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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Variation in hydroclimate sustains tropical forest biomass and promotes functional diversity

The fate of tropical forests under climate change is unclear as a result, in part, of the uncertainty in projected changes in precipitation and in the ability of vegetation models to capture the effects of drought-induced mortality on aboveground biomass (AGB). In this work, we evaluated the ability of a terrestrial biosphere model with demography and hydrodynamics (Ecosystem Demography, ED2-hydro) to simulate AGB and mortality of four tropical tree plant functional types (PFTs) that operate along light- and water-use axes. Model predictions were compared with observations of canopy trees at Barro Colorado Island (BCI), Panama. We then assessed the implications of eight hypothetical precipitation scenarios, including increased annual precipitation, reduced inter-annual variation, El Niño-related droughts and drier wet or dry seasons, on AGB and functional diversity of the model forest. When forced with observed meteorology, ED2-hydro predictions capture multiple BCI benchmarks. ED2-hydro predicts that AGB will be sustained under lower rainfall via shifts in the functional composition of the forest, except under the drier dry-season scenario. Furthermore these results support the hypothesis that inter-annual variation in mean and seasonal precipitation promotes the coexistence of functionally diverse PFTs because of the relative differences in mortality rates. If the hydroclimate becomes chronically drier or wetter, functional evenness related to drought tolerance may decline.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRSDate not supplied

Synthetic Hyperspectral Data for Global Water Quality Algorithm Development

Eutrophication and increasing prevalence of potentially toxic algal blooms (cyanoHABs) among global inland water bodies have become a major ecological concern and require direct attention. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local aquatic processes, to spatially resolved global products. Planned aquatic biogeochemistry remote sensing data products from hyperspectral imagers such as NASA’s Surface Biology and Geology (SBG) mission and relevant aquatic sensor sensitivity precursor airborne imaging spectrometer data provide unprecedented radiometric resolution and sensor sensitivity for characterizing complex aquatic ecosystems. However, scarcity of high-quality freshwater in-situ optical data hinders our capability to develop and validate robust retrieval algorithms. A state-of-the-art synthetic dataset of paired top-of-atmosphere, bottom-of-atmosphere, and optical and biogeophysical data was developed through radiative transfer modeling to simulate natural freshwater ecosystems. A synthetic or precursor dataset for SBG is being used to train robust machine learning models to derive water quality products pertinent to SBG mission objectives. The dataset is also used to show the potential of performing vigorous aquatic sensitivity studies and explored pathways for how best to optimize hyperspectral data for machine learning development. A processing pipeline and resultant global synthetic/precursor dataset for inland waters is presented to establish the innovation for water quality studies of inland waters globally. Optical Society of America Imaging and Applied Optics Congress, Hyperspectral Imaging and Sounding of the Environment (OSA HISE) Meeting, 19-23 July 2021, Virtual Meeting, https://www.osa.org/enus/meetings/osa_meetings/optical_sensors_and_sensing_congress/program/hyperspectral_imaging_and_sounding_of_the_environm/

Synthetic↗
NASA NTRS2010

Monitoring Coastal Marshes for Persistent Flooding and Salinity Stress

Our objective is to provide NASA remote sensing products that provide inundation and salinity information on an ecosystem level to support habitat switching models. Project born out of need by the Coastal Restoration Monitoring System (CRMS), joint effort by Louisiana Department of Natural Resources and the U.S. Geological Survey, for information on persistence of flooding by storm surge and other flood waters. The results of the this work support the habitat-switching modules in the Coastal Louisiana Ecosystem Assessment and Restoration (CLEAR) model, which provides scientific evaluation for restoration management. CLEAR is a collaborative effort between the Louisiana Board of Regents, the Louisiana Department of Natural Resources (LDNR), the U.S. Geological Survey (USGS), and the U.S. Army Corps of Engineers (USACE). Anticipated results will use: a) Resolution enhanced time series data combining spatial resolution of Landsat with temporal resolution of MODIS for inundation estimates. b) Potential salinity products from radar and multispectral modeling. c) Combined inundation and salinity inputs to habitat switching module to produce habitat switching maps (shown at left)

Kalcic, Maria↗
DOE OSTI2021

A Modified Vegetation Photosynthesis and Respiration Model (VPRM) for the Eastern USA and Canada, Evaluated With Comparison to Atmospheric Observations and Other Biospheric Models

