scholarly journals Effects of Mid-winter Snow Depth on Stand Selection by Wolverines, Gulo gulo luscus, in the Boreal Forest

2004 ◽  
Vol 118 (1) ◽  
pp. 56 ◽  
Author(s):  
Jonathan D. Wright ◽  
Jessica Ernst
Keyword(s):  
Boreal Forest ◽  
Snow Depth ◽  
Detrimental Effect ◽  
Timber Harvesting ◽  
Limiting Factor ◽  
Gulo Gulo ◽  
Buffering Effect ◽  
Conservation Implications ◽  
Winter Snow ◽  
Stand Type

Wolverines (Gulo gulo luscus) in a study area in the boreal upland forests of northwestern Alberta and northeastern British Columbia (approximately 57°N) were noted to be limited to upland landscapes, despite abundant food in adjacent lowland landscapes. Snow-tracking suggested that the species was selecting for the densest climax conifer stands for travel in search of food. It was hypothesized that snow depth was a limiting factor for Wolverines in the boreal forest during midwinter, and that they selected for this stand-type because of the buffering effect of this type of canopy on ground snow-depths. A series of snow-depth measurements were collected. Snow depths collected along Wolverine trails were very significantly lower than random snow depths collected under upland canopy (F = 32.84, df = 1, P << 0.010). There was a significant buffering effect on snow depth indicated for upland canopy (F = 11.1, df = 1, P < 0.010), while adjacent lowland canopy had no significant buffering effect on snow depth (F = 3.45, df = 1, P > 0.05). Wolverines were hypothesized to be limited to upland landscapes in the study area because of the buffering effect on snow-depth of the stand types found there, and not for reasons of food availability. Climax conifer stands were interpreted as being of high importance to Wolverine survival during winter. Conservation implications include the detrimental effect on Wolverine populations likely to result from current timber harvesting practices in the boreal forest.

scholarly journals Wolverine, Gulo gulo luscus, Resting Sites and Caching Behavior in the Boreal Forest

2004 ◽  
Vol 118 (1) ◽  
pp. 61 ◽  
Author(s):  
Jonathan D. Wright ◽  
Jessica Ernst
Keyword(s):  
Boreal Forest ◽  
Populus Tremuloides ◽  
Black Spruce ◽  
Timber Harvesting ◽  
Gulo Gulo ◽  
Feeding Site ◽  
Resting Sites ◽  
Conservation Implications ◽  
Spruce Stands ◽  
Good Visibility

Wolverine (Gulo gulo luscus) caches and resting sites were examined in a study area in the boreal upland forests of northwestern Alberta and northeastern British Columbia (approximately 57°N). Cache sites were in climax, or “overmature” stands of Black Spruce (Picea mariana) or mixed-wood of high complexity, dominated by conifers, and in which the Trembling Aspen (Populus tremuloides) and Balsam Poplar (Populus balsamifera) component consisted of mostly dead or dying trees characteristic of such old growth in the boreal uplands. Sites offered relatively good visibility of the surrounding stand. Sites were never located in the dense to extremely dense homogenous spruce stands documented as being favored for travel by Wolverines in the study area. The better used cache complexes were accessed by numerous well-used trails made by the Wolverines themselves. Caches consisted of the bones, hide and hair of Moose (Alces alces) believed to have been killed by Grey Wolves (Canis lupus). Caches were classified as “simple caches” composed of a single feeding site and/or excavation and “cache complexes” involving one or more feeding “stations”, latrines, resting sites, and climbing trees that may have been used as avenues of escape from competitors/predators. Resting sites were located atop the snow in relatively open locations that offered good visibility of the surroundings. Climax stands were implicated as being of importance to Wolverine caching behavior. Conservation implications include the detrimental effect on Wolverine populations likely to result from current timber harvesting practices in the boreal forest.

Impacts of 1.5 °C and 2 °C global warming on winter snow depth in Central Asia

2019 ◽  
Vol 651 ◽  
pp. 2866-2873 ◽  
Author(s):  
Yun Li ◽  
Hui Tao ◽  
Buda Su ◽  
Zbigniew W. Kundzewicz ◽  
Tong Jiang
Keyword(s):  
Global Warming ◽  
Central Asia ◽  
Snow Depth ◽  
Winter Snow

scholarly journals Effects of Winter Snow Cover on Spring Soil Moisture Based on Remote Sensing Data Product over Farmland in Northeast China

2020 ◽  
Vol 12 (17) ◽  
pp. 2716
Author(s):  
Shuang Liang ◽  
Xiaofeng Li ◽  
Xingming Zheng ◽  
Tao Jiang ◽  
Xiaojie Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Soil Moisture ◽  
Linear Regression ◽  
Snow Cover ◽  
Snow Depth ◽  
Northeast China ◽  
Regression Models ◽  
Linear Regression Models ◽  
Winter Snow ◽  
The Relationship

