skip to main content


Title: Pervasive alterations to snow-dominated ecosystem functions under climate change
Climate change projections consistently demonstrate that warming temperatures and dwindling seasonal snowpack will elicit cascading effects on ecosystem function and water resource availability. Despite this consensus, little is known about potential changes in the variability of ecohydrological conditions, which is also required to inform climate change adaptation and mitigation strategies. Considering potential changes in ecohydrological variability is critical to evaluating the emergence of trends, assessing the likelihood of extreme events such as floods and droughts, and identifying when tipping points may be reached that fundamentally alter ecohydrological function. Using a single-model Large Ensemble with sophisticated terrestrial ecosystem representation, we characterize projected changes in the mean state and variability of ecohydrological processes in historically snow-dominated regions of the Northern Hemisphere. Widespread snowpack reductions, earlier snowmelt timing, longer growing seasons, drier soils, and increased fire risk are projected for this century under a high-emissions scenario. In addition to these changes in the mean state, increased variability in winter snowmelt will increase growing-season water deficits and increase the stochasticity of runoff. Thus, with warming, declining snowpack loses its dependable buffering capacity so that runoff quantity and timing more closely reflect the episodic characteristics of precipitation. This results in a declining predictability of annual runoff from maximum snow water equivalent, which has critical implications for ecosystem stress and water resource management. Our results suggest that there is a strong likelihood of pervasive alterations to ecohydrological function that may be expected with climate change.  more » « less
Award ID(s):
2120804 2031238 1637686 2031253
NSF-PAR ID:
10356750
Author(s) / Creator(s):
; ; ; ; ; ; ;
Date Published:
Journal Name:
Proceedings of the National Academy of Sciences
Volume:
119
Issue:
30
ISSN:
0027-8424
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Abstract

    Alpine tundra ecosystems are highly vulnerable to climate warming but are governed by local‐scale abiotic heterogeneity, which makes it difficult to predict tundra responses to environmental change. Although land models are typically implemented at global scales, they can be applied at local scales to address process‐based ecological questions. In this study, we ran ecosystem‐scale Community Land Model (CLM) simulations with a novel hillslope hydrology configuration to represent topographically heterogeneous alpine tundra vegetation across a moisture gradient at Niwot Ridge, Colorado, USA. We used local observations to evaluate our simulations and investigated the role of topography and aspect in mediating patterns of snow, productivity, soil moisture, and soil temperature, as well as the potential exposure to climate change across an alpine tundra hillslope. Overall, our simulations captured observed gradients in abiotic conditions and productivity among heterogeneous, hydrologically connected vegetation communities (moist, wet, and dry). We found that south facing aspects were characterized by reduced snowpack and drier and warmer soils in all communities. When we extended our simulations to the year 2100, we found that earlier snowmelt altered the timing of runoff, with cascading effects on soil moisture, productivity, and growing season length. However, these effects were not distributed equally across the tundra, highlighting potential vulnerabilities of alpine vegetation in dry, wind‐scoured, and south facing areas. Overall, our results demonstrate how land model outputs can be applied to advance process‐based understanding of climate change impacts on ecosystem function.

     
    more » « less
  2. Abstract

    The declining mountain snowpack is expected to melt earlier and more slowly with climate warming. Previous work indicates that lower snowmelt rates are associated with decreased runoff. However, earlier snowmelt could increase runoff via lower vegetation water use in early spring. The relative importance of these factors with regard to runoff is linked to site‐specific conditions such as plant available water storage (PAWS) and energy availability. To disentangle the effects of snowmelt rate and timing on runoff production, we conducted a hydrologic modeling experiment at sites in Colorado (NR1) and California (P301) that controlled for snowmelt rate and timing multicollinearity. We tested the sensitivity of snowmelt season potential runoff (R), changes in subsurface storage (ΔS), and other water budget components to snowmelt rate (smr) and timing (smt) using multiple linear regression and global sensitivity analysis (GSA). Regression results confirmed thatRwas governed by the competing influence ofsmrandsmt. At both sites, ΔSwas more sensitive tosmtthansmrwhileRwas more sensitive tosmrat P301 and tosmtat NR1, reflecting energy limitation at NR1. GSA analyses mirrored the regressions forR, confirming thatsmtwas more important at NR1 than P301. This work suggests that runoff increases from earlier snowmelt may counteract runoff losses due to slower snowmelt and that this process is mediated by PAWS and energy availability. These results suggest thatRwill be more susceptible to future changes insmrandsmtat sites with greater PAWS and available energy.

