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Heidi Steltzer - One of the best experts on this subject based on the ideXlab platform.
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the Snowmelt niche differentiates three microbial life strategies that influence soil nitrogen availability during and after winter
Frontiers in Microbiology, 2020Co-Authors: Patrick O Sorensen, Heidi Steltzer, Harry R Beller, Markus Bill, Nicholas J Bouskill, Susan S Hubbard, Ulas Karaoz, Alexander PolussaAbstract:Soil microbial biomass can reach its annual maximum pool size beneath the winter snowpack and is known to decline abruptly following Snowmelt in seasonally snow-covered ecosystems. Observed differences in winter versus summer microbial taxonomic composition also suggests that phylogenetically conserved traits may permit winter- versus summer-adapted microorganisms to occupy distinct niches. In this study, we sought to identify archaea, bacteria, and fungi that are associated with the soil microbial bloom overwinter and the subsequent biomass collapse following Snowmelt at a high-altitude watershed in central Colorado, United States. Archaea, bacteria, and fungi were categorized into three life strategies (Winter-Adapted, Snowmelt-Specialist, Spring-Adapted) based upon changes in abundance during winter, the Snowmelt period, and after Snowmelt in spring. We calculated indices of phylogenetic relatedness (archaea and bacteria) or assigned functional attributes (fungi) to organisms within life strategies to infer whether phylogenetically conserved traits differentiate Winter-Adapted, Snowmelt-Specialist, and Spring-Adapted groups. We observed that the soil microbial bloom was correlated in time with a pulse of Snowmelt infiltration, which commenced 65 days prior to soils becoming snow-free. A pulse of nitrogen (N, as nitrate) occurred after Snowmelt, along with a collapse in the microbial biomass pool size, and an increased abundance of nitrifying archaea and bacteria (e.g., Thaumarchaeota, Nitrospirae). Winter- and Spring-Adapted archaea and bacteria were phylogenetically clustered, suggesting that phylogenetically conserved traits allow Winter- and Spring-Adapted archaea and bacteria to occupy distinct niches. In contrast, Snowmelt-Specialist archaea and bacteria were phylogenetically overdispersed, suggesting that the key mechanism(s) of the microbial biomass crash are likely to be density-dependent (e.g., trophic interactions, competitive exclusion) and affect organisms across a broad phylogenetic spectrum. Saprotrophic fungi were the dominant functional group across fungal life strategies, however, ectomycorrhizal fungi experienced a large increase in abundance in spring. If well-coupled plant-mycorrhizal phenology currently buffers ecosystem N losses in spring, then changes in Snowmelt timing may alter ecosystem N retention potential. Overall, we observed that Snowmelt separates three distinct soil niches that are occupied by ecologically distinct groups of microorganisms. This ecological differentiation is of biogeochemical importance, particularly with respect to the mobilization of nitrogen during winter, before and after Snowmelt.
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the Snowmelt niche differentiates three microbial life strategies that influence soil nitrogen availability during and after winter
bioRxiv, 2020Co-Authors: Patrick O Sorensen, Heidi Steltzer, Harry R Beller, Markus Bill, Nicholas J Bouskill, Susan S Hubbard, Ulas Karaoz, Alexander Polussa, Shi Wang, Kenneth H WilliamsAbstract:Soil microbial biomass can reach its annual maximum pool size beneath the winter snowpack and is known to decline abruptly following Snowmelt in seasonally snow-covered ecosystems. Observed differences in winter versus summer microbial taxonomic composition also suggests that phylogenetically conserved traits may permit winter- versus summer-adapted microorganisms to occupy distinct niches. In this study, we sought to identify archaea, bacteria, and fungi that are associated with the soil microbial bloom overwinter and the subsequent biomass collapse following Snowmelt at a high-altitude watershed in central Colorado, USA. Archaea, bacteria, and fungi were categorized into three life strategies (Winter-Adapted, Snowmelt-Specialist, Spring-Adapted) based on changes in abundance during winter, the Snowmelt period, and after Snowmelt in spring. We calculated indices of phylogenetic relatedness (archaea and bacteria) or assigned functional attributes (fungi) to organisms within life strategies to infer whether phylogenetically conserved traits differentiate Winter-Adapted, Snowmelt-Specialist, and Spring-Adapted groups. We observed that the soil microbial bloom was correlated in time with a pulse of Snowmelt infiltration, which commenced 65 days prior to soils becoming snow-free. A pulse of nitrogen (N, as nitrate) occurred after Snowmelt, along with a collapse in the microbial biomass pool size, and an increased abundance of nitrifying archaea and bacteria (e.g., Thaumarchaeota, Nitrospirae). Winter- and Spring-Adapted archaea and bacteria were phylogenetically clustered, suggesting that phylogenetically conserved traits allow Winter- and Spring-Adapted archaea and bacteria to occupy distinct niches. In contrast, Snowmelt-Specialist archaea and bacteria were phylogenetically overdispersed, suggesting that the key mechanism(s) of the microbial biomass crash are likely to be density-dependent (e.g., trophic interactions, competitive exclusion) and affect organisms across a broad phylogenetic spectrum. Saprotrophic fungi were the dominant functional group across fungal life strategies, however, ectomycorrhizal fungi experienced a large increase in abundance in spring. If well-coupled plant-mycorrhizal phenology currently buffers ecosystem N losses in spring, then changes in Snowmelt timing may alter ecosystem N retention potential. Overall, we observed that the Snowmelt separates three distinct soil niches that are occupied by ecologically distinct groups of microorganisms. This ecological differentiation is of biogeochemical importance, particularly with respect to the mobilization of nitrogen during winter, before and after Snowmelt.
