The responses of early foliar litter humification to reduced snow cover during winter in an alpine forest

2014 ◽  
Vol 94 (4) ◽  
pp. 453-461 ◽  
Author(s):  
Xiangyin Ni ◽  
Wanqin Yang ◽  
Han Li ◽  
Liya Xu ◽  
Jie He ◽  
...  
Keyword(s):  
Climate Change ◽  
Mass Loss ◽  
Soil Carbon ◽  
Snow Cover ◽  
Southwestern China ◽  
Snow Melt ◽  
Abies Faxoniana ◽  
Alpine Forest ◽  
Mass Losses ◽  
Litterbag Experiment

Ni, X., Yang, W., Li, H., Xu, L., He, J., Tan, B. and Wu, F. 2014. The responses of early foliar litter humification to reduced snow cover during winter in an alpine forest. Can. J. Soil Sci. 94: 453–461. Snow cover can be reduced by ongoing winter warming in alpine biomes, affecting foliar litter humification, but few reports are available. To quantitatively clarify how early foliar litter humification responds to reduced snow cover in winter, a field litterbag experiment was conducted in an alpine forest in southwestern China. Mass losses, ΔlogK, E4/E6, degrees of humification and humification rates of six typical local foliar litters were investigated at the snow formation, snow cover and snow melt stage under snowpack levels differing in depth (deep snowpack, medium snowpack, thin snowpack, no snowpack) from November 2012 to April 2013. The results indicated that 14–15% of willow (Salix paraplesia), 8–9% of fir (Abies faxoniana), 6–7% of birch (Betula albo-sinensis), 5–8% of cypress (Sabina saltuaria), larch (Larix mastersiana) and azalea (Rhododendron lapponicum) foliar litter was humified, which was about 50% of what decomposed during the first winter. Moreover, the early humification of foliar litter (except for fir and birch) responded positively to the reduced snow cover, but mass loss exhibited negative responses. Such results suggest that reduced snow cover in winter would increase soil carbon or other material sequestration in the scenario of climate change.

scholarly journals Climate Change Scenarios and Effects on Snow-Melt Runoff

2020 ◽  
Vol 6 (9) ◽  
pp. 1715-1725 ◽  
Author(s):  
Safieh Javadinejad ◽  
Rebwar Dara ◽  
Forough Jafary
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Annual Runoff ◽  
Hydrologic Model ◽  
Climate Change Scenarios ◽  
Snow Melt ◽  
Snowmelt Runoff ◽  
Rcp Scenarios ◽  
Temperature And Precipitation ◽  
Spring Runoff

Climate change is an important environmental issue, as progression of melting glaciers and snow cover is sensitive to climate alteration. The aim of this research was to model climate alterations forecasts, and to assess potential changes in snow cover and snow-melt runoff under the different climate change scenarios in the case study of the Zayandeh-rud River Basin. Three cluster models for climate change (NorESM1-M, IPSL-CM5A-LR and CSIRO-MK3.6.0) were applied under RCP 8.5, 4.5 and 2.6 scenarios, to examine climate influences on precipitation and temperature in the basin. Temperature and precipitation were determined for all three scenarios for four periods of 2021-2030, 2031-2040, 2041-2050 and 2051-2060. MODIS (MOD10A1) was also applied to examine snow cover using temperature and precipitation data. The relationship between snow-covered area, temperature and precipitation was used to forecast future snow cover. For modeling future snow melt runoff, a hydrologic model of SRM was used including input data of precipitation, temperature and snow cover. The results indicated that all three RCP scenarios lead to an increase in temperature, and reduction in precipitation and snow cover. Investigation in snowmelt runoff throughout the observation period (November 1970 to May 2006) showed that most of annual runoff is derived from snow melting. Maximum snowmelt runoff is generated in winter. The share of melt water in the autumn and spring runoff is estimated at 35 and 53%, respectively. The results of this study can assist water manager in making better decisions for future water supply.