Atmospheric CO 2 measurements from a dense surface network can help to evaluate terrestrial biosphere model (TBM) simulations of Net Ecosystem Exchange (NEE) with two key benefits. First, gridded CO 2 flux estimates can be evaluated over regional scales, not possible using flux tower observations at discrete locations for model evaluation. Second, TBM ability to explain atmospheric CO 2 fluctuations due to the biosphere can be directly tested, an important objective for anthropogenic emissions monitoring using atmospheric observations. Here, we customize the Vegetation Photosynthesis and Respiration Model (VPRM) for an eastern North American domain with strong biological activity upwind of urban areas. Parameters are optimized using flux tower observations from a historical database with sites in (and near) the domain. In addition, the respiration model (originally a linear function of temperature) is modified to account for impacts of changing foliage, non-linear temperature, and water stress. Flux estimates from VPRM, the Carnegie-Ames-Stanford Approach (CASA) model and the Simple Biosphere Model v4 (SiB4), are convolved with footprints from atmospheric transport models for evaluation with CO 2 observations at 21 towers in the domain, with roughly half of the towers used here for the first time. Results show that the new respiration model in VPRM helps to correct a growing season sink bias in the atmosphere associated with underestimated summertime respiration using the original model with annual parameters. The new VPRM also better explains fine-scale atmospheric CO 2 variability compared to other TBMs, due to higher resolution diagnostic phenology, the new respiration model, domain-specific parameters, and high-quality input data sets.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A Modeling framework for flocculated cohesive sediment transport in the current bottom boundary layer

Cohesive sediment transport, where its settling velocity is controlled by the flocculation process, is a crucial component in determining biochemical cycles, fate of pollutants, and morphodynamics in many aquatic ecosystems. In this study, a modeling framework is presented to investigate how flocculation influences cohesive sediment transport in the current bottom boundary layer in dilute conditions, consistent with the calibration range of the flocculation model. From a local analysis of floc dynamics in homogenous turbulence, we identify that the floc size distribution is mainly controlled by floc cohesion and yield strength. The uncertainty in fractal dimension plays a minor role for the floc size but it influences the resulting floc density and settling velocity. The transport analysis in the current boundary layer shows that the flocculation process alters the vertical distribution of the settling velocity and hence the sediment concentration with a strong dependence on cohesion, floc yield strength, and floc structure. When the flocs are more susceptible to breaking, a well-mixed concentration profile is obtained. In contrast, for flocs with higher cohesion or yield strength, higher concentration with a sharp gradient is observed close to the bed. Overall, the settling velocity exhibits a low vertical variability within 20 % of the depth-averaged value except near the bed. Further, this suggests that using a depth-averaged settling velocity yields acceptable predictions of the sediment concentration profiles, especially for flocs with lower cohesion.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Terrestrial Ecosystem Science (Flyer 2020)

A significant fraction of the carbon dioxide (CO 2 ) released to the atmosphere during energy production is taken up by terrestrial ecosystems. This carbon “sink” represents an important but poorly characterized buffer for offsetting the greenhouse gas effects of anthropogenic CO 2 emissions. Also unclear are the effects of related processes such as nutrient, water, and energy cycling—in addition to climate variability and change— on that uptake. Resolving the terrestrial biosphere’s role in the global carbon cycle is consequently a high priority for the Terrestrial Ecosystem Science (TES) program within the Department of Energy’s (DOE) Office of Biological and Environmental Research (BER). Understanding the mechanisms and dynamics of ecosystem processes in the face of a changing climate is also essential for improving the representation of terrestrial ecosystems and climate feedbacks in Earth system models (ESMs). TES supports research to advance fundamental understanding of terrestrial ecosystems and their roles in a changing climate.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Climate impacts in scenarios: time to close the loop?

