounded when both reach the limit of a species tolerance simultaneously.

An irreplaceability map for Tasmanian priority plant species

There is a strong need to map the relative importance of areas for nature conservation both inside and outside reserves, given increasing development pressures and ongoing threats to biodiversity. Nature conservation importance has typically been established using iterative or optimising systems which select areas to achieve explicit targets. Irreplaceability has been a concept used in many of these analyses. We calculated rarity-weighted richness values (irreplaceability scores) from reliable distributional data for all vascular plant species of conservation importance in one square kilometre grid cells covering the State of Tasmania, Australia. The spatial patterns of scores on the irreplaceability index were not strongly related to data collection intensity. Thus, our scores were reliable for most parts of the State, irrespective of survey effort, except where there were no or little survey data. Irreplaceability scores were high in places with concentrations of local endemics, on mountains with persistent snow cover, along the northern part of the coast and on the Bass Strait islands.

Establishment of Nothofagus pumilio at Upper Treelines Across a Precipitation Gradient in the Northern Patagonian Andes

ABSTRACTTrees 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.

A snow climatology of the Andes Mountains from MODIS snow cover data

ABSTRACTThis study develops a method for characterizing snow climatology in the Andes Mountains using the 8‐day maximum binary snow cover product from the Moderate Resolution Imaging Spectroradiometer sensor. The objectives are to: (1) identify regions with similar snow patterns and (2) identify snow persistence zones within these regions. Within a study area between 8° and 39°S, snow regions are defined using the (1) minimum elevation of snow cover, (2) rate of change of snow persistence with elevation, and (3) timing of the minimum elevation snow cover. In tropical latitudes (8°–23°S), snow cover is constrained to high elevations (>5000 m), and these areas have steep changes in snow persistence with elevation. Minimal differences in the elevation of snow on the east and west sides of the range suggest that temperature is a primary control on snow presence. Snow cover has minimal seasonal variability in the Tropics between 8° and 14°S, but it peaks in austral fall (March) after the wet season from 14° to 23°S. In mid‐latitudes (south of 23°S) snowline decreases in elevation with increasing latitude, and snow persistence changes with elevation are more gradual than in tropical regions. Snow cover peaks in the austral winter throughout the mid‐latitudes. Differences in elevations of snow accumulation between the east and west sides of the Andes are greatest between 28° and 37°S, where high mountain peaks produce a strong orographic effect and precipitation shadow. Within the snow regions, four snow zones are defined based on the average fraction of the year that snow persists: (1) little or no snow, (2) intermittent, (3) seasonal, and (4) permanent snow zones. Tropical latitudes have snow cover only on the highest peaks. Areas of seasonal and permanent snow zones are greatest between latitudes 28° and 37°S as a result of higher precipitation than mountains further north and higher elevations than mountains further south.

Estimation of snow and glacier melt contribution to Liddar stream in a mountainous catchment, western Himalaya: an isotopic approach

ABSTRACTSnow- and glacier-dominated catchments in the Himalayas are important sources of fresh water to more than one billion people. However, the contribution of snowmelt and glacier melt to stream flow remains largely unquantified in most parts of the Himalayas. We used environmental isotopes and geochemical tracers to determine the source water and flow paths of stream flow draining the snow- and glacier-dominated mountainous catchment of the western Himalaya. The study suggested that the stream flow in the spring season is dominated by the snowmelt released from low altitudes and becomes isotopically depleted as the melt season progressed. The tracer-based mixing models suggested that snowmelt contributed a significant proportion (5–66 %) to stream flow throughout the year with the maximum contribution in spring and summer seasons (from March to July). In 2013 a large and persistent snowpack contributed significantly (∼51 %) to stream flow in autumn (September and October) as well. The average annual contribution of glacier melt to stream flow is little (5 %). However, the monthly contribution of glacier melt to stream flow reaches up to 19 % in September during years of less persistent snow pack.