Effect of seasonal snow cover on litter decomposition in alpine forest

2013 ◽  
Vol 37 (4) ◽  
pp. 296-305 ◽  
Author(s):  
Qi-Qian WU ◽  
Fu-Zhong WU ◽  
Wan-Qin YANG ◽  
Zhen-Feng XU ◽  
Wei HE ◽  
...  
Keyword(s):  
Snow Cover ◽  
Litter Decomposition ◽  
Seasonal Snow ◽  
Alpine Forest ◽  
Seasonal Snow Cover

Fullerene-like Nanoparticles of WS2 as a Promising Protection from Erosive Wear of Gun Bore Nozzles

2020 ◽  
Vol 16 (1) ◽  
pp. 62-70 ◽  
Author(s):  
Narimane Rezgui ◽  
Danica Simić ◽  
Choayb Boulahbal ◽  
Dejan Micković
Keyword(s):  
Mass Loss ◽  
Solid Lubricant ◽  
Erosive Wear ◽  
Mechanical Resistance ◽  
Protective Function ◽  
Protective Layers ◽  
Total Mass Loss ◽  
Mass Losses ◽  
Before And After ◽  
Tube Life

Background: Erosive wear causes increase in the bore diameter of firearms barrels and nozzles. Most responsible factors for this erosion are friction and heat generated during the shot. Protection from erosive wear is very important for gun tube life cycle, and various protection methods are used: adding phlegmatizers in gunpowder composition or applying protective layers on the gun bore inner surface. Objective: In this research, a possibility is examined to protect the surface of a nozzle exposed to gunpowder erosion applying a layer of tungsten disulfide fullerene-like nanoparticles, IF-WS2, known as outstanding solid lubricant of a great mechanical resistance. Methods: Nanoparticles on the nozzle surface before and after the gunfire tests were observed using scanning electron microscopy/energy dispersive X-ray spectroscopy. Gunfire tests were performed on designed erosion device. Temperatures in the defined position near the affected surface were measured with thermocouples and compared for the nozzles with and without nanoprotection, as well as the nozzle mass loss after each round. Results: For the sample with IF-WS2 lower temperatures after firing and lower mass losses were observed. Mass loss after first round was 25.6% lower for the sample with protective nanoparticles layer, and the total mass loss was about 5% lower after five rounds. After the first round the nozzle without IF-WS2 was heated up to a temperature which was for 150.8°C higher than the nozzle with IF-WS2. Conclusion: Protective function of IF-WS2 is the most pronounced for the first round. The observed results encourage its further application in firearms gun bores protection.

scholarly journals Mass occurrence and habitat selection of Common Redpolls (Carduelis flammea) after a large seed crop year: snow-covered ground facilitates food access

2021 ◽  
Author(s):  
Svein Dale
Keyword(s):  
Climate Change ◽  
Habitat Selection ◽  
Snow Cover ◽  
Breeding Season ◽  
Boreal Forests ◽  
Large Seed ◽  
Mass Occurrence ◽  
Seed Crops ◽  
Ecosystem Changes ◽  
Selection Of

AbstractIn boreal forests, food supplies typically have cyclic variations, and many species here fluctuate in numbers from year to year. One group of species showing large variations in population size is birds specialized on seeds from masting trees. Here, I analyze spatial patterns of a mass occurrence and habitat selection of the Common Redpoll (Carduelis flammea) during the breeding season in southeastern Norway in 2020 after a year with large seed crops from Norway Spruce (Picea abies) and Downy Birch (Betula pubescens). I found that Common Redpoll numbers increased with elevation and towards the northwest. Numbers were also strongly and positively correlated with snow depth in early April when snow was present mainly above 400 m elevation. Sites with snow cover in early April (30% of all sites) held 96.4% of all individuals recorded. Field observations indicated that Common Redpolls foraged extensively for spruce seeds on the snow until the end of May when young were independent. I suggest that the mass occurrence was due to a unique combination of exceptionally large seed crops of two tree species coinciding in the same year. The masting produced large amounts of food both for overwintering (birch seeds) and for breeding (spruce seeds), and during the breeding season snow cover facilitated access to food resources. Dependency of Common Redpolls on snow cover suggests that climate change may negatively impact some seed-eaters in boreal regions. On the other hand, higher temperatures may induce more frequent masting which may be beneficial for seed-eaters. Thus, climate change is likely to lead to complex ecosystem changes in areas where snow cover may disappear.

