Spring Snowpack Research Articles

Climatic variation allows montane willows to escape an adaptive trade-off.

Adaptive responses to climate change, based on heritable variation in stress tolerance, may be important for plant population persistence. It is unclear which populations will mount the strongest future adaptive responses. It may be fruitful to identify populations that have escaped trade-offs among performance traits, which can hinder adaptation. Barring strong genetic constraints, the extent of trade-offs may depend on spatial relationships among climate variables shaping different traits. Here, we test for climate-driven ecotypic variation and trade-offs among drought and freezing sensitivity, and growth, for Lemmon's willow (Salix lemmonii) in a common garden study of 90 genotypes from 38 sites in the Sierra Nevada, USA. Salix lemmonii exhibits ecotypic variation in leaf turgor loss point, a measure of drought sensitivity, from -0.95 to -0.74 MPa along a gradient of spring snowpack. We also find variation in spring freezing sensitivity with minimum May temperature. However, we find no trade-off, as the climatic gradients shaping these traits are spatially uncorrelated in our study region, despite being negatively correlated across the Sierra Nevada. Species may escape adaptive trade-offs in geographic regions where climate variables are spatially decoupled. These regions may represent valuable reservoirs of heritable adaptive phenotypic variation.

Illuminating Snow Droughts: The Future of Western United States Snowpack in the SPEAR Large Ensemble

AbstractSeasonal snowpack in the Western United States (WUS) is vital for meeting summer hydrological demands, reducing the intensity and frequency of wildfires, and supporting snow‐tourism economies. While the frequency and severity of snow droughts (SD), that is, anomalously low snowpacks, are expected to increase under continued global warming, the uncertainty from internal climate variability remains challenging to quantify with observations alone. Using a 30‐member large ensemble from a state‐of‐the‐art global climate model, the Seamless System for Prediction and EArth System Research (SPEAR), and an observations‐based data set, we find WUS SD changes are already significant. By 2100, SPEAR projects SDs to be nearly 9 times more frequent under shared socioeconomic pathway 5‐8.5 (SSP5‐8.5) and 5 times more frequent under SSP2‐4.5, compared to a 1921–2011 average. By investigating the influence of the two primary drivers of SD, temperature and precipitation amount, we find the average WUS SD will become warmer and wetter. To assess how these changes affect future summer water availability, we track late winter and spring snowpack across WUS watersheds, finding differences in the onset time of a “no‐snow” threshold between regions and large internal variability within the ensemble that are both on the order of decades. We attribute the inter‐regional variability to differences in the regions' mean winter temperature and the intra‐regional variability to irreducible internal climate variability which is not well‐explained by temperature variations alone. Despite strong scenario forcing, internal climate variability will continue to drive variations in SD and no‐snow conditions through 2100.

Warm places, warm years, and warm seasons increase parasitizing of moose by winter ticks

AbstractObserved links between parasites, such as ticks, and climate change have aroused concern for human health, wildlife population dynamics, and broader ecosystem effects. The one‐host life history of the winter tick (Dermacentor albipictus) links each annual cohort to environmental conditions during three specific time periods when they are predictably vulnerable: spring detachment from hosts, summer larval stage, and fall questing for hosts. We used mixed‐effects generalized linear models to investigate the drivers of tick loads carried by moose (Alces alces) relative to these time periods and across 750 moose, 10 years, and 16 study areas in the western United States. We tested for the effects of biotic factors (moose density, shared winter range, vegetation, migratory behavior) and weather conditions (temperature, snow, humidity) during each seasonal period when ticks are vulnerable and off‐host. We found that warm climatic regions, warm seasonal periods across multiple partitions of the annual tick life cycle, and warm years relative to long‐term averages each contributed to increased tick loads. We also found important effects of snow and other biotic factors such as host density and vegetation. Tick loads in the western United States were, on average, lower than those where tick‐related die‐offs in moose populations have occurred recently, but loads carried by some individuals may be sufficient to cause mortality. Lastly, we found interannual variation in tick loads to be most correlated with spring snowpack, suggesting this environmental component may have the highest potential to induce change in tick load dynamics in the immediate future of this region.

Hit Snooze: An Imperiled Hibernator Assesses Spring Snow Conditions to Decide Whether to Terminate Hibernation or Reenter Torpor.