Extensive forests and persistent snow cover promote snowshoe hare occupancy in Wisconsin

Range boundaries are a manifestation of species' tolerances to environmental factors, including climate and human disturbance. As such, studying populations persisting along range boundaries can provide important insights into species' sensitivity to environmental change. Because multiple environmental influences may contribute to a range limit, studies focusing on range boundaries can guide management and conservation of these critical populations. To this end, we quantified the environmental factors associated with snowshoe hare (Lepus americanus) occurrence at their southern range limit in Wisconsin. We surveyed 199 locations across a regional southern range boundary of snowshoe hares and analyzed the data within an occupancy modeling framework to test the hypothesis that this range boundary results from an interaction between winter climate and land cover. We found that dense vegetation structure and increasing forest and snow cover duration had positive effects on snowshoe hare occupancy along their southern range boundary, supporting our prediction that a suite of abiotic factors is associated with the southerly distribution of this winter-adapted mammal. These effects were additive and we found limited support for climate–land cover interactions, forest composition, winter snow depth, or predator occurrence. Spatial predictions of occupancy using only forest and snow cover variables denote a sharp range boundary, further illustrating the importance of these variables in shaping this species distribution. Our results highlight an important vulnerability of snowshoe hares to future climate change, and options for mediating this vulnerability through the maintenance of early successional habitat and forested landscapes along their southern range boundary. © 2016 The Wildlife Society.

Variations of Annual Minimum Snow and Ice Extent over Canada and Neighboring Landmass Derived from MODIS 250-m Imagery for 2000–2014

. Snow and ice are important hydrological resources. Their minimum spatial extent over land, here referred to as annual minimum snow/ice (MSI) cover, plays a very important role as an indicator of long-term changes and baseline capacity for surface water storage. Data from Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra satellite for the period of 2000–2014 were utilized in this study. The level-2 MODIS swath imagery for bands B1 to B7 was employed and the 500-m bands B3–B7 were spatially downscaled to a 250-m swath grid. The imagery is available daily with multiple overpasses. This allows for more accurate identification of annual minimum in comparison to high-resolution imagery (e.g., Landsat, ASTER, etc.) available at much coarser temporal rates. Atmospherically corrected 10-day clear-sky composites converted into normalized surface reflectance over the warm season (April 1 to September 20) were employed to identify persistent snow and ice presence. Results were compared with our previous results derived from the MODIS Circumpolar Arctic clear-sky composites, generated for the end of melting season, and showed smaller MSI extent by 24%, on average. Produced MSI distributions were also compared with the permanent snow and ice maps available from 6 global land cover datasets: (i) Global Land Cover GLC-2000, (ii & iii) European Space Agency's (ESA) Globcover circa 2005 and 2009, (iv–vi) land cover maps derived under the ESA Climate Change Initiative (CCI) for 2000, 2005, and 2010. Significant biases were discovered between various land cover datasets and our results. For example, GLC-2000 overestimated snow/ice extent by 194% (325,400 km2) for the Canadian Arctic. The biases over the entire landmass (excluding Greenland) are 135% (3.7 × 105 km2), 113% (3.0 × 105 km2), 89% (2.2 × 105 km2), and 28% (0.8 × 105 km2) between our results and GLC-2000, ESA Globcover 2005, ESA Globcover 2009, and ESA CCI datasets, correspondingly. The derived MSI extent was compared with Randolph Glacier Inventory (RGI) 4.0 and showed much better consistency (ranging from 1% to 15%).

Transition of dominant peak flow source from snowmelt to rainfall along the Colorado Front Range: Historical patterns, trends, and lessons from the 2013 Colorado Front Range floods

AbstractThe Colorado Front Range has a large elevation gradient with deep seasonal snowpack in the mountains and limited snow accumulation in the foothills and plains. This study examines how the sources of annual peak flows (snowmelt, rainfall, mixed) change with the fraction of time snow persists on the ground, snow persistence (SP), and whether these sources have changed over time. Sources of peak flows for 20 gaging stations are estimated using a gridded rain and snow model forced with PRISM daily precipitation and both PRISM and TopoWx temperature. The mean snowmelt contribution to peak flow is highly correlated with SP (r2 = 0.86–0.90). Watersheds with SP < 0.3 (low snow, elevation <2000 m) are rainfall‐dominated, and watersheds with SP > 0.7 (persistent snow, elevation >3100 m) are mostly snowmelt‐dominated, with mixed sources between these thresholds. Rainfall runoff peak flows are possible at all elevations, but their likelihood declines with increasing SP. Rainfall runoff from an extreme storm in September 2013 produced the highest annual peaks at many stations, including some snowmelt‐dominated watersheds. Regional Kendall trend tests indicate that the contributions of snowmelt to peak flows and total annual inputs have declined in the mixed source zone. These changes may affect hydrographs, as analyses confirm that snowmelt runoff generally produces more attenuated peaks than rainfall runoff. Discrimination of peak flow source is sensitive to input data and model structure for mixed rain and snowmelt events, and both observation and modeling research are needed to help understand potential runoff changes in these conditions.