Spatial variability of topsoil δ13C across Qinghai-Tibet Plateau

2021 ◽  
Author(s):  
Yunsen Lai ◽  
Shaoda Li ◽  
Xiaolu Tang ◽  
Xinrui Luo ◽  
Liang Liu ◽  
...  
Keyword(s):  
Climate Change ◽  
Machine Learning ◽  
Spatial Variability ◽  
Soil Carbon ◽  
Tibet Plateau ◽  
Learning Approach ◽  
Carbon Turnover ◽  
Machine Learning Approach ◽  
Qinghai Tibet Plateau ◽  
Soil Carbon Turnover

<p>Soil carbon isotopes (δ<sup>13</sup>C) provide reliable insights at the long-term scale for the study of soil carbon turnover and topsoil δ<sup>13</sup>C could well reflect organic matter input from the current vegetation. Qinghai-Tibet Plateau (QTP) is called “the third pole of the earth” because of its high elevation, and it is one of the most sensitive and critical regions to global climate change worldwide. Previous studies focused on variability of soil δ<sup>13</sup>C at in-site scale. However, a knowledge gap still exists in the spatial pattern of topsoil δ<sup>13</sup>C in QTP. In this study, we first established a database of topsoil δ<sup>13</sup>C with 396 observations from published literature and applied a Random Forest (RF) algorithm (a machine learning approach) to predict the spatial pattern of topsoil δ<sup>13</sup>C using environmental variables. Results showed that topsoil δ<sup>13</sup>C significantly varied across different ecosystem types (p < 0.05).  Topsoil δ<sup>13</sup>C was -26.3 ± 1.60 ‰ for forest, 24.3 ± 2.00 ‰ for shrubland, -23.9 ± 1.84 ‰ for grassland, -18.9 ± 2.37 ‰ for desert, respectively. RF could well predict the spatial variability of topsoil δ<sup>13</sup>C with a model efficiency (pseudo R<sup>2</sup>) of 0.65 and root mean square error of 1.42. The gridded product of topsoil δ<sup>13</sup>C and topsoil β (indicating the decomposition rate of soil organic carbon, calculated by δ<sup>13</sup>C divided by logarithmically converted SOC) with a spatial resolution of 1000 m were developed. Strong spatial variability of topsoil δ<sup>13</sup>C was observed, which increased gradually from the southeast to the northwest in QTP. Furthermore, a large variation was found in β, ranging from -7.87 to -81.8, with a decreasing trend from southeast to northwest, indicating that carbon turnover rate was faster in northwest QTP compared to that of southeast. This study was the first attempt to develop a fine resolution product of topsoil δ<sup>13</sup>C for QTP using a machine learning approach, which could provide an independent benchmark for biogeochemical models to study soil carbon turnover and terrestrial carbon-climate feedbacks under ongoing climate change.</p>

The optical behaviour of snow during a melting season at Ny Ålesund (Svalbard, Norway)

2021 ◽  
Author(s):  
Roberto Salzano ◽  
Christian Lanconelli ◽  
Giulio Esposito ◽  
Marco Giusto ◽  
Mauro Montagnoli ◽  
...  
Keyword(s):  
Climate Change ◽  
Snow Cover ◽  
Full Range ◽  
Time Lapse ◽  
Test Site ◽  
Remotely Sensed ◽  
Optical Behaviour ◽  
Remotely Sensed Data ◽  
Snow Cover Area ◽  
Significant Information