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Biological consequences of earlier Snowmelt from desert dust deposition in alpine landscapes.
Proceedings of the National Academy of Sciences of the United States of America, 2009Co-Authors: Heidi Steltzer, Chris Landry, Thomas H. Painter, Justin Anderson, Edward AyresAbstract:Dust deposition to mountain snow cover, which has increased since the late 19th century, accelerates the rate of Snowmelt by increasing the solar radiation absorbed by the snowpack. Snowmelt occurs earlier, but is decoupled from seasonal warming. Climate warming advances the timing of Snowmelt and early season phenological events (e.g., the onset of greening and flowering); however, earlier Snowmelt without warmer temperatures may have a different effect on phenology. Here, we report the results of a set of Snowmelt manipulations in which radiation-absorbing fabric and the addition and removal of dust from the surface of the snowpack advanced or delayed Snowmelt in the alpine tundra. These changes in the timing of Snowmelt were superimposed on a system where the timing of Snowmelt varies with topography and has been affected by increased dust loading. At the community level, phenology exhibited a threshold response to the timing of Snowmelt. Greening and flowering were delayed before seasonal warming, after which there was a linear relationship between the date of Snowmelt and the timing of phenological events. Consequently, the effects of earlier Snowmelt on phenology differed in relation to topography, which resulted in increasing synchronicity in phenology across the alpine landscape with increasingly earlier Snowmelt. The consequences of earlier Snowmelt from increased dust deposition differ from climate warming and include delayed phenology, leading to synchronized growth and flowering across the landscape and the opportunity for altered species interactions, landscape-scale gene flow via pollination, and nutrient cycling.
Noah P. Molotch - One of the best experts on this subject based on the ideXlab platform.
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Snowmelt rate dictates streamflow
Geophysical Research Letters, 2016Co-Authors: T. B. Barnhart, Noah P. Molotch, Ben Livneh, Adrian A. Harpold, John F. Knowles, Dominik SchneiderAbstract:Declining mountain snowpack and earlier Snowmelt across the western United States has implications for downstream communities. We present a possible mechanism linking Snowmelt rate and streamflow generation using a gridded implementation of the Budyko framework. We computed an ensemble of Budyko streamflow anomalies (BSA) using Variable Infiltration Capacity model-simulated evapotranspiration, potential evapotranspiration, and estimated precipitation at 1/16° resolution from 1950-2013. BSA was correlated with simulated baseflow efficiency (r2 = 0.64) and simulated Snowmelt rate (r2 = 0.42). The strong correlation between Snowmelt rate and baseflow efficiency (r2 = 0.73) links these relationships and supports a possible streamflow generation mechanism wherein greater Snowmelt rates increase subsurface flow. Rapid Snowmelt may thus bring the soil to field capacity, facilitating below-root-zone percolation, streamflow, and a positive BSA. Previous works have shown that future increases in regional air temperature may lead to earlier, slower Snowmelt, and hence, decreased streamflow production via the mechanism proposed by this work.