Reaching a full understanding of the consequences of climate change for society and ecosystems, and the ensuing needs for adaptation, requires a consideration of the interactions between human and Earth systems. Currently, however, climate research largely separates the influence of society on climate from the influence of climate on society; that is, it doesn’t “close the loop.” A primary example of this approach is the generation and use of earth system model (ESM) simulations in the climate change research community. Large-scale socio-economic models, known as integrated assessment models (IAMs), are used to project emissions and land use change which serve as input to ESMs. ESM projections then serve as input to models of impacts on society and ecosystems. But, according to this modeling chain, those impacts do not affect the emissions and land use that drove the ESMs in the first place. Previous work has not drawn firm conclusions on whether this feedback would be large enough to warrant explicitly accounting for it. Two prominent possibilities, however, are that emissions and land use scenarios representing the high and low ends of the plausible range of future climate change are both too extreme. The high-end scenario may miss damaging impacts that would reduce economic activity, and therefore emissions, while the low-end scenario may ignore climate feedbacks that would make large-scale land-based carbon removal ineffective and therefore would hamper mitigation at the level assumed by the scenario. In this piece, we identify the opportunities and challenges that implementing such feedback loops would face. We argue that recent developments in climate impact research, human system modeling and ESM emulation make the time ripe to use IAMs in a structured model intercomparison exercise. Model intercomparison projects have benefitted the climate modeling community for decade snow, and more recently have also benefitted the impact modeling community. An IAM intercomparison focused on integrating impacts could make large strides in testing the implications of these feedbacks and assessing whether closing the loop would fundamentally change our outlook on future climate changes and their consequences.

Tebaldi, Claudia↗
DOE OSTI2023

Terrestrial carbon dynamics in an era of increasing wildfire

In an increasingly flammable world, wildfire is altering the terrestrial carbon balance. However, the degree to which novel wildfire regimes disrupt biological function remains unclear. Here, we synthesize the current understanding of above and below ground processes that govern carbon loss and recovery across diverse ecosystems. In this study, we find that intensifying wildfire regimes are increasingly exceeding biological thresholds of resilience, causing ecosystems to convert to a lower carbon-carrying capacity. Growing evidence suggests that plants compensate for fire damage by allocating carbon below ground to access nutrients released by fire, while wildfire selects for microbial communities with rapid growth rates and the ability to metabolize pyrolyzed carbon. Determining controls on carbon dynamics following wildfire requires integration of experimental and modeling frameworks across scales and ecosystems. Fire severity is expected to increase as a result of warming. This will potentially amplify climate change due to its impact on the carbon cycle. This Review discusses ecosystem carbon loss and recovery following wildfire, and highlights where further work is needed to inform model predictions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Beyond Static Benchmarking: Using Experimental Manipulations to Evaluate Land Model Assumptions

Land models are often used to simulate terrestrial responses to future environmental changes, but these models are not commonly evaluated with data from experimental manipulations. Results from experimental manipulations can identify and evaluate model assumptions that are consistent with appropriate ecosystem responses to future environmental change. We conducted simulations using three coupled carbon-nitrogen versions of the Community Land Model (CLM, versions 4, 4.5, and—the newly developed—5), and compared the simulated response to nitrogen (N) and atmospheric carbon dioxide (CO 2 ) enrichment with meta-analyses of observations from similar experimental manipulations. In control simulations, successive versions of CLM showed a poleward increase in gross primary productivity and an overall bias reduction, compared to FLUXNET-MTE observations. Simulations with N and CO 2 enrichment demonstrate that CLM transitioned from a model that exhibited strong nitrogen limitation of the terrestrial carbon cycle (CLM4) to a model that showed greater responsiveness to elevated concentrations of CO 2 in the atmosphere (CLM5). Overall, CLM5 simulations showed better agreement with observed ecosystem responses to experimental N and CO 2 enrichment than previous versions of the model. These simulations also exposed shortcomings in structural assumptions and parameterizations. Specifically, no version of CLM captures changes in plant physiology, allocation, and nutrient uptake that are likely important aspects of terrestrial ecosystems' responses to environmental change. These highlight priority areas that should be addressed in future model developments. Moving forward, incorporating results from experimental manipulations into model benchmarking tools that are used to evaluate model performance will help increase confidence in terrestrial carbon cycle projections.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Coordination of rooting, xylem, and stomatal strategies explains the response of conifer forest stands to multi-year drought in the southern Sierra Nevada of California

Abstract. Extreme droughts are a major determinant of ecosystem disturbance that impacts plant communities and feeds back into climate change through changes in plant functioning. However, the complex relationships between aboveground and belowground plant hydraulic traits and their role in governing plant responses to drought are not fully understood. In this study, we use a model, the Functionally Assembled Terrestrial Ecosystem Simulator in a configuration that includes plant hydraulics (FATES-Hydro), to investigate ecosystem responses to the 2012–2015 California drought in comparison with observations at a site in the southern Sierra Nevada that experienced widespread tree mortality during this drought. We conduct a sensitivity analysis to explore how different plant water sourcing and hydraulic strategies lead to differential responses during normal and drought conditions. The analysis shows the following. Deep roots that sustain productivity through the dry season are needed for the model to capture observed seasonal cycles of evapotranspiration (ET) and gross primary productivity (GPP) in normal years, and deep-rooted strategies are nonetheless subject to large reductions in ET and GPP when the deep soil reservoir is depleted during extreme droughts, in agreement with observations. Risky stomatal strategies lead to greater productivity during normal years as compared to safer stomatal control, but they also lead to a high risk of xylem embolism during the 2012–2015 drought. For a given stand density, stomatal and xylem traits have a stronger impact on plant water status than on ecosystem-level fluxes. Our study highlights the significance of resolving plant water sourcing strategies to represent drought impacts on plants and consequent feedbacks in models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Informing Robust Functional Relationship Benchmarks: An Evaluation of the Temperature Sensitivity of Ecosystem Respiration Across the Arctic-Boreal Region