AbstractMany animals follow annual cycles wherein physiology and behavior change seasonally. Hibernating mammals undergo one of the most drastic seasonal alterations of physiology and behavior, the timing of which can have significant fitness consequences. The environmental cues regulating these profound phenotypic changes will heavily influence whether hibernators acclimate and ultimately adapt to climate change. Hence, identifying the cues and proximate mechanisms responsible for hibernation termination timing is critical. Northern Idaho ground squirrels (Urocitellus brunneus)-a rare, endemic species threatened with extinction-exhibit substantial variation in hibernation termination phenology, but it is unclear what causes this variation. We attached geolocators to free-ranging squirrels to test the hypothesis that squirrels assess surface conditions in spring before deciding whether to terminate seasonal heterothermy or reenter torpor. Northern Idaho ground squirrels frequently reentered torpor following a brief initial emergence from hibernacula and were more likely to do so earlier in spring or when challenged by residual snowpack. Female squirrels reentered torpor when confronted with relatively shallow snowpack upon emergence, whereas male squirrels reentered torpor in response to deeper spring snowpack. This novel behavior was previously assumed to be physiologically constrained in male ground squirrels by testosterone production required for spermatogenesis and activated by the circannual clock. Assessing surface conditions to decide when to terminate hibernation may help buffer these threatened squirrels against climate change. Documenting the extent to which other hibernators can facultatively alter emergence timing by reentering torpor after emergence will help identify which species are most likely to persist under climate change.

The timing of reproduction is responding plastically, not genetically, to climate change in yellow-bellied marmots (Marmota flaviventer).

With global climates changing rapidly, animals must adapt to new environmental conditions with altered weather and phenology. The key to adapting to these new conditions is adjusting the timing of reproduction to maximize fitness. Using a long-term dataset on a wild population of yellow-bellied marmots (Marmota flaviventer) at the Rocky Mountain Biological Laboratory (RMBL), we investigated how the timing of reproduction changed with changing spring conditions over the past 50 years. Marmots are hibernators with a 4-month active season. It is thus crucial to reproduce early enough in the season to have time to prepare for hibernation, but not too early, as snow cover prevents access to food. Importantly, climate change in this area has, on average, increased spring temperatures by 5°C and decreased spring snowpack by 50 cm over the past 50 years. We evaluated how female marmots adjust the timing of their reproduction in response to changing conditions and estimated the importance of both microevolution and plasticity in the variation in this timing. We showed that, within a year, the timing of reproduction is not as tightly linked to the date a female emerges from hibernation as previously thought. We reported a positive effect of spring snowpack but not of spring temperature on the timing of reproduction. We found inter-individual variation in the timing of reproduction, including low heritability, but not in its response to changing spring conditions. There was directional selection for earlier reproduction since it increased the number and proportion of pups surviving their first winter. Taken together, the timing of marmot reproduction might evolve via natural selection; however, plastic changes will also be extremely important. Further, future studies on marmots should not operate under the assumption that females reproduce immediately following their emergence.

Spring Snowpack Influences on the Volume and Timing of Spring and Peak-Season Overnight Visitation to Yosemite Wilderness

Abstract Wilderness visitation, particularly overnight use, is reactive to climate variability because backpackers face greater exposure to and dependence on environmental conditions. This study examines the effect that spring snowpack had on the timing and volume of permits issued for overnight use of the Yosemite Wilderness during peak and shoulder-season months (April–October) from 2002 to 2019. We categorize 1 April snowpack at Tuolumne Meadows into snow drought (<75%), high snowpack (>125%), and near-average snowpack (75%–125%). Results confirm wilderness-wide differences between snowpack categories, including change in spring overnight visitors (April–June: +20% snow drought and −28% high snowpack). Our findings confirm that snow drought allows for more access to high-elevation trailheads when seasonal roads are open earlier in spring (May–June: +74% Tioga Road and +81% Tuolumne Meadows). Mid- to high-elevation trailheads experience a sustained increase in use during high-snowpack years (June–October: +12% Yosemite Valley and Big Oak Flat; +15% Glacier Point Road and Wawona; +32% Hetch Hetchy) because a narrower seasonal access window leads to filled permit quotas in the high country and displaces use to lower-elevation trailheads. These findings have implications for wilderness stewards, including biophysical and experiential impacts on wilderness character from earlier and longer seasons, especially at higher elevation and in fragile alpine and subalpine areas, as snow drought in mountain-protected areas becomes more common. Recommendations to address greater early-season use and its attendant impacts include adaptively managing permits for different types of snowpack years, including potential changes in the number, timing, and destination of select trailhead quotas.

