Critical snow density threshold for Dall’s sheep (Ovis dalli dalli)

2018 ◽  
Vol 96 (10) ◽  
pp. 1170-1177 ◽  
Author(s):  
Kelly J. Sivy ◽  
Anne W. Nolin ◽  
Christopher L. Cosgrove ◽  
Laura R. Prugh
Keyword(s):  
Snow Depth ◽  
Animal Movement ◽  
Population Declines ◽  
Snow Density ◽  
Energetic Costs ◽  
Snow Properties ◽  
Ovis Dalli ◽  
Snow Conditions ◽  
Dall’S Sheep ◽  
Density Threshold

Snow cover can significantly impact animal movement and energetics, yet few studies have investigated the link between physical properties of snow and energetic costs. Quantification of thresholds in snow properties that influence animal movement are needed to help address this knowledge gap. Recent population declines of Dall’s sheep (Ovis dalli dalli Nelson, 1884) could be due in part to changing snow conditions. We examined the effect of snow density, snow depth, and snow hardness on sinking depths of Dall’s sheep tracks encountered in Wrangell–St. Elias National Park and Preserve, Alaska. Snow depth was a poor predictor of sinking depths of sheep tracks (R2 = 0.02, p = 0.38), as was mean weighted hardness (R2 = 0.09, p = 0.07). Across competing models, top layer snow density (0–10 cm) and sheep age class were the best predictors of track sink depths (R2 = 0.58). Track sink depth decreased with increasing snow density, and the snowpack supported the mass of a sheep above a density threshold of 329 ± 18 kg/m3 (mean ± SE). This threshold could aid interpretation of winter movement and energetic costs by animals, thus improving our ability to predict consequences of changing snowpack conditions on wildlife.

scholarly journals Seasonal influence of snow conditions on Dall’s sheep productivity in Wrangell-St Elias National Park and Preserve

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0244787
Author(s):  
Christopher L. Cosgrove ◽  
Jeff Wells ◽  
Anne W. Nolin ◽  
Judy Putera ◽  
Laura R. Prugh
Keyword(s):  
Snow Depth ◽  
National Park ◽  
Meteorological Data ◽  
Multiple Regression Model ◽  
Snow Accumulation ◽  
Population Declines ◽  
Climate Conditions ◽  
Remote Cameras ◽  
Snow Conditions ◽  
Dall’S Sheep

Dall’s sheep (Ovis dalli dalli) are endemic to alpine areas of sub-Arctic and Arctic northwest America and are an ungulate species of high economic and cultural importance. Populations have historically experienced large fluctuations in size, and studies have linked population declines to decreased productivity as a consequence of late-spring snow cover. However, it is not known how the seasonality of snow accumulation and characteristics such as depth and density may affect Dall’s sheep productivity. We examined relationships between snow and climate conditions and summer lamb production in Wrangell-St Elias National Park and Preserve, Alaska over a 37-year study period. To produce covariates pertaining to the quality of the snowpack, a spatially-explicit snow evolution model was forced with meteorological data from a gridded climate re-analysis from 1980 to 2017 and calibrated with ground-based snow surveys and validated by snow depth data from remote cameras. The best calibrated model produced an RMSE of 0.08 m (bias 0.06 m) for snow depth compared to the remote camera data. Observed lamb-to-ewe ratios from 19 summers of survey data were regressed against seasonally aggregated modelled snow and climate properties from the preceding snow season. We found that a multiple regression model of fall snow depth and fall air temperature explained 41% of the variance in lamb-to-ewe ratios (R2 = .41, F(2,38) = 14.89, p<0.001), with decreased lamb production following deep snow conditions and colder fall temperatures. Our results suggest the early establishment and persistence of challenging snow conditions is more important than snow conditions immediately prior to and during lambing. These findings may help wildlife managers to better anticipate Dall’s sheep recruitment dynamics.

Zonation des conditions d'enneigement en toundra forestière, Baie d'Hudson, Nouveau-Québec

1975 ◽  
Vol 53 (10) ◽  
pp. 1021-1030 ◽  
Author(s):  
Serge Payette ◽  
Jacques Ouzilleau ◽  
Louise Filion
Keyword(s):  
Picea Glauca ◽  
Snow Depth ◽  
Black Spruce ◽  
Ground Cover ◽  
Climatic Conditions ◽  
Snow Density ◽  
Forest Tundra ◽  
Snow Properties ◽  
Latitudinal Pattern ◽  
Snow Conditions