During land model development, simulated carbon dynamics are often benchmarked against observational data sets to evaluate model performance. Functional relationship benchmarks are the relationship between a driving variable (e.g., temperature) and a response variable (e.g., ecosystem respiration) and are a promising tool for assessing model performance by evaluating modeled sensitivities to changing environmental conditions. However, observed functional relationships can be influenced by choices made during data collection and throughout the benchmarking process, impacting the inferred skill of land models. To avoid misrepresenting a model's true performance, it is necessary to systematically evaluate best practices when constructing functional relationship benchmarks. We developed a set of guidelines for constructing functional relationship benchmarks, considering the choice of data set, number of daily observations, temporal extent, and temporal resolution across Alaska and Canada over a 20-year period from 2001 to 2020. The temperature sensitivity of ecosystem respiration from observations, evaluated through an apparent Q 10 , is highly variable both spatially and as a result of the data processing approach applied in the benchmark formation. When benchmarking 13 models from the Warming Permafrost Model Intercomparison Project (WrPMIP), the range in inferred model skill is substantially impacted by the choices applied in constructing functional relationship benchmarks. The inferred performance of a given model is most sensitive to the number of daily observations and temporal extent, followed by choice of benchmark data set and temporal averaging. Results from this analysis can guide the development of consistent and robust functional relationships for future model evaluation studies.

Poe, Jeralyn [Northern Arizona University, Flagsta↗
DOE OSTI2020

Relative Impact of Sea Ice and Temperature Changes on Arctic Marine Production

We use a modern Earth system model to approximate the relative importance of ice versus temperature on Arctic marine ecosystem dynamics. We show that while the model adequately simulates ice volume, water temperature, air-sea CO 2 flux, and annual primary production in the Arctic, itunderestimates upper water column nitrate across the region. This nitrate bias is likely responsible for the apparent underestimation of ice algae production. Despite this shortcoming, the model appears to be a useful tool for exploring the impacts of environmental change on phytoplankton production and carbon dynamics over the Arctic Ocean. Our experiments indicate that under a warmer climate scenario, the percentage of ocean warming that could be apportioned to a reduction in ice area ranged from 11% to 100%, while decreasing ice area could account for 22–100% of the increase in annual ocean primary production. The change to CO2 air-sea flux in response to ice and temperature changes averaged an Arctic-wide 5.5 Tg C yr –1 (3.5%) increase, into the ocean. This increased carbon sink may be short-lived, as ice cover continues to decrease and the ocean warms. The change in carbon fixation from phytoplankton in response to increased temperatures and reduced ice was generally more than a magnitude larger than the changes to CO 2 flux, highlighting the importance of fully considering changes to the marine ecosystem when assessing Arctic carbon cycle dynamics. Our work demonstrates the importance of ice dynamics in controlling ocean warming and production and thus the need for well-behaved ice and BGC models within Earth system models if we hope to accurately predict Arctic changes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2019