Selection processes of Arctic seasonal glacier snowpack bacterial communities

BackgroundArctic snowpack microbial communities are continually subject to dynamic chemical and microbial input from the atmosphere. As such, the factors that contribute to structuring their microbial communities are complex and have yet to be completely resolved. These snowpack communities can be used to evaluate whether they fit niche-based or neutral assembly theories.MethodsWe sampled snow from 22 glacier sites on 7 glaciers across Svalbard in April during the maximum snow accumulation period and prior to the melt period to evaluate the factors that drive snowpack metataxonomy. These snowpacks were seasonal, accumulating in early winter on bare ice and firn and completely melting out in autumn. Using a Bayesian fitting strategy to evaluate Hubbell’s Unified Neutral Theory of Biodiversity at multiple sites, we tested for neutrality and defined immigration rates at different taxonomic levels. Bacterial abundance and diversity were measured and the amount of potential ice-nucleating bacteria was calculated. The chemical composition (anions, cations, organic acids) and particulate impurity load (elemental and organic carbon) of the winter and spring snowpack were also characterized. We used these data in addition to geographical information to assess possible niche-based effects on snow microbial communities using multivariate and variable partitioning analysis.ResultsWhile certain taxonomic signals were found to fit the neutral assembly model, clear evidence of niche-based selection was observed at most sites. Inorganic chemistry was not linked directly to diversity, but helped to identify predominant colonization sources and predict microbial abundance, which was tightly linked to sea spray. Organic acids were the most significant predictors of microbial diversity. At low organic acid concentrations, the snow microbial structure represented the seeding community closely, and evolved away from it at higher organic acid concentrations, with concomitant increases in bacterial numbers.ConclusionsThese results indicate that environmental selection plays a significant role in structuring snow microbial communities and that future studies should focus on activity and growth.A4vcHcKNh9Gahh9Z6pYiCtVideo

Summer ecosystem structure in mountain lakes linked to interannual variability of lake ice, snowpack, and landscape attributes

AbstractMountain lakes experience interannual variability in spring snowpack and ice cover that can lead to differences in physical, chemical, and biological properties in the succeeding summer. Lake studies that capture extreme years of snow and ice would be useful to understand and anticipate effects of climate change, but such data are rare for remote mountain lakes. Monitoring of lakes in Olympic, North Cascades, and Mount Rainier National Parks from 2007 to 2018 allowed us to examine limnological differences along interannual and elevation‐driven climate gradients that included unusually high (2011–2012) and 100‐yr record low (2015) snowpack years. Years with lower spring snowpack had earlier ice‐out. Across lakes, our analysis suggested an average of 0.075°C lake warming per day of lost ice duration (0.525°C per week), giving rise to other ecosystem changes linked to temperature such as lower dissolved oxygen, higher total dissolved N, higher chlorophyll, and higher abundance of cladoceran zooplankton. Conversely, in years with higher snowpack and a shorter ice‐free season, lakes were colder and clearer (1 m deeper Secchi depth for every 1 m May snow water equivalent), with more dilute ions as well as lower algal biomass and zooplankton abundance. These results add to evidence that changes in snowpack or ice‐out dates alter mountain lake ecology through multiple processes associated with hydrology, terrestrial‐aquatic connection, water temperature, productivity, ion composition, and plankton communities.

Transient Effects of Snow Cover Duration on Primary Growth and Leaf Traits in a Tundra Shrub.

With the recent climate warming, tundra ecotones are facing a progressive acceleration of spring snowpack melting and extension of the growing season, with evident consequences to vegetation. Along with summer temperature, winter precipitation has been recently recognised as a crucial factor for tundra shrub growth and physiology. However, gaps of knowledge still exist on long-living plant responses to different snowpack duration, especially on how intra-specific and year-to-year variability together with multiple functional trait adjustments could influence the long-term responses. To fill this gap, we conducted a 3 years snow manipulation experiment above the Alpine treeline on the typical tundra species Juniperus communis, the conifer with the widest distributional range in the north emisphere. We tested shoot elongation, leaf area, stomatal density, leaf dry weight and leaf non-structural carbohydrate content of plants subjected to anticipated, natural and postponed snowpack duration. Anticipated snowpack melting enhanced new shoot elongation and increased stomatal density. However, plants under prolonged snow cover seemed to compensate for the shorter growing period, likely increasing carbon allocation to growth. In fact, these latter showed larger needles and low starch content at the beginning of the growing season. Variability between treatments slightly decreased over time, suggesting a progressive acclimation of juniper to new conditions. In the context of future warming scenarios, our results support the hypothesis of shrub biomass increase within the tundra biome. Yet, the picture is still far from being complete and further research should focus on transient and fading effects of changing conditions in the long term.