Explaining the distribution, structure and species composition of snow-patch vegetation in Tasmania, Australia

The term ‘snow patch’ indicates an area in an alpine zone with distinct vegetation because snow persists there longer than in the surrounding areas. Snow patches are a well known rare and threatened ecosystem on mainland Australia, but little is known of their distribution and vegetation in Tasmania. We describe, and determine the environmental relationships of, snow patches and their vegetation in Tasmania. There are 119 snow patches in Tasmania, covering 86 ha in toto, 43 of which have some fjaeldmark vegetation and the rest of which have a complete vegetation cover. Snow patches are confined to the taller, more continental mountains where they occur on north-east- to east-facing slopes, with the surrounding alpine vegetation usually being free of persistent snow. Their considerable floristic and structural variability relates to substrate and climate. Within Tasmania, several species are largely restricted to snow patches. The high degree of Tasmanian endemism in the snow-patch vegetation makes it distinct from the snow-patch vegetation of mainland Australia. The Tasmanian snow patches are also distinct in their environmental conditions. In Tasmania, snow does not usually persist over the winter outside the 119 snow patches. There are five floristic communities in these patches, all being distinct from those in mainland Australian snow patches. The Tasmanian snow patches merit listing as a threatened ecosystem on the basis of their distinctiveness and restricted extent.

Soil moisture response to experimentally altered snowmelt timing is mediated by soil, vegetation, and regional climate patterns

AbstractSoil moisture in seasonally snow‐covered environments fluctuates seasonally between wet and dry states. Climate warming is advancing the onset of spring snowmelt and may lengthen the summer‐dry state and ultimately cause drier soil conditions. The magnitude of either response may vary across elevation and vegetation types. We situated our study at the lower boundary of persistent snow cover and the upper boundary of subalpine forest with paired treatment blocks in aspen forest and open meadow. In treatments plots, we advanced snowmelt timing by an average of 14 days by adding dust to the snow surface during spring melt. We specifically wanted to know whether early snowmelt would increase the duration of the summer‐dry period and cause soils to be drier in the early‐snowmelt treatments compared with control plots. We found no difference in the onset of the summer‐dry state and no significant differences in soil moisture between treatments. To better understand the reasons soil moisture did not respond to early snowmelt as expected, we examined the mediating influences of soil organic matter, texture, temperature, and the presence or absence of forest. In our study, late‐spring precipitation may have moderated the effects of early snowmelt on soil moisture. We conclude that landscape characteristics, including soil, vegetation, and regional weather patterns, may supersede the effects of snowmelt timing in determining growing season soil moisture, and efforts to anticipate the impacts of climate change on seasonally snow‐covered ecosystems should take into account these mediating factors. Copyright © 2015 John Wiley & Sons, Ltd.

Snow cover, freeze‐thaw, and the retention of nutrients in an oceanic mountain ecosystem

