Snowy Season Research Articles

Annual Carbon Gas Emissions from a Boreal Peatland in Continuous Permafrost Zone, Northeast China

Peatland is a significant ecosystem that has accumulated one‐third of the soil carbon in boreal regions. However, the net carbon balance, particularly with current carbon emissions, remains unclear. In this study, the annual ecosystem respiration and CH4 fluxes from a peatland located in Northeast China are reported. Ecosystem respiration fluxes from the shrub‐moss‐ and Eriophorum‐dominated communities in the peatland varied from 12 to 272 mg C m−2 h−1 during the snow‐free season, and the Eriophorum‐dominated community emitted more CO2. Rates of ecosystem respiration were strongly regulated by temperature and water table depth. The CH4 fluxes emitted from the peatland throughout a year varied with the type of the vegetation community during the snow‐free season. No distinct episodic CH4 efflux during the freeze–thaw cycles was observed from the shrub‐moss‐dominated community, whereas a subtle pulse of CH4 was found in the Eriophorum‐dominated community. The annual ecosystem respiration and CH4 fluxes from the peatland were 356 and 1.51 g C m−2 per year, respectively. The contributions of CO2 and CH4 fluxes from the snowy season to annual emissions were much lower than those found in other boreal peatlands, whereas 24% of the annual methane flux was emitted during the freeze–thaw cycles. The results highlight the importance of gaseous carbon efflux in the estimation of carbon flux from peatlands, as well as the contribution of carbon efflux during the snow‐covered season.

積雪期の被害地震の文献調査

In Japan more than half of her territory is assigned as heavy snow region and earthquakes in snowy season may cause much sever damage by snow and low temperature. The authors have been carried out literature surveys on historical earthquakes. In this paper the 1854 Ansei Tokai earthquake was surveyed in order to find snow effects in snowy region. Many snow effects can be pointed out in the snowy region which has not been revealed in details.

Canopy interception loss in a Pinus sylvestris var. mongolica forest of Northeast China

Pinus sylvestris var. mongolica is one of the main species to be afforested in deserts of China. But little work has been carried out on the canopy interception loss of this plant species. For researching the canopy interception loss of a natural P. sylvestris forest, we observed the gross precipitation, gross snowfall, throughfall and stemflow in a sample plot at the Forest Ecosystem Research Station of Mohe in the Great Khingan Mountains of Northeast China from July 2012 to September 2013. Considering the spatial variability of the throughfall, we increased the area rather than the number of collector and randomly relocated them once a week. The results demonstrated that the throughfall, stemflow, and derived estimates of rainfall and snowfall interception loss during the main rainy and snowy seasons were 77.12%±5.70%, 0.80%, 22.08%±5.51% and 21.39%±1.21% of the incident rainfall or snowfall, respectively. The stemflow didn’t occur unless the accumulated rainfall reached up to 4.8 mm. And when the gross precipitation became rich enough, the stemflow increased with increasing tree diameters. Our analysis revealed that throughfall was not observed when rainfall was no more than 0.99 mm, indicating that the canopy storage capacity at saturation was 0.99 mm for P. sylvestris forest.