Large‐diameter trees affect snow duration in post‐fire old‐growth forests

AbstractSnow duration in post‐fire forests is influenced by neighbourhoods of trees, snags, and deadwood. We used annually resolved, spatially explicit tree and tree mortality data collected in an old‐growth, mixed‐conifer forest in the Sierra Nevada, California, that burned at low to moderate severity to calculate 10 tree neighbourhood metrics for neighbourhoods up to 40 m from snow depth and snow disappearance sampling points. We developed two linear mixed models, predicting snow disappearance timing as a function of tree neighbourhood, litter density, and simulated incoming solar radiation, and two multiple regression models explaining variation in snow depth as a function of tree neighbourhood. Higher densities of post‐fire large‐diameter snags within 10 m of a sampling point were related to higher snow depth (indicating reduced snow interception). Higher densities of large‐diameter trees within 5 m and larger amounts of litter were associated with shorter snow duration (indicating increased longwave radiation emittance and accelerated snow albedo decay). However, live trees with diameters >60 cm within 10 m of a snow disappearance sampling point were associated with a longer‐lasting spring snowpack. This suggests that, despite the local effects of canopy interception and emitted longwave radiation from boles of large trees, shading from their canopies may prolong snow duration over a larger area. Therefore, conservation of widely spaced, large‐diameter trees is important in old‐growth forests because they are resistant to fire and can enhance the seasonal duration of snowmelt.

Altitudinal Gradient Characteristics of Spatial and Temporal Variations of Snowpack in the Changbai Mountain and Their Response to Climate Change

The variations in the snowpack in water towers of the world due to climate change have threatened the amount and timing of freshwater supplied downstream. However, it remains to be further investigated whether snowpack variation in water towers exhibits elevational heterogeneity at different altitude gradients and which climatic factors mainly influence these differences. Therefore, Changbai Mountain, a high-latitude water tower, was selected to analyze the changes in the snowpack by the methods of modified Mann–Kendall based on the daily meteorological data from the China Meteorological Data Service Centre. Meanwhile, the responses of snowpack change to climatic factors over recent decades were assessed and generalized using additive models. The results showed that the snow depth was greater in the higher altitude areas than in the lower elevation areas at different times. Areas with a snow depth of over 70 mm increased significantly in the 2010s. Increasing trends were shown at different altitudes from December to March of the next year during 1960~2018. However, a significant decreasing trend was shown in April, except for altitudes of 600–2378 m. The snow cover time at different altitudes showed a trend of first increasing and then decreasing during 1960~2018. The date of maximum snow depth appears to be more lagged as the altitude increases. In addition, the spring snowpack melted significantly faster in the 2010s than that in the 1960s. The snowpack variation in low-altitude regions is mainly influenced by ET and relative humidity. However, the mean temperature gradually became an important factor, affecting the snow depth variation with the increase in altitude. Therefore, the results of this study will be beneficial to the ecological protection and sustainable development of water towers.

Let it snow? Spring snowpack and microsite characterize the regeneration niche of high‐elevation pines

AbstractAimThe persistence potential of forests under rapid climate change will depend on species‐specific tolerances to increasing growing season soil moisture stress as snowpack declines. High‐elevation tree species may be particularly vulnerable to increasing water stress and associated changes to disturbance regimes because they occur at the environmental margins of tree distributions and are considered snowpack dependent. Here, we evaluate the interacting effects of climate, disturbance, and microsite conditions on tree regeneration in high‐elevation, migration‐limited pines that have experienced recent disturbance‐induced tree mortality.LocationGreat Basin (California and Nevada), USATaxonGymnosperms; PinaceaeMethodsWe used field observations from 70 sites that varied in climate, disturbance, and local site conditions across semi‐arid, high‐elevation forests of the Great Basin. We employed structural equation models to evaluate how climate and disturbance interact with microsite conditions to influence regeneration.ResultsWe found a broad range of establishment conditions for high‐elevation conifers—whitebark, limber, and bristlecone pines—across climatic and disturbance gradients in the Great Basin, but our research detected clear differences in the regeneration niche for each species that may lead to differential survival as climate and disturbance conditions continue to change. Regeneration of whitebark and bristlecone pines diverged in their responses to spring snowpack conditions, with whitebark pine increasing and bristlecone pine decreasing with greater spring snowpack. Limber pine regenerated across a range of climatic and landscape conditions, and this generalist strategy may be advantageous if future climate and disturbance conditions exceed tolerances of more specialized high‐elevation conifers.Main ConclusionsOur findings highlight the critical role that spring snowpack, and consequently growing season soil moisture, plays in determining the persistence potential of high‐elevation conifers. However, this role varies among species and thus may drive compositional changes as earlier snowmelt drives soil moisture declines across mountainous landscapes of the western United States.