As the climate warms, winters with less snow and therefore more soil freeze‐thaw cycles are likely to become more frequent in oceanic mountain areas. It is a concern that this might impair the soil's ability to store carbon and nutrients, and lead to increased leaching losses of dissolved C and nutrients and subsequent changes in nutrient cycling and ecosystem productivity.Through a combination of laboratory and field experiments, we studied short‐term effects of changing winter conditions on carbon and nutrient leaching from two plant‐soil systems with contrasting snow conditions (shallow/intermittent vs. deep/persistent snow). In the laboratory we exposed cores (soil and vegetation) from sites with either intermittent or persistent winter snow cover to five different freeze‐thaw scenarios of realistic frequency and duration. Additionally, we set up a transplant experiment at our field site by reciprocally transplanting soil‐plant monoliths between sites with intermittent and persistent snow. Together, the field and laboratory experiments aimed to assess how carbon and nutrient leaching was affected by both historical snow conditions and short‐term (through freeze‐thaw scenarios and transplantation) changes in snow cover and thermal conditions.Both a greater number of freeze‐thaw cycles and longer duration of sub‐zero temperatures increased carbon and nutrient leaching from incubated soil cores. Cores from sites with persistent snow generally had lower nutrient losses under control conditions, but greater losses following induced freeze‐thaw cycles than cores from intermittent snow sites. The character of the leached dissolved organic carbon (DOC) suggested fresh organic material, such as live plant roots or microbes, as the source of carbon and nutrients. Nutrient losses from the plant‐soil systems in the field were greater at sites with persistent winter snow due to greater volumes of percolating water in spring. This suggests that increasingly severe and frequent soil freeze‐thaw events in oceanic mountain ecosystems can enhance the mobilization of C, N and P in labile forms but, in the absence of water fluxes, these nutrients would remain available for in‐situ cycling. Thus, under future warmer winter conditions, increased carbon and nutrient losses from oceanic mountain ecosystems could occur if winters with little snow coincide with wet spring conditions.

Deriving Snow Cover Metrics for Alaska from MODIS

Moderate Resolution Imaging Spectroradiometer (MODIS) daily snow cover products provide an opportunity for determining snow onset and melt dates across broad geographic regions; however, cloud cover and polar darkness are limiting factors at higher latitudes. This study presents snow onset and melt dates for Alaska, portions of western Canada and the Russian Far East derived from Terra MODIS snow cover daily 500 m grid data (MOD10A1) and evaluates our method for filling data gaps caused by clouds or polar darkness. Pixels classified as cloud or no data were reclassified by: spatial filtering using neighboring pixel values; temporal filtering using pixel values for days before/after cloud cover; and snow-cycle filtering based on a time series assessment of a pixel’s position within snow accumulation, cover or melt periods. During the 2012 snow year, these gap-filling methods reduced cloud pixels from 27.7% to 3.1%. A total of 12 metrics (e.g., date of first and last snow, date of persistent snow cover and periods of intermittence) for each pixel were calculated by snow year. A comparison of MODIS-derived snow onset and melt dates with in situ observations from 244 weather stations generally showed an early bias in MODIS-derived dates and an effect of increasing cloudiness exacerbating bias. Our results show that mean regional duration of seasonal snow cover is 179–311 days/year and that snow cover is often intermittent, with 41% of the area experiencing ≥2 snow-covered periods during a snow season. Other regional-scale patterns in the timing of snow onset and melt are evident in the yearly 500 m gridded products publically available at http://static.gina.alaska.edu/NPS_products/MODIS_snow/.

Individual Variations of Winter Surface Air Temperature over Northwest and Northeast China and Their Respective Preceding Factors

AbstractBased on monthly mean surface air temperature (SAT) from 71 stations in northern China and NCEP/NCAR and NOAA-CIRES (Cooperative Institute for Research in Environmental Sciences) twentieth century reanalysis data, the dominant modes of winter SAT over northern China were explored. The results showed that there are two modes that account for a majority of the total variance over northern China. The first mode is unanimously colder (warmer) over the whole of northern China. The second mode is characterized by a dipole structure that is colder (warmer) over Northwest China (NWC) and warmer (colder) over Northeast China (NEC), accounting for a fairly large proportion of the total variance. The two components constituting the second mode, the individual variations of winter SAT over NWC and NEC and their respective preceding factors, were further investigated. It was found that the autumn SAT anomalies are closely linked to persistent snow cover anomalies over Eurasia, showing the delayed effects on wi...