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interannual variability of Snowmelt in the sierra nevada and rocky mountains united states examples from two alpine watersheds
Water Resources Research, 2012Co-Authors: Steven M Jepsen, Noah P. Molotch, Mark W. Williams, Karl Rittger, James O SickmanAbstract:[1] The distribution of snow and the energy flux components of Snowmelt are intrinsic characteristics of the alpine water cycle controlling the location of source waters and the effect of climate on streamflow. Interannual variability of these characteristics is relevant to the effect of climate change on alpine hydrology. Our objective is to characterize the interannual variability in the spatial distribution of snow and energy fluxes of Snowmelt in watersheds of a maritime setting, Tokopah Basin (TOK) in California's southern Sierra Nevada, and a continental setting, Green Lake 4 Valley (GLV4) in Colorado's Front Range, using a 12 year database (1996–2007) of hydrometeorological observations and satellite-derived snow cover. Snowpacks observed in GLV4 exhibit substantially greater spatial variability than in TOK (0.75 versus 0.28 spatial coefficient of variation). In addition, modeling results indicate that the net turbulent energy flux contribution to Snowmelt in GLV4 is, on average, 3 times greater in magnitude (mean 29% versus 10%) and interannual variability (standard deviation 17% versus 6%) than in TOK. These energy flux values exhibit strong seasonality, increasing as the melt season progresses to times later in the year (R2 = 0.54–0.77). This seasonality of energy flux appears to be associated with Snowmelt rates that generally increase with onset date of melt (0.02 cm d−2). This seasonality in Snowmelt rate, coupled to differences in hydrogeology, may account for the observed differences in correspondence between the timing of Snowmelt and timing of streamflow in these watersheds.
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Estimating stream chemistry during the Snowmelt pulse using a spatially distributed, coupled Snowmelt and hydrochemical modeling approach
Water Resources Research, 2008Co-Authors: Noah P. Molotch, Thomas Meixner, Mark W. WilliamsAbstract:[1] We used remotely sensed snow cover data and a physically based Snowmelt model to estimate the spatial distribution of energy fluxes, Snowmelt, snow water equivalent, and snow cover extent over the different land cover types within the Green Lakes Valley, Front Range, Colorado. The spatially explicit snowpack model was coupled to the Alpine Hydrochemical Model (AHM), and estimates of hydrochemistry at the basin outlflow were compared with the baseline AHM approach, which implicitly prescribes Snowmelt. The proportions of total meltwater production from soil, talus, and rock subunits were 46, 25, and 29%, respectively, for the baseline simulation without our advanced Snowmelt representation. Conversely, simulations in which the AHM was coupled to our distributed Snowmelt model ascribed the largest meltwater production to talus (47%) subunits, with 37% ascribed to soil and 16% ascribed to rock. Accounting for these differences in AHM reduced model overestimates of cation concentration during Snowmelt; modeled Ca2+ estimates explained 82 and 70% (P values < 0.01) of observations with and without the coupled model, respectively. Similarly, the coupled model explained more variability in nitrate concentrations, with 83 versus 70% (P values < 0.01) explained by the coupled and baseline models, respectively. Early Snowmelt over talus subunits was not detected at the basin outflow, confirming earlier reports that deeper flow paths are needed in biogeochemical models of alpine systems. Realistic treatment of Snowmelt within these models will allow efforts to improve understanding of flow paths and predict catchment response to increases in atmospheric deposition and climate change.
Carol Kendall - One of the best experts on this subject based on the ideXlab platform.
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Isotope variations in a Sierra Nevada snowpack and their relation to meltwater
Journal of Hydrology, 2001Co-Authors: P. V. Unnikrishna, Jeffrey J. Mcdonnell, Carol KendallAbstract:Abstract Isotopic variations in melting snow are poorly understood. We made weekly measurements at the Central Sierra Snow Laboratory, California, of snow temperature, density, water equivalent and liquid water volume to examine how physical changes within the snowpack govern meltwater δ18O. Snowpack samples were extracted at 0.1 m intervals from ground level to the top of the snowpack profile between December 1991 and April 1992. Approximately 800 mm of precipitation fell during the study period with δ18O values between −21.35 and −4.25‰. Corresponding snowpack δ18O ranged from −22.25 to −6.25‰. The coefficient of variation of δ18O in snowpack levels decreased from −0.37 to −0.07 from winter to spring, indicating isotopic snowpack homogenization. Meltwater δ18O ranged from −15.30 to −8.05‰, with variations of up to 2.95‰ observed within a single Snowmelt episode, highlighting the need for frequent sampling. Early Snowmelt originated in the lower snowpack with higher δ18O through ground heat flux and rainfall. After the snowpack became isothermal, infiltrating Snowmelt displaced the higher δ18O liquid in the lower snowpack through a piston flow process. Fractionation analysis using a two-component mixing model on the isothermal snowpack indicated that δ18O in the initial and final half of major Snowmelt was 1.30‰ lower and 1.45‰ higher, respectively, than the value from simple mixing. Mean snowpack δ18O on individual profiling days showed a steady increase from −15.15 to −12.05‰ due to removal of lower δ18O Snowmelt and addition of higher δ18O rainfall. Results suggest that direct sampling of Snowmelt and snow cores should be undertaken to quantify tracer input compositions adequately. The Snowmelt sequence also suggests that regimes of early lower δ18O and later higher δ18O melt may be modeled and used in catchment tracing studies.