不同厚度雪被对高山森林6种凋落物分解过程中酸溶性和酸不溶性组分的影响

PDF HTML阅读 XML下载 导出引用 引用提醒 不同厚度雪被对高山森林6种凋落物分解过程中酸溶性和酸不溶性组分的影响 DOI: 10.5846/stxb201311292844 作者: 作者单位: 四川农业大学生态林业研究所林业生态工程重点实验室,四川农业大学生态林业研究所林业生态工程重点实验室,四川农业大学生态林业研究所林业生态工程重点实验室,四川农业大学生态林业研究所林业生态工程重点实验室,四川农业大学生态林业研究所林业生态工程重点实验室,四川农业大学生态林业研究所林业生态工程重点实验室,四川农业大学生态林业研究所林业生态工程重点实验室 作者简介: 通讯作者: 中图分类号: 基金项目: 国家自然科学基金项目(31170423, 31270498); 国家"十二五"科技支撑计划(2011BAC09B05); 四川省杰出青年学术与技术带头人培育项目(2012JQ0008, 2012JQ0059); 中国博士后科学基金特别资助(2012T50782) Effects of snow cover on acid-soluble extractive and acid-insoluble residue during foliar litter decomposition in the alpine forest Author: Affiliation: Key Laboratory of Ecological Forestry Engineering,Institute of Ecological Forestry,Sichuan Agricultural University,Wenjiang,Key Laboratory of Ecological Forestry Engineering,Institute of Ecological Forestry,Sichuan Agricultural University,Wenjiang,Key Laboratory of Ecological Forestry Engineering,Institute of Ecological Forestry,Sichuan Agricultural University,Wenjiang,Key Laboratory of Ecological Forestry Engineering,Institute of Ecological Forestry,Sichuan Agricultural University,Wenjiang,Key Laboratory of Ecological Forestry Engineering,Institute of Ecological Forestry,Sichuan Agricultural University,Wenjiang,Key Laboratory of Ecological Forestry Engineering,Institute of Ecological Forestry,Sichuan Agricultural University,Wenjiang,Key Laboratory of Ecological Forestry Engineering,Institute of Ecological Forestry,Sichuan Agricultural University,Wenjiang Fund Project: 摘要 | 图/表 | 访问统计 | 参考文献 | 相似文献 | 引证文献 | 资源附件 | 文章评论 摘要:高山森林冬季不同厚度雪被格局可能通过影响凋落物的分解过程中酸溶性和酸不溶性组分特征,改变凋落物分解过程,但缺乏必要关注。采用凋落物分解袋法,研究了高山森林林窗中央至林下形成的天然雪被厚度梯度(厚型雪被、中型雪被、薄型雪被和无雪被)覆盖下,6 种典型物种岷江冷杉(Abies faxoniana)、红桦(Betula albo-sinensis)、四川红杉(Larix mastersiana)、方枝柏(Sabina saltuaria)、康定柳(Salix paraplesia)和高山杜鹃(Rhododendron lapponicum)凋落物在不同关键时期(雪被形成期、雪被覆盖期和雪被融化期)的酸溶性组分和酸不溶性组分变化特征。经历一个冬季的分解后,6 种凋落物酸溶性组分绝对含量呈降低趋势,除红桦外5 种凋落物酸不溶性组分绝对含量呈增加趋势。不同厚度雪被显著影响雪被覆盖期和融化期凋落物酸不溶性和酸溶性组分绝对变化量;其中方枝柏、红桦和康定柳凋落物酸不溶性组分增加量在厚型雪被下显著高于其它雪被覆盖;而相对于阔叶凋落物酸溶性组分变化量在薄型雪被和无雪被梯度达到最大值,针叶凋落物酸溶性组分在厚型雪被下具有最大的变化量。一个冬季分解结束后,表征6 种凋落物酸溶性和酸不溶性组分含量相对比例的LCI指数(Lignocellulose index)总体升高,雪被对LCI指数的影响主要表现在雪被覆盖期和融化期,且方枝柏、岷江冷杉和康定柳凋落物LCI在冬季分解后均在厚型雪被达到最高值。同时统计分析结果表明,物种极显著影响冬季不同阶段凋落物酸溶性和酸不溶性组分的变化。这些结果意味着气候变暖情景下,高山森林冬季雪被和冻融格局的改变将显著影响凋落物分解过程中酸溶性、酸不溶性组分以及LCI指数代表的抵抗性组分结构的变化,且影响趋势受到凋落物质量的调控。 Abstract:Acid-soluble extractive (ASE) and acid-insoluble residue (AIR) are two essential components in foliar litter, and play an important role in the litter decomposition. Changes in ASE and AIR concentrations are not only one of crucial processes in litter decomposition, but also run the process of mineralization and humification of organic materials in litter to a large extent. Theoretically, ASE and AIR concentrations in litter vary with tree species, precipitation, soil temperature and moisture, and other biotic and abiotic factors. In the alpine forest ecosystem, the interception of canopy on snow accumulation and the effects of canopy shading on snow ablation in winter often create a snowpack gradient on the forest floor between the center of a gap and under the forest canopy in snowy season, and in turn might give strong effects on the dynamics of ASE and AIR in litter inside and outside of the canopy gap. As yet, little information has been available on the effects of snow cover on ASE and AIR concentrations in litter at different critical periods. Therefore, litterbags with foliar litter of birch (Betula albo-sinensis), cypress (Sabina saltuaria), larch (Larix mastersiana), fir (Abies faxoniana), willow (Salix paraplesia), and azalea (Rhododendron lapponicum) were placed on the forest floor along snow over gradients (deep snow, medium snow, thin snow and none snow) created by forest gap, canopy edge, expanded edge and closed canopy in three alpine forests of eastern Tibet Plateau. The litterbags were sampled at the stages of snow formation, snow cover and snow ablation from October 2012 to April 2013, and the concentrations of ASE and AIR in sampled litter were measured in time. Meanwhile, the LCI (Lignocellulose index) was also calculated. Over the first winter of litter decomposition, the absolute ASE concentration in foliar litter continued to decline as litter decomposition proceeded regardless of plant species, while AIR concentration in foliar litter increased except for birch leaf litter. Snow cover gave significant (P<0.05) effects on ASE and AIR concentrations in foliar litter at snow cover and ablation stages regardless of plant species. Absolute AIR concentration in cypress, birch and willow litter beneath deep snowpack increased more significantly in comparison with those beneath shallow and no snowpacks. The response of ASE concentration in foliar litter to snow cover depended on plant leaf forms. The maximum changes of absolute ASE concentrations in broadleaf litter were found beneath the thin and no snowpacks, whereas those in needle litters showed the opposite trend. After a snowy season, LCI, an index of indicating the relative changes of ASE and AIR concentrations in foliar litter increased significantly (P<0.05) regardless of plant species. The effects of snowpacks on LCI in foliar litter were observed mainly at the stages of snow cover and ablation, and the foliar litter of cypress, fir and willow had the highest LCI beneath the deep snowpack. In addition, the statistical analysis revealed that the wintertime dynamics of ASE and AIR concentrations and LCI in foliar litter were influenced significantly (P<0.01) by litter quality determined by plant species. The results here imply that the changes of winter snow cover pattern as affected by winter warming and forest gap regeneration will give a strong effect on the dynamics of ASE and AIR concentrations and the relative ratios of ASE to AIR in foliar litter, and in turn alter the process of mineralizaition and humification of organic materials in the alpine forest ecosystems. However, the effects of snow cover on the dynamics of ASE and AIR concentrations also depend on litter quality related with plant species. 参考文献 相似文献 引证文献