Relative snowpack response to elevation, temperature and precipitation in the Crown of the Continent region of North America 1980-2013.

Water availability in western Canada and the United States is dependent on the accumulation of snowpack in the montane regions and threatened by increased winter temperature and more precipitation as rain linked to climate change. In order to make reasoned decisions to adapt to climate change managers require knowledge of the role of temperature and precipitation in SWE development and data to distinguish the relative retention response of snowpack regions to expected temperature and precipitation regime shifts at the watershed scale. Using the Daymet interpolated 1 km2 dataset, effects of elevation, temperature (Tmax, Tmin and Tavg) and precipitation on April 1 SWE in the Crown of the Continent were tested by linear regression and Kendall correlation. Changes in Daymet estimated snow water equivalent (SWE) in response to increased temperatures and changes in precipitation were estimated in two ways: 1) comparing April 1SWE in the 11 warmest (mean Tmax February) and driest (mean precipitation January to March) years with the 22 cooler/wetter years 1981–2013 and 2) SWE retention from April 1 to June 1 over the period 1980 to 2013 across 120 watersheds in a major continental headwater region, the Crown of the Continent of North America. Historical analysis of period warm year April 1 SWE was assumed to indicate the recent impact of warmer winter temperatures. Changes in snowpack April 1 to June 1 reflected likely effects on peak runoff and were, therefore, also relevant for future climate change adaptation considerations. Winter (JFM) precipitation proved more influential than temperature in shaping April 1 SWE response at the regional scale. Of the three factors, elevation was most positively associated with April 1 SWE at the watershed scale. Temperature and precipitation influenced SWE accumulation and persistence at the watershed scale, but higher precipitation was more closely associated with higher April 1 SWE retention. Ranking of watershed snowpack retention in warm and dry years, combined with spring snowpack retention offers data to assist identification of watersheds with greatest snowpack persistence in the face of anticipated climate change effects.

Seasonal and interannual variability of melt-season albedo at Haig Glacier, Canadian Rocky Mountains

Abstract. In situ observations of summer (June through August, or JJA) albedo are presented for the period 2002–2017 from Haig Glacier in the Canadian Rocky Mountains. The observations provide insight into the seasonal evolution and interannual variability of snow and ice albedo, including the effects of summer snowfall, the decay of snow albedo through the melt season, and the potential short-term impacts of regional wildfire activity on glacier-albedo reductions. Mean JJA albedo (± 1σ) recorded at an automatic weather station in the upper ablation zone of the glacier was αS=0.55 ± 0.07 over this period, with no evidence of long-term trends in surface albedo. Each summer the surface conditions at the weather station undergo a transition from a dry, reflective spring snowpack (αS∼0.8) to a wet, homogeneous midsummer snowpack (αS∼0.5) to exposed, impurity-rich glacier ice, with a measured albedo of 0.21 ± 0.06 over the study period. The ice albedo drops to ∼ 0.12 during years of intense regional wildfire activity such as 2003 and 2017, but it recovers from this in subsequent years. This seasonal albedo decline is well simulated through a parameterization of snow-albedo decay based on cumulative positive degree days (PDDs), but the parameterization does not capture the impact of summer snowfall events, which cause transient increases in albedo and significantly reduce glacier melt. We introduce this effect through a stochastic parameterization of summer precipitation events within a surface energy balance model. The amount of precipitation and the date of snowfall are randomly selected for each model realization based on a predefined number of summer snow events. This stochastic parameterization provides an improved representation of the mean summer albedo and mass balance at Haig Glacier. We also suggest modifications to conventional degree-day melt factors to better capture the effects of seasonal albedo evolution in temperature-index or positive-degree-day melt models on mountain glaciers. Climate, hydrology, or glacier mass balance models that use these methods typically use a binary rather than continuum approach to prescribing melt factors, with one melt factor for snow and one for ice. As alternatives, monthly melt factors effectively capture the seasonal albedo evolution, or melt factors can be estimated as a function of the albedo where these data are available.