Data on snow depth and snow density of various forest–tundra coniferous stands are presented in this paper. A latitudinal pattern in snow conditions is observed in the forest–tundra environment, as predicted from the facts that are obtained when this phytogeographical region is subdivided, firstly, into a forested subzone in the southern part and a shrub subzone (or krummholz) in the northern part and, secondly, into a maritime ecoclimatic area near Hudson Bay and a continental ecoclimatic area inland. The most snowy coniferous stands are located in the shrub subzone; snow density rises gradually from the taiga to the tundra. The highest values in snow properties are found in the maritime ecoclimatic area. These data suggest the following observations: (1) maximum snow depth measured in the northern part of the forest–tundra is explained by an increase of barren ground cover and by the presence of more open coniferous stands, which favor snow drifting and snow trapping; (2) the gradual increase in snow density is related to more rigorous climatic conditions; wind exposure is rather important since these sites are getting more open; and (3) the differences in snow conditions between the ecoclimatic areas show that the maritime environment is more windy; the presence of scattered and erected white spruce (Picea glauca (Moench) Voss) in various krummholz formations in that area favors more efficient snow traps than those of krummholz formations located in the continental area. The latter is dominated by prostrate and erect black spruce (Picea mariana (Mill.) BSP.) always densely agglomerated. The latitudinal pattern in snow conditions reflects the climatic conditions of the forest–tundra, and this determines the specific ecological distribution of coniferous stands.

Effect of altered snow conditions on decomposition in three subalpine plant communities

2014 ◽  
Vol 9 (8) ◽  
pp. 811-822 ◽  
Author(s):  
Miroslav Zeidler ◽  
Martin Duchoslav ◽  
Marek Banaš
Keyword(s):  
Soil Temperature ◽  
Vegetation Type ◽  
Vegetation Types ◽  
Snow Density ◽  
Cellulose Decomposition ◽  
Snow Properties ◽  
Melting Period ◽  
Spatio Temporal ◽  
Snow Conditions

AbstractSnow cover and its spatio-temporal changes play a crucial role in the ecological functioning of mountains. Some human activities affecting snow properties may cause shifts in the biotic components of ecosystems, including decomposition. However, these activities remain poorly understood in subalpine environments. We explored the effect of human-modified snow conditions on cellulose decomposition in three vegetation types. Snow density, soil temperature, and the decomposition of cellulose were studied in Athyrium, Calamagrostis, and Vaccinium vegetation types, comparing stands intersected by groomed ski slope and natural (outside the ski slope) stands. Increased snow density caused the deterioration of snow insulation and decreased the soil temperature inside the ski slope only slightly in comparison with that outside the ski slope in all vegetation types studied. The decomposition was apparently lower in Athyrium vegetation relative to the other vegetation types and strongly (Athyrium vegetation) to weakly lower (other vegetation types) in groomed than in ungroomed stands. Wintertime, including the melting period, was decisive for overall decomposition. Our results suggest that differences in decomposition are influenced by ski slope operations and vegetation type. Alterations in snow conditions appeared to be subtle and long-term but with important consequences for conservation management.

scholarly journals Habitat selection by Dall’s sheep is influenced by multiple factors including direct and indirect climate effects

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248763
Author(s):  
Jocelyn L. Aycrigg ◽  
Adam G. Wells ◽  
Edward. O. Garton ◽  
Buck Magipane ◽  
Glen E. Liston ◽  
...  
Keyword(s):  
Habitat Selection ◽  
Resource Selection ◽  
Thermal Conditions ◽  
Population Declines ◽  
Energetic Costs ◽  
Changing Climate ◽  
Ecological Requirements ◽  
Resource Pulses ◽  
Nutritional Needs ◽  
Dall’S Sheep

Arctic and boreal environments are changing rapidly, which could decouple behavioral and demographic traits of animals from the resource pulses that have shaped their evolution. Dall’s sheep (Ovis dalli dalli) in northwestern regions of the USA and Canada, survive long, severe winters and reproduce during summers with short growing seasons. We sought to understand the vulnerability of Dall’s sheep to a changing climate in Lake Clark National Park and Preserve, Alaska, USA. We developed ecological hypotheses about nutritional needs, security from predators, energetic costs of movement, and thermal shelter to describe habitat selection during winter, spring, and summer and evaluated habitat and climate variables that reflected these hypotheses. We used the synoptic model of animal space use to estimate parameters of habitat selection by individual females and calculated likelihoods for ecological hypotheses within seasonal models. Our results showed that seasonal habitat selection was influenced by multiple ecological requirements simultaneously. Across all seasons, sheep selected steep rugged areas near escape terrain for security from predators. During winter and spring, sheep selected habitats with increased forage and security, moderated thermal conditions, and lowered energetic costs of movement. During summer, nutritional needs and security influenced habitat selection. Climate directly influenced habitat selection during the spring lambing period when sheep selected areas with lower snow depths, less snow cover, and higher air temperatures. Indirectly, climate is linked to the expansion of shrub/scrub vegetation, which was significantly avoided in all seasons. Dall’s sheep balance resource selection to meet multiple needs across seasons and such behaviors are finely tuned to patterns of phenology and climate. Direct and indirect effects of a changing climate may reduce their ability to balance their needs and lead to continued population declines. However, several management approaches could promote resiliency of alpine habitats that support Dall’s sheep populations.