インターバル撮影画像による積雪寒冷期の斜面変動の調査

インターバル撮影画像による積雪寒冷期の斜面変動の調査

Snow Cover Detection Based on Visible Red and Blue Channel from MODIS Imagery Data

In the present work, a new snow cover detection method based on visible red and blue bands from MODIS imagery data is proposed for Akita prefecture under the sunny cloud-free conditions. Before the snow cover detection, the MODIS imagery of the study area is pre-processed by geographic correction, clipping, atmospheric correction and topographic correction. Snow cover detection is carried out by applying the reflectance similarities of snow and other substances in the visible red band 1 and blue band 3. Then, the threshold values are confirmed to distinguish snow pixels from other substances by analyzing the composited true color images and 2-dimensional scatter plots. The MOD10_L2 products and in-situ snow depth data from 31 observation stations across the whole study area are chosen to compare and validate the effectivity of proposed method for snow cover detection. We calculate the overall accuracy, over-estimation error and under-estimation error of snow cover detection during the snowy season from May 2012 to April 2014, and the results are compared by classifying all of the observation stations into forest areas, basin areas and plain areas. It proves that the snow cover can be detected effectively in Akita prefecture by the proposed method. And the average overall accuracy of proposed method is higher than MOD10_L2 product, improved by 26.27%. The proposed method is expected to improve the environment management and agricultural development for local residents.