Winter Management of Yearling Steers in a Grass‐Fed Beef Production System

The role of winter pasture management for beef production systems requires clarification. We designed four pasture management systems to sustain a 0.5 kg average daily gain (ADG) of spring‐born steers during fall and winter. The experiment was conducted at West Virginia University, Reedsville Experimental Farm. Treatments replicated three times on 0.81 ha grazing units included: (i) naturalized grazingland with haylage (NGH), (ii) orchardgrass (Dactylis glomerata L.) cultivated pastureland, animals moved to drylot with hay (OCD), (iii) orchardgrass cultivated pastureland with haylage (OCH), and (iv) tall fescue (Lolium arundinaceum, Schreb., Darbysh.) cultivated pastureland with haylage (TCH). Grasslands were stockpiled from August and N (84 kg ha−1) was applied to all except NGH. Grazing began in November and ended in January with a stocking density of 4.9 steers ha−1hay or haylage were fed until April. Pelleted soybean (Glycine max L.) hulls (PSH) were fed when ADG fell below 0.5 kg. Herbage disappearance was highest in TCH (1521 kg ha−1). Herbage accumulation of TCH was reduced more by dry weather during stockpiling. Differences in nutritive value between grasslands were small, as OCH and OCD had greater crude protein (CP) whereas NGH had lower CP. No differences in ADG were found between treatments; however, in 2006–2007 and 2008–2009 with early and persistent snow cover, supplementation was required, being significant in 2006–2007. Yearling steers can be maintained during winter with a combination of stockpiled and conserved forages fed to achieve gains of 0.5 kg ha−1d−1.

Tillage Management and Seasonal Effects on Denitrifier Community Abundance, Gene Expression and Structure over Winter.

Tillage effects on denitrifier communities and nitrous oxide (N2O) emissions were mainly studied during the growing season. There is limited information for the non-growing season, especially in northern countries where winter has prolonged periods with sub-zero temperatures. The abundance and structure of the denitrifier community, denitrification gene expression and N2O emissions in fields under long-term tillage regimes [no-tillage (NT) vs conventional tillage (CT)] were assessed during two consecutive winters. NT exerted a positive effect on nirK and nosZ denitrifier abundance in both winters compared to CT. Moreover, the two contrasting managements had an opposite influence on nirK and nirS RNA/DNA ratios. Tillage management resulted in different denitrifier community structures during both winters. Seasonal changes were observed in the abundance and the structure of denitrifiers. Interestingly, the RNA/DNA ratios were greater in the coldest months for nirK, nirS and nosZ. N2O emissions were not influenced by management but changed over time with two orders of magnitude increase in the coldest month of both winters. In winter of 2009-2010, emissions were mainly as N2O, whereas in 2010-2011, when soil temperatures were milder due to persistent snow cover, most emissions were as dinitrogen. Results indicated that tillage management during the growing season induced differences in denitrifier community structure that persisted during winter. However, management did not affect the active cold-adapted community structure.

Landsat-based snow persistence map for northwest Alaska

Landsat imagery for northwest Alaska from 1 February to 31 August, 1985–2011 was used to map snow persistence at high spatial resolution. We analyzed 11,645 scenes covering 505,800km2, including five Arctic National Park units and the range of the Western Arctic caribou herd (85 Landsat path/rows). A cloud mask was created using the Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS). Terrain shadows were calculated from ASTER G-DEM2 and solar incidence angle. The presence of snow cover was determined using separate Snowmap algorithms for non-shadowed and shadowed pixels. Resulting snow cover data were reformatted into 562 30×30km tiles, with an average sample size per pixel of 216 cloud-free observations. A binary classification tree was used to successfully determine the day of the year that best marked the change from snow to snow-free conditions for 99.8% of the study area. An internal consistency check evaluating the occurrence of snow-free data earlier than that day or snow data later than that day, showed that 98.7% of the land pixels were consistently classified ≥90% of the time. Comparison with MODIS end of snow season data showed an average difference of 4.2days. The snow persistence map was strongly correlated with the few SNOTEL stations in the study area (r2=0.856). Broadly, most snowmelt over the study area occurs from late April through early June, with timing delayed farther north and at higher elevations. Many local-scale snow patterns are evident in the detailed, 30-m product. The snow persistence map was co-registered to Landsat land cover mapping, creating a powerful, publicly available resource for ecosystem and land use analyses (https://irma.nps.gov/App/Reference/Profile/2203863).