scholarly journals Spatial and Temporal Variation of Bulk Snow Properties in North Boreal and Tundra Environments Based on Extensive Field Measurements

2016 ◽  
Author(s):  
H.-R. Hannula ◽  
J. Lemmetyinen ◽  
A. Kontu ◽  
C. Derksen ◽  
J. Pulliainen
Keyword(s):  
Land Cover ◽  
Snow Depth ◽  
Field Measurements ◽  
Northern Taiga ◽  
Spatial And Temporal Variation ◽  
Snow Properties ◽  
Spatial Frequencies ◽  
Forested Areas ◽  
Snow Conditions ◽  
Airborne Sar

Abstract. In this paper, an extensive dataset of snow in situ measurements, collected in support of airborne SAR-acquisitions in Sodankylä and Saariselkä test sites in northern Finland, is used to analyse the heterogeneity of bulk snow properties (snow depth, density and water equivalent) over different land cover types in northern taiga and tundra areas. In addition, the applicability of different spatial frequencies of snow sampling to estimate the true snow conditions is investigated. Overall, the highest variability in bulk snow properties was found over sparsely vegetated land cover groups, but the scale of variation was smaller in forested areas, as these areas exhibited a low correlation length in snow depth. This implies that more frequent measurements should be executed in forested (~ every < 5 m) than in open areas (~ every 7.5–12.5 m) to catch the true variability in snow depth. The results also indicated that the current spatial resolutions of space borne microwave radiometers and radars used for the remote retrieval of bulk snow properties are all well above the limit to fully describe the spatial variation of e.g. snow depth even in open areas. This conclusion supports the demand of research investigating high-resolution parameter retrieval in remote sensing of snow, e.g. using advanced SAR techniques.

scholarly journals Using next generation sequencing of alpine plants to improve fecal metabarcoding diet analysis for Dall’s sheep

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Kelly E. Williams ◽  
Damian M. Menning ◽  
Eric J. Wald ◽  
Sandra L. Talbot ◽  
Kumi L. Rattenbury ◽  
...  
Keyword(s):  
Sequence Data ◽  
Vascular Plant ◽  
Alpine Plants ◽  
Diet Analysis ◽  
Reference Sequence ◽  
Reference Library ◽  
Ovis Dalli ◽  
Plant Animal Interactions ◽  
Dall’S Sheep ◽  
Northwestern North America

Abstract Objectives Dall’s sheep (Ovis dalli dalli) are important herbivores in the mountainous ecosystems of northwestern North America, and recent declines in some populations have sparked concern. Our aim was to improve capabilities for fecal metabarcoding diet analysis of Dall’s sheep and other herbivores by contributing new sequence data for arctic and alpine plants. This expanded reference library will provide critical reference sequence data that will facilitate metabarcoding diet analysis of Dall’s sheep and thus improve understanding of plant-animal interactions in a region undergoing rapid climate change. Data description We provide sequences for the chloroplast rbcL gene of 16 arctic-alpine vascular plant species that are known to comprise the diet of Dall’s sheep. These sequences contribute to a growing reference library that can be used in diet studies of arctic herbivores.

Superovulation in Dall's sheep (Ovis dalli dalli)

1990 ◽  
Vol 33 (1) ◽  
pp. 201 ◽  
Author(s):  
B.C. Buckrell ◽  
C.J. Gartley ◽  
K.G. Mehren ◽  
K.L. Goodrowe
Keyword(s):  
Ovis Dalli ◽  
Dall’S Sheep

scholarly journals Theoretical framework for estimating snow distribution through point measurements

2015 ◽  
Vol 9 (1) ◽  
pp. 1-44
Author(s):  
E. Trujillo ◽  
M. Lehning
Keyword(s):  
Snow Depth ◽  
Survey Design ◽  
Spatial Location ◽  
Theoretical Framework ◽  
Statistical Properties ◽  
Spatial Covariance ◽  
Sample Mean ◽  
Snow Properties ◽  
Survey Designs