Homogenization of precipitation time series with ACMANT

New method for the time series homogenization of observed precipitation (PP) totals is presented; this method is a unit of the ACMANT software package. ACMANT is a relative homogenization method; minimum four time series with adequate spatial correlations are necessary for its use. The detection of inhomogeneities (IHs) is performed with fitting optimal step function, while the calculation of adjustment terms is based on the minimization of the residual variance in homogenized datasets. Together with the presentation of PP homogenization with ACMANT, some peculiarities of PP homogenization as, for instance, the frequency and seasonal variation of IHs in observed PP data and their relation to the performance of homogenization methods are discussed. In climatic regions of snowy winters, ACMANT distinguishes two seasons, namely, rainy season and snowy season, and the seasonal IHs are searched with bivariate detection. ACMANT is a fully automatic method, is freely downloadable from internet and treats either daily or monthly input. Series of observed data in the input dataset may cover different periods, and the occurrence of data gaps is allowed. False zero values instead of missing data code or physical outliers should be corrected before running ACMANT. Efficiency tests indicate that ACMANT belongs to the best performing methods, although further comparative tests of automatic homogenization methods are needed to confirm or reject this finding.

Effects of Road Deicer Runoff on Benthic Macroinvertebrate Communities in Korean Freshwaters with Toxicity Tests of Calcium Chloride (CaCl2)

We investigated the effects of road deicer runoff on benthic macroinvertebrate communities in Korean freshwaters focusing on the effects of CaCl2 deicer. Quantitative field sampling was conducted at eight sites (lakes and streams) in South Korea, and toxicity tests were conducted on 48-h lethal and effective concentrations (LC50 and EC50) of road deicer (CaCl2 74 %) and high-grade CaCl2 (96 %) on five selected macroinvertebrate species (Gammarus sobaegensis, Caridina denticulata denticulata, Glyptotendipes tokunagai, Cloeon dipterum, and Ecdyonurus levis). Although Cl− concentrations were significantly different between the seasons (before and after snowfall) at most of the study sites, community values (species richness, density, dominance index, and diversity index) were not significantly different between the seasons. In the bioassay, 2.85 g L−1 CaCl2 elicited abnormal swimming behavior of test organisms based on EC50 values. The LC50 values of the five test species ranged from 3.54 to 20.73 g L−1. For all tested species, the LC50 of road deicer was higher than that of high-grade CaCl2. This study shows that despite the heavy application of road deicers during the snowy season, the deicer may not directly affect benthic macroinvertebrate communities over short time periods because Cl− concentrations in the field sites (<0.025 g L−1) were much lower than the LC50 values. Because the quantity of deicers used in this region continues to increase, long-term research into the effects of deicers on benthic macroinvertebrates is needed.

Utilizing Microscopic Traffic and Weather Data to Analyze Real-Time Crash Patterns in the Context of Active Traffic Management