W.w. Miller - One of the best experts on this subject based on the ideXlab platform.
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Nutrient fluxes in a snow-dominated, semi-arid forest: Spatial and temporal patterns
Biogeochemistry, 2001Co-Authors: D.w. Johnson, R.b. Susfalk, R.a. Dahlgren, T.g. Caldwell, W.w. MillerAbstract:We tested five hypotheses regarding the potential effects of precipitation change on spatial and temporal patterns of water flux, ion flux, and ion concentration in a semiarid, Snowmelt-dominated forest in Little Valley, Nevada. Variations in data collected from 1995 to 1999 were used to examine the potential effects of snowpack amount and duration on ion concentrations and fluxes. Soil solution NO_3 ^−, NH_4 ^+, and ortho-phosphate concentrations and fluxes were uniformly low, and the variations in concentration bore no relationship to Snowmelt water flux inputs of these ions. Weathering and cation exchange largely controlled the concentrations and fluxes of base cations from soils in these systems; however, soil solution base cation concentrations were affected by cation concentrations during Snowmelt episodes. Soil solution Cl^− and SO_4 ^2− concentrations closely followed the patterns in Snowmelt water, suggesting minimal buffering of either ion by soils. In contrast to other studies, the highest concentration and the majority of ion flux from the snowpack in Little Valley occurred in the later phases of Snowmelt. Possible reasons for this include sublimation of the snowpack and dry deposition of organic matter during the later stages of Snowmelt. Our comparison of interannual and spatial patterns revealed that variation in ion concentration rather than water flux is the most important driver of variation in ion flux. Thus, it is not safe to assume that changes in total precipitation amount will cause concomitant changes in ion inputs to this system.
James P Mcnamara - One of the best experts on this subject based on the ideXlab platform.
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simulated soil water storage effects on streamflow generation in a mountainous Snowmelt environment idaho usa
Hydrological Processes, 2009Co-Authors: Mark S Seyfried, Laura E Grant, Danny Marks, Adam Winstral, James P McnamaraAbstract:Although soil processes affect the timing and amount of streamflow generated from Snowmelt, they are often overlooked in estimations of Snowmelt-generated streamflow in the western USA. The use of a soil water balance modelling approach to incorporate the effects of soil processes, in particular soil water storage, on the timing and amount of Snowmelt generated streamflow, was investigated. The study was conducted in the Reynolds Mountain East (RME) watershed, a 38 ha, Snowmelt-dominated watershed in southwest Idaho. Snowmelt or rainfall inputs to the soil were determined using a well established snow accumulation and melt model (Isnobal). The soil water balance model was first evaluated at a point scale, using periodic soil water content measurements made over two years at 14 sites. In general, the simulated soil water profiles were in agreement with measurements (P 0·85), y-intercept values near 0, slopes near 1 and low average differences between measured and modelled values. In addition, observed soil water dynamics were generally consistent with critical model assumptions. Spatially distributed simulations over the watershed for the same two years indicate that streamflow initiation and cessation are closely linked to the overall watershed soil water storage capacity, which acts as a threshold. When soil water storage was below the threshold, streamflow was insensitive to Snowmelt inputs, but once the threshold was crossed, the streamflow response was very rapid. At these times there was a relatively high degree of spatial continuity of satiated soils within the watershed. Incorporation of soil water storage effects may improve estimation of the timing and amount of streamflow generated from mountainous watersheds dominated by Snowmelt. Copyright © 2008 John Wiley & Sons, Ltd.