Abstract. In recent years, marked improvements in our knowledge of the statistical properties of the spatial distribution of snow properties have been achieved thanks to improvements in measuring technologies (e.g. LIDAR, TLS, and GPR). Despite of this, objective and quantitative frameworks for the evaluation of errors and extrapolations in snow measurements have been lacking. Here, we present a theoretical framework for quantitative evaluations of the uncertainty of point measurements of snow depth when used to represent the average depth over a profile section or an area. The error is defined as the expected value of the squared difference between the real mean of the profile/field and the sample mean from a limited number of measurements. The model is tested for one and two dimensional survey designs that range from a single measurement to an increasing number of regularly-spaced measurements. Using high-resolution (~1 m) LIDAR snow depths at two locations in Colorado, we show that the sample errors follow the theoretical behavior. Furthermore, we show how the determination of the spatial location of the measurements can be reduced to an optimization problem for the case of the predefined number of measurements, or to the designation of an acceptable uncertainty level to determine the total number of regularly-spaced measurements required to achieve such error. On this basis, a series of figures are presented that can be used to aid in the determination of the survey design under the conditions described, and under the assumption of prior knowledge of the spatial covariance/correlation properties. With this methodology, better objective survey designs can be accomplished, tailored to the specific applications for which the measurements are going to be used. The theoretical framework can be extended to other spatially distributed snow variables (e.g. SWE) whose statistical properties are comparable to those of snow depth.

scholarly journals Validation of modeled snow properties in Afghanistan, Pakistan, and Tajikistan

2019 ◽  
Author(s):  
Edward H. Bair ◽  
Karl Rittger ◽  
Jawairia A. Ahmad ◽  
Doug Chabot
Keyword(s):  
Snow Depth ◽  
Snow Water Equivalent ◽  
Median Number ◽  
In Situ Measurements ◽  
Snow Properties ◽  
Wide Range ◽  
Spatial Estimates ◽  
Snow Water ◽  
Critical Layers

Abstract. Ice and snowmelt feed the Indus and Amu Darya rivers, yet there are limited in situ measurements of these resources. Previous work in the region has shown promise using snow water equivalent (SWE) reconstruction, which requires no in situ measurements, but validation has been a problem until recently when we were provided with daily manual snow depth measurements from Afghanistan, Tajikistan, and Pakistan by the Aga Khan Agency for Habitat (AKAH). For each station, accumulated precipitation and SWE were derived from snow depth using the SNOWPACK model. High-resolution (500 m) reconstructed SWE estimates from the ParBal model were then compared to the modeled SWE at the stations. The Alpine3D model was then used to create spatial estimates at 25 km to compare with estimates from other snow models. Additionally, the coupled SNOWPACK and Alpine3D system has the advantage of simulating snow profiles, which provide stability information. Following previous work, the median number of critical layers and percentage of facets across all of the pixels containing the AKAH stations was computed. For SWE at the point scale, the reconstructed estimates showed a bias of −42 mm (−19 %) at the peak. For the coarser spatial SWE estimates, the various models showed a wide range, with reconstruction being on the lower end. For stratigraphy, a heavily faceted snowpack is observed in both years, but 2018, a dry year, according to most of the models, showed more critical layers that persisted for a longer period.

On the Values and Variability of Degree-Day Melting Factor in Finland

1980 ◽  
Vol 11 (5) ◽  
pp. 235-242 ◽  
Author(s):  
Esko Kuusisto
Keyword(s):  
Open Field ◽  
Snow Depth ◽  
Canopy Cover ◽  
Snow Density ◽  
Density Measurements ◽  
Seasonal Course ◽  
Degree Day ◽  
Forest Sites ◽  
Cent Increase

About 96,000 snow depth and 17,000 snow density measurements were used to study the most widely used variable in snowmelt forecasting, the degree-day factor. This data was collected on 12 stake stations each with 25 stakes in forest and 9 on open field during 1959 to 1978. The seasonal averages of degree-day factor are studied; they vary rather widely from station to station. The average for all forest sites is 2.42 mm°dC−1d−1 and for all open sites 3.51 mm°C−1d−1. A 10 per cent increase of canopy cover in forest decreases the degree-day factor on the average by 0.16 mm°C−1d−1. On rainy pentades the degree-day factor is larger especially in forest sites. Finally, the seasonal course of the degree-day factor and its dependance on snow density are discussed.

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