This paper investigates the effects of microscopic traffic, weather, and roadway geometric factors on the occurrence of specific crash types for a freeway. The I-70 Freeway was chosen for this paper since automatic vehicle identification (AVI) and weather detection systems are implemented along this corridor. A main objective of this paper is to expand the purpose of the existing intelligent transportation system to incorporate traffic safety improvement and suggest active traffic management (ATM) strategies by identifying the real-time crash patterns. Crashes have been categorized as rear-end, sideswipe, and single-vehicle crashes. AVI segment average speed, real-time weather data, and roadway geometric characteristic data were utilized as explanatory variables in this paper. First, binary logistic regression models were estimated to compare single- with multivehicle crashes and sideswipe with rear-end crashes. Then, a hierarchical logistic regression model that simultaneously fits two conditional logistic regression models for the three crash types has been developed. Results from the models indicate that single-vehicle crashes are more likely to occur in snowy seasons, at moderate slopes, three-lane segments, and under free-flow conditions, whereas the sideswipe crash occurrence differs from rear-end crashes with the visibility situation, segment number of lanes, grades, and their directions (up or down). Furthermore, the innovative way of estimating two conditional logistic regression models simultaneously in the Bayesian framework fits the correlated data structure well. Conclusions from this paper imply that different ATM strategies should be designed for three- and two-lane roadway sections and are also considering the seasonal effects.

Impact assessment of dam construction and forest management for Japanese macaque habitats in snowy areas

Japanese macaques (Macaca fuscata) in their northernmost habitats represent a keystone species and play a central role in heavy snowfall ecosystems. However, distributions have been restricted by pre-war hunting, and populations are facing issues of natural forest losses caused by new dam constructions and massive conifer plantations. In the present study, we predicted the influences of these environmental conditions on macaque habitats during each season, and evaluated the effect of natural forest restoration as a mitigation measure. We constructed multiple habitat suitability models on the basis of different forest change scenarios, by using maximum entropy modeling (Maxent). We predicted the influence of each scenario by calculating the habitat unit (habitat quality × habitat quantity). We made the following predictions: (1) the influences of environmental conditions on habitat models vary seasonally, but dam construction destroys the optimum macaque habitats in every season; (2) restoration of conifer plantations to semi-natural forests does not always contribute to the improvement of total habitat unit, except in snowy seasons; and (3) in comparison with encouraging natural forest restoration in plantation areas and maintaining the standard-rotation plantation management, the implementation of long-rotation plantation in existing plantation areas provides more suitable alternative habitats for macaques in non-snowy seasons.

Discrimination of Winter and Summer Tires Using Road Surface Vibration Caused by Passing Vehicles

Abstract An important role of tires is to help automobile drivers to obviate serious traffic accidents, particularly in the snowy season. In practice, the types of tires are monitored by visual inspection with human eyes. This report is concerned with the reliable detection of tire types using the vibration signals of road surface on passing vehicles. The vibration signals vary momentarily depending on several mechanisms, such as vibration impact, tire tread patterns, and so on. Then, it may be possible to passively and easily discriminate the types of tires; i.e., the least signal differences between winter and summer tires. To detect tire vibration signals from vehicles running at 30, 40, 50 and 60 km/h on average only when road surfaces were dry or wet, we used a commercially available accelerometer as a sensor, which enabled us to easily reduce cost and size in realizing a practical system for detecting tire types. To classify tires into two categories of winter and summer ones, we herein propose several effective signals, featuring a simple detection method based on the principal component analysis. From the experimental results, obtained in snowy areas, it has been demonstrated that such signal features are believed to be a potential tool for a reliable detection of the tire types by using only the vibration signals from passing vehicles.

Atlantic influence on spring snowfall over the Alps in the past 150 years

Global warming is believed to be responsible for the reduction of snow amount and duration over the Alps. In fact, a rapid shortening of the snowy season has been measured and perceived by ecosystems and society in the past 30 years, despite the large year-to-year variability. This trend is projected to continue during the 21st century in the climate change scenarios with increasing greenhouse gas concentrations. Superimposed on the long-term trend, however, there is a low-frequency variability of snowfall associated with multi-decadal changes in the large-scale circulation. The amplitude of this natural low-frequency variation might be relatively large, determining rapid and substantial changes of snowfall, as recently observed. This is already known for winter snowfall over the Alps in connection with the recent tendency toward the positive phase of the North Atlantic Oscillation. In this study, we show that the low-frequency variability of Alpine spring snowfall in the past 150 years is affected by the Atlantic Multi-decadal Oscillation (AMO), which is a natural periodic fluctuation of Northern Atlantic sea surface temperature. Therefore, the recently observed spring snowfall reduction might be, at least in part, explained by the shift toward a positive AMO phase that happened in the 1990s.