Accelerated Snowmelt Protocol to Simulate Climate Change Induced Impacts on Snowpack Dependent Ecosystems.

Field studies that simulate the effects of climate change are important for a predictive understanding of ecosystem responses to a changing environment. Among many concerns, regional warming can result in advanced timing of spring snowmelt in snowpack dependent ecosystems, which could lead to longer snow-free periods and drier summer soils. Past studies investigating these impacts of climate change have manipulated snowmelt with a variety of techniques that include manual snowpack alteration with a shovel, infrared radiation, black sand and fabric covers. Within these studies however, sufficient documentation of methods is limited, which can make experimental reproduction difficult. Here, we outline a detailed plot-scale protocol that utilizes a permeable black geotextile fabric deployed on top of an isothermal spring snowpack to induce advanced snowmelt. The method offers a reliable and cost-effective approach to induce snowmelt by passively increasing solar radiation absorption at the snow surface. In addition, control configurations with no snowpack manipulation are paired adjacent to the induced snowmelt plot for experimental comparison. Past and ongoing deployments in Colorado subalpine ecosystems indicate that this approach can accelerate snowmelt by 14-23 days, effectively mimicking snowmelt timing at lower elevations. This protocol can be applied to a variety of studies to understand the hydrological, ecological, and geochemical impacts of regional warming in snowpack dependent ecosystems.

On the causes of the summer 2015 Eastern Washington wildfires

In the summer of 2015, Eastern Washington State (east of 122°W) experienced over 2000 fires that burned a record amount of area, saw the deaths of three firefighters, and caused hazardous air quality throughout much of the region. The area burned during the 2015 fire season (∼471 000 hectares) was over three times that of the next largest year in the previous 32 years. We examine Eastern Washington’s 2015 fire season in the context of the historical fire record, which is available from satellite remote sensing observations for the past 32 years. We explore the relationship between fire activity and physical climatic factors, including temperature and precipitation, fuel characteristics, such as dry fuel moisture, historical land cover change, forest health, and fire behavior, such as ignition and propagation. Summer 2015 was anomalously warm in Eastern Washington—nearly 1 °C warmer than the previous record warm year and 1.4 °C warmer than the 32-year climatology. It followed a near-record warm winter with anomalously low spring snowpack, whereas winter precipitation in 2014–2015 was near normal. We find that the extreme 2015 fire year was not attributable to any one physical factor, but rather was related to a combination of anomalously dry and warm summer conditions, a lightning storm in mid-August, early propagation and growth through grasslands, and high grassland fuel loadings caused by anomalous growth in the preceding late winter and spring. At the local level, prediction of the anomalous 2015 burned area is not associated with any single variable; however, the combination of conditions, especially climate and fuel loads, are likely to recur in the future.

Influence of Atmospheric Rivers on Mountain Snowpack in the Western United States

In the coastal mountains of western North America, most extreme precipitation is associated with atmospheric rivers (ARs), narrow bands of moisture originating in the tropics. Here we quantify how interannual variability in atmospheric rivers influences snowpack in the western United States in observations and a model. We simulate the historical climate with the Model for Prediction Across Scales (MPAS) with physics from the Community Atmosphere Model, version 5 [CAM5 (MPAS-CAM5)], using prescribed sea surface temperatures. In the global variable-resolution domain, regional refinement (at ~30 km) is applied to our region of interest and upwind over the northeast Pacific. To better characterize internal variability, we conduct simulations with three ensemble members over 30 years of the historical period. In the Cascade Range, with some exceptions, winters with more atmospheric river days are associated with less snowpack. In California’s Sierra Nevada, winters with more ARs are associated with greater snowpack. The slope of the linear regression of observed snow water equivalent (SWE) on reanalysis-based AR count has the same sign as that arrived at using the model, but is statistically significant in observations only for California. In spring, internal variance plays an important role in determining whether atmospheric river days appear to be associated with greater or less snowpack. The cumulative (winter through spring) number of atmospheric river days, on the other hand, has a relationship with spring snowpack, which is consistent across ensemble members. Thus, the impact of atmospheric rivers on winter snowpack has a greater influence on spring snowpack than spring atmospheric rivers in the model for both regions and in California consistently in observations.