Spring soil moisture (SM) is of great importance for monitoring agricultural drought and waterlogging in farmland areas. While winter snow cover has an important impact on spring SM, relatively little research has examined the correlation between winter snow cover and spring SM in great detail. To understand the effects of snow cover on SM over farmland, the relationship between winter snow cover parameters (maximum snow depth (MSD) and average snow depth (ASD)) and spring SM in Northeast China was examined based on 30 year passive microwave snow depth (SD) and SM remote-sensing products. Linear regression models based on winter snow cover were established to predict spring SM. Moreover, 4 year SD and SM data were applied to validate the performance of the linear regression models. Additionally, the effects of meteorological factors on spring SM also were analyzed using multiparameter linear regression models. Finally, as a specific application, the best-performing model was used to predict the probability of spring drought and waterlogging in farmland in Northeast China. Our results illustrated the positive effects of winter snow cover on spring SM. The average correlation coefficient (R) of winter snow cover and spring SM was above 0.5 (significant at a 95% confidence level) over farmland. The performance of the relationship between snow cover and SM in April was better than that in May. Compared to the multiparameter linear regression models in terms of fitting coefficient, MSD can be used as an important snow parameter to predict spring drought and waterlogging probability in April. Specifically, if the relative SM threshold is 50% when spring drought occurs in April, the prediction probability of the linear regression model concerning snow cover and spring SM can reach 74%. This study improved our understanding of the effects of winter snow cover on spring SM and will be beneficial for further studies on the prediction of spring drought.

Opportunities and costs of intensification and clustering of forest management activities

2008 ◽  
Vol 38 (4) ◽  
pp. 711-720 ◽  
Author(s):  
Anne-Hélène Mathey ◽  
Emina Krcmar ◽  
John Innes ◽  
Ilan Vertinsky
Keyword(s):  
Forest Management ◽  
Boreal Forest ◽  
Timber Harvesting ◽  
Conservation Areas ◽  
Intensive Forest Management ◽  
Trade Offs ◽  
Planning Approach ◽  
Increasing Demand ◽  
Canadian Boreal Forest ◽  
The Cost

The intensification of forest management in Canada has been advocated as a possible solution to the conundrum that increasing demand for conservation areas and increasing pressure for timber production have created. The benefits and disadvantages of intensive forest management in the context of the Canadian boreal forest are unclear and reaching conclusions about its general value from stand analyses may be difficult. In this study, a boreal forest in Ontario has been used to investigate the potential of intensive management to generate financial revenues and meet management constraints on volume flow and old-growth retention. Two aspects of intensive forest management are considered: intensive silviculture and concentrated harvest activities. The plans are generated with a decentralized planning approach based on cellular automata. The results for the case study show that increasing silviculture intensity can help fulfill high timber flow requirements under strict conservation requirements. This comes at the cost of reduced net revenues but from a smaller timber harvesting landbase. The main trade-offs found were those between harvest flow and financial benefits. Clustering both protected areas and harvest operations could help achieve the conservation and timber-related objectives simultaneously by improving the habitat value of conserved areas and decreasing the operational costs in harvested areas.

Genetic Variability of Wolverines (Gulo gulo) from the Northwest Territories, Canada: Conservation Implications

2000 ◽  
Vol 81 (1) ◽  
pp. 186-196 ◽  
Author(s):  
G. M. Wilson ◽  
R. A. Van Den Bussche ◽  
P. K. Kennedy ◽  
A. Gunn ◽  
K. Poole
Keyword(s):  
Genetic Variability ◽  
Northwest Territories ◽  
Gulo Gulo ◽  
Conservation Implications

Change in winter snow depth and its impacts on vegetation in China

2010 ◽  
pp. no-no ◽  
Author(s):  
SHUSHI PENG ◽  
SHILONG PIAO ◽  
PHILIPPE CIAIS ◽  
JINGYUN FANG ◽  
XUHUI WANG
Keyword(s):  
Snow Depth ◽  
Winter Snow

Factors influencing permafrost temperatures across tree line in the uplands east of the Mackenzie Delta, 2004–20101This article is one of a series of papers published in this CJES Special Issue on the theme of Fundamental and applied research on permafrost in Canada.2Polar Continental Shelf Contribution 03611.