Spatial distribution and temporal trends of polycyclic aromatic hydrocarbons (PAHs) in water and sediment from Songhua River, China

The spatial and temporal distributions of polycyclic aromatic hydrocarbons (PAHs) in the Songhua River, Harbin, China, were investigated. Seventy-seven samples, 42 water and 35 sediment samples, were collected in April and October of 2007 and January of 2008. The concentrations of total PAHs in water ranged from 163.54 to 2,746.25ng/L with the average value of 934.62ng/L, which were predominated by 2- and 3-ring PAHs. The concentrations of total 16 PAHs in sediment ranged from 68.25 to 654.15ng/g dw with the average value of 234.15ng/g dw, which were predominated by 4-, 5- and 6-ring PAHs. Statistical analysis of the PAH concentrations shown that the highest concentrations of the total PAHs were found during rainy season (October of 2007) and the lowest during snowy season (January of 2008). Ratios of specific PAH compounds, including fluoranthene/(fluoranthene+pyrene) (Flu/(Flu+Pyr)) and phenanthrene/(phenanthrene+anthracene) (An/(Ant+PhA)), were calculated to evaluate the possible sources of PAH contaminations. These ratios reflected pyrolytic inputs of PAHs in Songhua River water and a mixed pattern of pyrolytic and petrogenic inputs of PAHs in the Songhua River sediments. Ecotoxicological risk levels calculated for PAHs suggested that there were individual PAHs, which can less frequently cause biological impairment in some samples, but no samples had constituents that may frequently cause biological impairment. Total toxic benzo[a]pyrene equivalent of ΣcPAHs varied from 10.03 to 29.7ng/g dw and from 0.36 to 1.92ng/g dw for total toxic tetrachlorodibenzo-p-dioxin equivalent. The level of PAHs indicated a low toxicological risk to this area.

Resource use of Japanese macaques in heavy snowfall areas: implications for habitat management

Populations of Japanese macaque (Macaca fuscata) that inhabit the northernmost distribution of any nonhuman primates have been listed as endangered in Japan; however, macaques are widely known for being pests that cause agricultural damage. This study identified priority areas for the conservation and management of macaque habitats, by comparing the resource use of troops occupying remote mountains (montane troops) against troops inhabiting disturbed forests adjacent to settlements (rural troops). We collected species presence data across 2 years by radio-tracking two montane troops and two rural troops in the Shirakami Mountains. We developed seasonal utilization distributions by using the kernel method, and identified habitat characteristics by using ecological-niche factor analysis (ENFA). Our results indicate that environmental factors influencing the potential habitat varied widely with season in montane troops as compared with that in rural troops. ENFA results demonstrated that rural troops exhibited more biased resource use and narrower niche breadths than montane troops. Based on our findings, we propose that (1) primary broadleaf forests are the spring habitat conservation priority of montane troops; (2) the habitat unit--the product of habitat suitability index and its surface area--for montane troops is enhanced by removing old conifer plantations from the forest edge at low elevations; (3) such removal around settlements may also contribute toward removing a frontline refuge for rural troops intruding farmlands; and (4) intensive prevention measures against macaque intrusions into settlements during the bottleneck snowy season contribute toward reducing the habitat unit of rural troops.

Does the Usage of a Pedometer and a Diary Improve Physical Activity during the Snowy Season?

Does the Usage of a Pedometer and a Diary Improve Physical Activity during the Snowy Season?