<p><span>Polar areas are the most sensitive targets of </span><span>the </span><span>climate change and the continuous monitoring of the cryosphere represents a critical issue. The satellite remote sensing can fill this gap but further integration between remotely-sensed multi-spectral images and field data is crucial to validate retrieval algorithms and climatological models. The optical behaviour of snow, at different wavelengths, provides significant information about the micro-physical characteristics of the surface and this allow to discriminate different snow/ice covers. The aim of this work is to present an approach based on combining unmanned observations on spectral albedo and on the analysis of time-lapse images of sky and ground conditions in a</span><span>n </span><span>Ar</span><span>c</span><span>tic </span><span>test-site </span><span>(Svalbard, Norway). Terrestrial photography can provide, in fact, important information about the cloud cover and support the discrimination between white-sky or clear-sky illuminating conditions. Similarly, time-lapse cameras can provide a detailed description of the snow cover, estimating the fractional snow cover area. The spectral albedo was obtained by a narrow band device that was compared to a full-range commercial system and to remotely sensed data acquired during the 2015 spring/summer period at the </span><span>Amundsen - Nobile</span><span> Climate Change Tower (Ny </span><span>Å</span><span>lesund). The results confirmed the possibility to have continuous observations of the snow surface (microphisical) characteristics and highlighted the opportunity to monitor the spectral variations of snowed surfaces during the melting period. It was possible, </span><span>therefore,</span><span> to estimate spectral indexes, such as NDSI and SWIR albedo, and to found interesting links between both features and air/ground temperatures, wind-speed and precipitations. Different melting phases were detected and different processes were associated with the observed spectral variations.</span></p>

Subsoil organic carbon turnover is dominantly controlled by soil properties in grasslands across China

2021 ◽  
Author(s):  
Yuehong Shi ◽  
Xiaolu Tang ◽  
Peng Yu ◽  
Li Xu ◽  
Guo Chen ◽  
...  
Keyword(s):  
Climate Change ◽  
Organic Carbon ◽  
Soil Properties ◽  
Soil Carbon ◽  
Carbon Turnover ◽  
Area Index ◽  
Important Indicator ◽  
Environmental Controls ◽  
Biogeochemical Models ◽  
Soc Stock

<p>Soil carbon turnover time (τ, year) is an important indicator of soil carbon stability, and a major factor in determining soil carbon sequestration capacity. Many studies investigated τ in the topsoil or the first meter underground, however, little is known about subsoil τ (0.2 – 1.0 m) and its environmental drivers, while world subsoils below 0.2 m accounts for the majority of total soil organic carbon (SOC) stock and may be as sensitive as that of the topsoil to climate change. We used the observations from the published literatures to estimate subsoil τ (the ratio of SOC stock to net primary productivity) in grasslands across China and employed regression analysis to detect the environmental controls on subsoil τ. Finally, structural equation modelling (SEM) was applied to identify the dominant environmental driver (including climate, vegetation and soil). Results showed that subsoil τ varied greatly from 5.52 to 702.17 years, and the mean (± standard deviation) subsoil τ was 118.5 ± 97.8 years. Subsoil τ varied significantly among different grassland types that it was 164.0 ± 112.0 years for alpine meadow, 107.0 ± 47.9 years for alpine steppe, 177.0 ± 143.0 years for temperate desert steppe, 96.6 ± 88.7 years for temperate meadow steppe, 101.0 ± 75.9 years for temperate typical steppe. Subsoil τ significantly and negatively correlated (p < 0.05) with vegetation index, leaf area index and gross primary production, highlighting the importance of vegetation on τ. Mean annual temperature (MAT) and precipitation (MAP) had a negative impact on subsoil τ, indicating a faster turnover of soil carbon with the increasing of MAT or MAP under ongoing climate change. SEM showed that soil properties, such as soil bulk density, cation exchange capacity and soil silt, were the most important variables driving subsoil τ, challenging our current understanding of climatic drivers (MAT and MAP) controlling on topsoil τ, further providing new evidence that different mechanisms control topsoil and subsoil τ. These conclusions demonstrated that different environmental controls should be considered for reliable prediction of soil carbon dynamics in the top and subsoils in biogeochemical models or earth system models at regional or global scales.</p>