     
    more » « less
  3. Abstract

    Climate change is altering biogeochemical, metabolic, and ecological functions in lakes across the globe. Historically, mountain lakes in temperate regions have been unproductive because of brief ice‐free seasons, a snowmelt‐driven hydrograph, cold temperatures, and steep topography with low vegetation and soil cover. We tested the relative importance of winter and summer weather, watershed characteristics, and water chemistry as drivers of phytoplankton dynamics. Using boosted regression tree models for 28 mountain lakes in Colorado, we examined regional, intraseasonal, and interannual drivers of variability in chlorophyllaas a proxy for lake phytoplankton. Phytoplankton biomass was inversely related to the maximum snow water equivalent (SWE) of the previous winter, as others have found. However, even in years with average SWE, summer precipitation extremes and warming enhanced phytoplankton biomass. Peak seasonal phytoplankton biomass coincided with the warmest water temperatures and lowest nitrogen‐to‐phosphorus ratios. Although links between snowpack, lake temperature, nutrients, and organic‐matter dynamics are increasingly recognized as critical drivers of change in high‐elevation lakes, our results highlight the additional influence of summer conditions on lake productivity in response to ongoing changes in climate. Continued changes in the timing, type, and magnitude of precipitation in combination with other global‐change drivers (e.g., nutrient deposition) will affect production in mountain lakes, potentially shifting these historically oligotrophic lakes toward new ecosystem states. Ultimately, a deeper understanding of these drivers and pattern at multiple scales will allow us to anticipate ecological consequences of global change better.

     
    more » « less
  4. Abstract

    The western United States (US) is a hotspot for snow drought. The Oregon Cascade Range is highly sensitive to warming and as a result has experienced the largest mountain snowpack losses in the western US since the mid‐20th century, including a record‐breaking snow drought in 2014–2015 that culminated in a state of emergency. While Oregon Cascade snowpacks serve as the state's primary water supply, short instrumental records limit water managers' ability to fully constrain long‐term natural snowpack variability prior to the influence of ongoing and projected anthropogenic climate change. Here, we use annually‐resolved tree‐ring records to develop the first multi‐century reconstruction of Oregon Cascade April 1st Snow Water Equivalent (SWE). The model explains 58% of observed snowpack variability and extends back to 1688 AD, nearly quintupling the length of the existing snowpack record. Our reconstruction suggests that only one other multiyear event in the last three centuries was as severe as the 2014–2015 snow drought. The 2015 event alone was more severe than nearly any other year in over three centuries. Extreme low‐to‐high snowpack “whiplash” transitions are a consistent feature throughout the reconstructed record. Multi‐decadal intervals of persistent below‐the‐mean peak SWE are prominent features of pre‐instrumental snowpack variability, but are generally absent from the instrumental period and likely not fully accounted for in modern water management. In the face of projected snow drought intensification and warming, our findings motivate adaptive management strategies that address declining snowpack and increasingly variable precipitation regimes.

     
    more » « less
  5. Long-term snowpack decline is among the best-understood impacts of climate change on water resources systems. This trend has been observed for decades and is projected to continue even in climate projections in which total runoff volumes do not change significantly. For basins in which snowpack has historically provided intra-annual water storage, snowpack decline creates several issues that may require adaptation to infrastructure, operations, or both. This study develops an approach to analyze vulnerabilities and adaptations specifically focused on the challenge of snowpack decline, using the northern California reservoir system as a case study. We first introduce an open-source daily time-step simulation model of this system, which is validated against historical observations of operations. Multiobjective vulnerabilities to snowpack decline are then examined using a set of downscaled climate scenarios to capture the physically based effects of rising temperatures. A statistical analysis shows that the primary impacts include water supply shortage and lower reservoir storage resulting from the seasonal shift in runoff timing. These challenges identified from the vulnerability assessment inform proposed adaptations to operations to maintain multiobjective performance across the ensemble of plausible future scenarios, which include other uncertain hydrologic changes. To adapt seasonal reservoir management without the cost of additional infrastructure, we specifically propose and test adaptations that parameterize the structure of existing operating policies: a dynamic flood control rule curve and revised snowpack-to-streamflow forecasting methods to improve seasonal runoff predictability given declining snowpack. These adaptations are shown to mitigate the majority of vulnerabilities caused by snowpack decline across the scenario ensemble, with remaining opportunities for improvement using formal policy search and dynamic adaptation techniques. The coupled approach to vulnerability assessment and adaptation is generalizable to other snowmelt-dominated water resources systems facing the loss of seasonal storage due to rising temperatures. 
    more » « less