Determination of snow cover from MODIS data for the Tibetan Plateau region

This paper addresses a snow-mapping algorithm for the Tibetan Plateau region using Moderate Resolution Imaging Spectroradiometer (MODIS) data. Accounting for the effects of the atmosphere and terrain on the satellite observations at the top of the atmosphere (TOA), particularly in the rugged Tibetan Plateau region, the surface reflectance is retrieved from the TOA reflectance after atmospheric and topographic corrections. To reduce the effect of the misclassification of snow and cloud cover, a normalized difference cloud index (NDCI) model is proposed to discriminate snow/cloud pixels, separate from the MODIS cloud mask product MOD35. The MODIS land surface temperature (LST) product MOD11_L2 is also used to ensure better accuracy of the snow cover classification. Comparisons of the resulting snow cover with those estimated from high spatial-resolution Landsat ETM+ data and obtained from MODIS snow cover product MOD10_L2 for the Mount Everest region for different seasons in 2002, show that the MODIS snow cover product MOD10_L2 overestimates the snow cover with relative error ranging from 20.1% to 55.7%, whereas the proposed algorithm estimates the snow cover more accurately with relative error varying from 0.3% to 9.8%. Comparisons of the snow cover estimated with the proposed algorithm and those obtained from MOD10_L2 product with in situ measurements over the Hindu Kush-Himalayan (HKH) region for December 2003 and January 2004 (the snowy seasons) indicate that the proposed algorithm can map the snow cover more accurately with greater than 90% agreement.

Activity-specific evaluation of winter habitat use by Japanese macaques in snow areas, northern Japan: Implications for conifer plantation management

Monocultural conifer plantations are often recognized as low quality habitats for most mammals, owing to the scarcity of understory plants. This paper presents a multifaceted assessment of conifer plantations as habitats of Japanese macaques (Macaca fuscata) inhabiting an area of heavy snow cover in northern Japan. We evaluated habitat use by two macaque troops in cool-temperate forests, including conifer plantations, which are located in the Shirakami Mountains. Habitat use was classified into three behavioral categories; feeding, resting, and traveling. We directly observed two radio-tagged troops by using the scan sampling technique throughout the day during winter, which is the main bottleneck season in terms of food availability. At each sampling event, we recorded the location of different troops and the behavioral patterns of individuals. We then constructed suitability models for each of the three types of habitat use, by using ecological-niche factor analysis (ENFA) with 12 environmental variables. The ENFA results showed that macaques avoid old conifer plantations, but use young conifer plantations for all behavioral categories, especially as feeding sites. However, the suitability models indicated that geographic features have a larger influence on macaque habitat use than forest cover type. In fact, the feeding, resting, and traveling sites were concentrated on the southern slopes of near the roads at low altitudes. Our findings provided a reasonable indication that macaque habitat use during the snowy season has greater sensitivity to microclimate, such as the amount of sunlight and air temperature, compared to other environmental conditions (e.g., the distribution of food resources). In light of this finding, we suggest that standard timber production does not necessarily directly compete with the conservation of macaque habitats.

Assessment of Interaction of Crash Occurrence, Mountainous Freeway Geometry, Real-Time Weather, and Traffic Data

This study investigated the effect of the interaction between roadway geometric features and real-time weather and traffic data on the occurrence of crashes on a mountainous freeway. The Bayesian logistic regression technique was used to link a total of 301 crash occurrences on I-70 in Colorado with the space mean speed collected in real time from an automatic vehicle identification (AVI) system and real-time weather and roadway geometry data. The results suggested that the inclusion of roadway geometrics and real-time weather with data from an AV I system in the context of active traffic management systems was essential, in particular with roadway sections characterized by mountainous terrain and adverse weather. The modeling results showed that the geometric factors were significant in the dry and the snowy seasons and that the likelihood of a crash could double during the snowy season because of the interaction between the pavement condition and steep grades. The 6-min average speed at the crash segment during the 6 to 12 min before the crash and the visibility 1 h before the crash were found to be significant during the dry season, whereas the logarithms of the coefficient of variation in speed at the crash segment during the 6 to 12 min before the crash, the visibility 1 h before the crash, as well as the precipitation 10 min before the crash were found to be significant during the snowy season. The results from the two models suggest that different active traffic management strategies should be in place during these two distinct seasons.