2012 ◽  
Vol 49 (8) ◽  
pp. 877-894 ◽  
Author(s):  
M.J. Palmer ◽  
C.R. Burn ◽  
S.V. Kokelj
Keyword(s):  
Snow Depth ◽  
Applied Research ◽  
Abrupt Change ◽  
Late Winter ◽  
Mackenzie Delta ◽  
Near Surface ◽  
Ground Temperatures ◽  
Winter Snow ◽  
Shrub Tundra ◽  
Snow Conditions

Air and near-surface ground temperatures, late-winter snow conditions, and characteristics of the vegetation cover and soil were measured across the forest–tundra transition in the uplands east of the Mackenzie Delta, Northwest Territories, in 2004–2010. Mean late-winter snow depth decreased northward from 73 cm in the subarctic boreal forest near Inuvik to 22 cm in low-shrub tundra. Annual near-surface ground temperatures decreased northward by 0.1–0.3 °C/km near the northern limit of trees, in association with an abrupt change in snow depth. The rate decreased to 0.01–0.06 °C/km in the tundra. The freezing season is twice as long as the thawing season in the region, so measured differences in the regional ground thermal regime were dominated by the contrast in winter surface conditions between forest and tundra.

scholarly journals Nanoparticles in boreal forest and coastal environment: a comparison of observations and implications of the nucleation mechanism

2009 ◽  
Vol 9 (6) ◽  
pp. 26627-26651 ◽  
Author(s):  
K. Lehtipalo ◽  
M. Kulmala ◽  
M. Sipilä ◽  
T. Petäjä ◽  
M. Vana ◽  
...  
Keyword(s):  
Boreal Forest ◽  
Pulse Height ◽  
Particle Formation ◽  
Coastal Environment ◽  
Nucleation Mechanism ◽  
Limiting Factor ◽  
Size Distributions ◽  
New Particle Formation ◽  
Particle Size Distributions ◽  
Large Molecules

Abstract. The detailed mechanism of secondary new particle formation in the atmosphere is still under debate. It is proposed that particle formation happens via activation of 1–2 nm atmospheric neutral molecular clusters and/or large molecules. Since traditional instrumentation does not reach these sizes, the hypothesis has not yet been verified. By directly measuring particle size distributions down to mobility diameters of about 1.3 nm with a pulse-height CPC we provide evidence of the nucleation mechanism in coastal environment (Mace Head, Ireland) and in boreal forest (Hyytiälä, Finland). In both places neutral sub-3 nm condensation nuclei (nano-CN) were continuously present, even when no new particle formation was detected. In Mace Head, however, the concentration of the nano-CN was far too low to account for the particle formation rates during particle bursts. Thus the results imply that on coastal sites new particle formation initiates, as proposed earlier, via homogenous nucleation from biogenic iodine vapors. In contrary, activation of pre-existing nano-CN remains a possible explanation in the boreal forest, but the observed concentrations are not the limiting factor for the particle formation events.

scholarly journals Mapping snow depth within a tundra ecosystem using multiscale observations and Bayesian methods

2016 ◽  
Author(s):  
Haruko M. Wainwright ◽  
Anna K. Liljedahl ◽  
Baptiste Dafflon ◽  
Craig Ulrich ◽  
John E. Peterson ◽  
...  
Keyword(s):  
High Precision ◽  
Snow Depth ◽  
Spatial Sampling ◽  
Multi Scale ◽  
Arctic Alaska ◽  
Winter Snow ◽  
Digital Elevation ◽  
Tundra Ecosystem ◽  
Ice Wedge ◽  
Ground Penetrating

Abstract. This paper compares and integrates different strategies to characterize the variability of end-of-winter snow depth and its relationship to topography in ice-wedge polygon tundra of Arctic Alaska. Snow depth was measured using in situ snow depth probes, and estimated using ground penetrating radar (GPR) surveys and the Photogrammetric Detection and Ranging (PhoDAR) technique with an unmanned aerial system (UAS). We found that GPR data provided high-precision estimates of snow depth (RMSE = 2.9 cm), with a spatial sampling of 10 cm along transects. UAS-based approaches provided snow depth estimates in a less laborious manner compared to GPR and probing while yielding a high precision (RMSE = 6.0 cm) and a fine spatial sampling (4 cm by 4 cm). We then investigated the spatial variability of snow depth and its correlation to micro- and macrotopography using the snow-free LiDAR digital elevation map (DEM) and the wavelet approach. We found that the end-of-winter snow depth was highly variable over short (several meter) distances, and the variability was correlated with microtopography. Microtopographic lows (i.e., troughs and centers of low-centered polygons) were filled in with snow, which resulted in a smooth and even snow surface following macrotopography. We developed and implemented a Bayesian approach to integrate the snow-free LiDAR DEM and multi-scale measurements (probe and GPR) as well as the topographic correlation for estimating snow depth over the landscape. Our approach led to high precision estimates of snow depth (RMSE = 6.0 cm), at 0.5-meter resolution and over the LiDAR domain (750 m by 700 m).

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