Controls on gross production in an aspen–sagebrush vegetation mosaic

AbstractThe critical zone (CZ; defined as the zone between the top of the vegetation canopy and the groundwater) mediates the impact of precipitation amount and timing on water availability and plant productivity. However, CZ structure, including soil and subsurface properties, are almost always unknown, leading to considerable uncertainty in the links between precipitation, plant water availability, and gross production. Using multiyear records of gross ecosystem CO2 exchange (GEE), micrometeorology, and streamflow, we examined the sensitivity of GEE to environmental controls in a sagebrush shrubland and an aspen forest. The sites were within 500 m of each other and had similar precipitation and temperature but marked differences in CZ structure. Cumulative growing season GEE was approximately two times greater at the aspen compared with the sagebrush, underscoring the importance of CZ properties in structuring spatial “hot spots” for carbon cycling. Larger soil water holding capacity and topography that produced lateral subsurface flow to the aspen enabled marked difference in plant functional type. Annual variability in growing season GEE within each site was not driven by annual precipitation; this lack of relationship was attributed to the CZ's limited ability to store water and an associated increase in water yield. Instead, both seasonal timing and cumulative growing season GEE for the sagebrush varied with spring and summer rain, whereas aspen GEE responded to spring snowpack conditions. These results emphasized how mapping and understanding CZ structure will help predict the spatial variability in plant functional type and temporal sensitivity of growing season GEE.

Assessment of future climate change impacts on nonpoint source pollution in snowmelt period for a cold area using SWAT

The source area of Liao River is a typical cold region in northeastern China, which experiences serious problems with agricultural nonpoint source pollution (NPS), it is important to understand future climate change impacts on NPS in the watershed. This issue has been investigated by coupling semi distributed hydrological model (SWAT), statistical downscaling model (SDSM) and global circulation model (GCMs). The results show that annual average temperature would rise by 2.1 °C (1.3 °C) in the 2080 s under scenario RCP8.5 (RCP4.5), and annual precipitation would increase by 67 mm (33 mm). The change in winter temperature and precipitation is most significant with an increase by 0.23 °C/10a (0.17 °C/10a) and 1.94 mm/10a (2.78 mm/10a). The future streamflow, TN and TP loads would decrease by 19.05% (10.59%), 12.27% (8.81%) and 10.63% (6.11%), respectively. Monthly average streamflow, TN and TP loads would decrease from March to November, and increase from December to February. This is because the increased precipitation and temperature in winter, which made the spring snowpack melting earlier. These study indicate the trends of nonpoint source pollution during the snowmelt period under climate change conditions, accordingly adaptation measures will be necessary.

Cumulative effects of climate and landscape change drive spatial distribution of Rocky Mountain wolverine (Gulo gulo L.).

Contemporary landscapes are subject to a multitude of human‐derived stressors. Effects of such stressors are increasingly realized by population declines and large‐scale extirpation of taxa worldwide. Most notably, cumulative effects of climate and landscape change can limit species’ local adaptation and dispersal capabilities, thereby reducing realized niche space and range extent. Resolving the cumulative effects of multiple stressors on species persistence is a pressing challenge in ecology, especially for declining species. For example, wolverines (Gulo gulo L.) persist on only 40% of their historic North American range. While climate change has been shown to be a mechanism of range retractions, anthropogenic landscape disturbance has been recently implicated. We hypothesized these two interact to effect declines. We surveyed wolverine occurrence using camera trapping and genetic tagging at 104 sites at the wolverine range edge, spanning a 15,000 km2 gradient of climate, topographic, anthropogenic, and biotic variables. We used occupancy and generalized linear models to disentangle the factors explaining wolverine distribution. Persistent spring snow pack—expected to decrease with climate change—was a significant predictor, but so was anthropogenic landscape change. Canid mesocarnivores, which we hypothesize are competitors supported by anthropogenic landscape change, had comparatively weaker effect. Wolverine population declines and range shifts likely result from climate change and landscape change operating in tandem. We contend that similar results are likely for many species and that research that simultaneously examines climate change, landscape change, and the biotic landscape is warranted. Ecology research and species conservation plans that address these interactions are more likely to meet their objectives.