Experiments on wind-driven heat exchange processes over melting snow

2021 ◽  
Author(s):  
Michael Haugeneder ◽  
Tobias Jonas ◽  
Dylan Reynolds ◽  
Michael Lehning ◽  
Rebecca Mott
Keyword(s):  
Snow Cover ◽  
Surface Wind ◽  
Infrared Camera ◽  
Snow Accumulation ◽  
Internal Boundary ◽  
Small Scale ◽  
Snow Melt ◽  
Two Dimensional ◽  
Atmospheric Conditions ◽  
Near Surface

<p>Snowmelt runoff predictions in alpine catchments are challenging because of the high spatial variability of t<span>he snow cover driven by </span>various snow accumulation and ablation processes. In spring, the coexistence of bare and snow-covered ground engages a number of processes such as the enhanced lateral advection of heat over partial snow cover, the development of internal boundary layers, and atmospheric decoupling effects due to increasing stability at the snow cover. The interdependency of atmospheric conditions, topographic settings and snow coverage remains a challenge to accurately account for these processes in snow melt models.<br>In this experimental study, we used an Infrared Camera (VarioCam) pointing at thin synthetic projection screens with negligible heat capacity. Using the surface temperature of the screen as a proxy for the air temperature, we obtained a two-dimensional instantaneous measurement. Screens were installed across the transition between snow-free and snow-covered areas. With IR-measurements taken at 10Hz, we capture<span> the dynamics of turbulent temperature fluctuations</span><span> </span>over the patchy snow cover at high spatial and temporal resolution. From this data we were able to obtain high-frequency, two-dimensional windfield estimations adjacent to the surface.</p><p>Preliminary results show the formation of a stable internal boundary layer (SIBL), which was temporally highly variable. Our data suggest that the SIBL height is very shallow and strongly sensitive to the mean near-surface wind speed. Only strong gusts were capable of penetrating through this SIBL leading to an enhanced energy input to the snow surface.</p><p>With these type of results from our experiments and further measurements this spring we aim to better understand small scale energy transfer processes over patch snow cover and it’s dependency on the atmospheric conditions, enabling to improve parameterizations of these processes in coarser-resolution snow melt models.</p>

Glaciohydrology of the Himalaya-Karakoram

Science ◽  
2021 ◽  
pp. eabf3668
Author(s):  
Mohd. Farooq Azam ◽  
Jeffrey S. Kargel ◽  
Joseph M. Shea ◽  
Santosh Nepal ◽  
Umesh K. Haritashya ◽  
...  
Keyword(s):  
Climate Change ◽  
Water Resources ◽  
Current Status ◽  
Snow Melt ◽  
Resources Management ◽  
Critical Knowledge ◽  
Glacier Melt ◽  
Sustainable Water Resources Management ◽  
The Himalaya ◽  
Sustainable Water Resources

Understanding the response of Himalayan-Karakoram (HK) rivers to climate change is crucial for ~1 billion people who partly depend on these water resources. Policymakers tasked with the sustainable water resources management for agriculture, hydropower, drinking, sanitation, and hazards require an assessment of rivers’ current status and potential future changes. This review demonstrates that glacier and snow melt are important components of HK rivers, with greater hydrological importance for the Indus than Ganges and Brahmaputra basins. Total river runoff, glacier melt, and seasonality of flow are projected to increase until the 2050s, with some exceptions and large uncertainties. Critical knowledge gaps severely affect modeled contributions of different runoff components, future runoff volumes and seasonality. Therefore, comprehensive field- and remote sensing-based methods and models are needed.

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