Soil CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; efflux of a larch forest in northern Japan

Abstract. We had continuously measured soil CO2 efflux (Rs) in a larch forest in northern Japan at hourly intervals for the snow-free period in 2003 with an automated chamber system and partitioned Rs into heterotrophic respiration (Rh) and autotrophic respiration (Rr) by using the trench method. In addition, we applied the soil CO2 concentration gradients method to continuously measure soil CO2 profiles under snowpack in the snowy period and to partition Rs into topsoil (Oa and A horizons) CO2 efflux (Ft) with a depth of 0.13 m and sub-soil (C horizon) CO2 efflux (Fc). We found that soil CO2 effluxes were strongly affected by the seasonal variation of soil temperature but weakly correlated with soil moisture, probably because the volumetric soil moisture (30–40% at 95% confidence interval) was within a plateau region for root and microbial activities. The soil CO2 effluxes changed seasonally in parallel with soil temperature in topsoil with the peak in late summer. On the other hand, the contribution of Rr to Rs was the largest at about 50% in early summer, when canopy photosynthesis and plant growth were more active. The temperature sensitivity (Q10) of Rr peaked in June. Under snowpack, Rs was stable until mid-March and then gradually increased with snow melting. Rs summed up to 79 gC m−2 during the snowy season for 4 months. The annual Rs was determined at 934 gC m−2 y−1 in 2003, which accounted for 63% of ecosystem respiration. The annual contributions of Rh and Rs to Rs were 57% and 43%, respectively. Based on the gradient approach, Rs was partitioned vertically into litter (Oi and Oe horizons) with a depth of 0.01–0.02 m, topsoil and sub-soil respirations with proportions of 6, 72 and 22%, respectively, on an annual basis. The vertical distribution of CO2 efflux was consistent with those of soil carbon and root biomass.

Does Self-monitoring Of Daily Step Maintain Physical Activity Level In Winter At Snowy Area?

Physical activity level (PAL) is important to maintain a healthy life style. Self monitoring is supposed to be useful and important tool to maintain PAL. Previous studies have reported that PAL decreases in winter compared to other seasons, especially in snowy areas. However, there is no study whether self-monitoring may affect PAL in winter at snowy area. PURPOSE: To test whether self monitoring of PAL in winter at snowy area increases PA levels in winter, and function. METHODS: 191 female subjects aged from 40-77 years (58±8 yrs, means±SD), residing in a snowy area (Hokkadio, Japan) participated in this study. Each subject was asked to check diary and steps by pedometer through one-year. However, we did not force compliance to increase PAL in order to observe effects of only self-monitoring. International Physical activity Questionnaire (IPAQ) was surveyed and physical fitness test (side jump, step over and duck under the rope and sit-ups) were performed. Data was collected in June (baseline evaluation), pre-snowy season (November) and post-snowy season (March). RESULTS: Forty-nine subjects completed all tests through one year. Based on daily steps: subjects were divided into a well-checked group (WCG, n=25) who checked daily step counts > 1.5 months in both seasons and a poor-checked group (PCG, n=24) who checked < 1.5 month in both seasons. There were no differences in physical function between groups at baseline value. From June to November, step over and duck under the rope (19.0±5.3 vs. 17.9±4.7 sec. p<0.05) and sit-ups (13±8 vs. 15±6 reps p<0.01) were significantly improved in WCG, whereas there was no changes in PCG. From November to March, there was no change in physical function for both groups. PAL calculated by IPAQ was not different in each group between seasons and there were no significant differences in PAL at baseline and during pre-snowy season. However, PAL in snowy season of WCG was significantly higher than that of PCG (212±218 vs. 116±95 kcal; p=0.03). CONCLUSIONS: Women who self-monitor their activity maintain higher activity levels during winter months in a snowy area. This effect might be independent of physical fitness level.