The Arctic-Boreal vulnerability experiment model benchmarking system

NASA's Arctic-Boreal Vulnerability Experiment (ABoVE) integrates field and airborne data into modeling and synthesis activities for understanding Arctic and Boreal ecosystem dynamics. The ABoVE Benchmarking System (ABS) is an operational software package to evaluate terrestrial biosphere models against key indicators of Arctic and Boreal ecosystem dynamics, i.e.: carbon biogeochemistry, vegetation, permafrost, hydrology, and disturbance. The ABS utilizes satellite remote sensing data, airborne data, and field data from ABoVE as well as collaborating research networks in the region, e.g.: the Permafrost Carbon Network, the International Soil Carbon Network, the Northern Circumpolar Soil Carbon Database, AmeriFlux sites, the Moderate Resolution Imaging Spectroradiometer, the Orbiting Carbon Observatory 2, and the Soil Moisture Active Passive mission. The ABS is designed to be interactive for researchers interested in having their models accurately represent observations of key Arctic indicators: a user submits model results to the system, the system evaluates the model results against a set of Arctic-Boreal benchmarks outlined in the ABoVE Concise Experiment Plan, and the user then receives a quantitative scoring of model strengths and deficiencies through a web interface. This interactivity allows model developers to iteratively improve their model for the Arctic-Boreal Region by evaluating results from successive model versions. We show here, for illustration, the improvement of the Lund–Potsdam–Jena-Wald Schnee und Landschaft (LPJwsl) version model through the ABoVE ABS as a new permafrost module is coupled to the existing model framework. The ABS will continue to incorporate new benchmarks that address indicators of Arctic-Boreal ecosystem dynamics as they become available.

ABoVE↗
NASA NTRS1998

Field Micrometeorological Measurements, Process-Level Studies and Modeling of Methane and Carbon Dioxide Fluxes in a Boreal Wetland Ecosystem

The main instrumentation platform consisted of eddy correlation sensors mounted on a scaffold tower at a height of 4.2 m above the peat surface. The sensors were attached to a boom assembly which could be rotated into the prevailing winds. The boom assembly was mounted on a movable sled which, when extended, allowed sensors to be up to 2 m away from the scaffolding structure to minimize flow distortion. When retracted, the sensors could easily be installed, serviced or rotated. An electronic level with linear actuators allowed the sensors to be remotely levelled once the sled was extended. Two instrument arrays were installed. A primary (fast-response) array consisted of a three-dimensional sonic anemometer, a methane sensor (tunable diode laser spectrometer), a carbon dioxide/water vapor sensor, a fine wire thermocouple and a backup one-dimensional sonic anemometer. The secondary array consisted of a one-dimensional sonic anemometer, a fine wire thermocouple and a Krypton hygrometer. Descriptions of these sensors may be found in other reports (e.g., Verma; Suyker and Verma). Slow-response sensors provided supporting measurements including mean air temperature and humidity, mean horizontal windspeed and direction, incoming and reflected solar radiation, net radiation, incoming and reflected photosynthetically active radiation (PAR), soil heat flux, peat temperature, water-table elevation and precipitation. A data acquisition system (consisting of an IBM compatible microcomputer, amplifiers and a 16 bit analog-to-digital converter), housed in a small trailer, was used to record the fast response signals. These signals were low-pass filtered (using 8-pole Butterworth active filters with a 12.5 Hz cutoff frequency) and sampled at 25 Hz. Slow-response signals were sampled every 5 s using a network of CR21X (Campbell Scientific, Inc., Logan Utah) data loggers installed in the fen. All signals were averaged over 30-minute periods (runs).

Verma, S. B.↗
NASA NTRS2023

Models for Facilitating Government-Funded Activities in the Post-ISS LEO Ecosystem

This study helps elucidate NASA’s future options for facilitating government-funded activities in the post-International Space Station (ISS) low-Earth orbit (LEO) ecosystem. NASA is preparing for the retirement of the ISS and transition of LEO activities to one or more Commercial LEO Destinations (CLDs) by 2030. This transition necessitates new models for connecting NASA and other users of the LEO environment to platforms and opportunities. In light of this transition, NASA senior leadership tasked the Office of Technology, Policy, and Strategy (OTPS) with answering two questions: 1) what are potential models for an ISS National Lab facilitating government-funded or subsidized activities on a commercial LEO platform after the transition of the ISS to one or more private platforms, and 2) in light of these options, what modifications would be helpful to make in the current ISSNL-CASIS partnership and the NASA management processes as NASA plans for the transition of the ISS by 2030? To answer the first question, we conducted a stakeholder-driven analysis to identify a trade space of six differentiated model options. We then evaluated their performance in three potential future scenarios, according to evaluation criteria deemed important to stakeholders. The six models are illustrative and representational of a potential trade space. Additionally, each model requires change to current legislation. To further aid in leadership decision-making, we provided considerations for how to strengthen each model by mixing and matching different model aspects. To answer the second question, we looked to strengths of the top-performing models to evolve the current ISSNL-CASIS relationship and improve NASA’s posture for success post-ISS. We identified four possible modifications to the ISSNL-CASIS partnership and NASA’s management of these activities. By implementing these modifications early, NASA can increase the return from ISSNL-CASIS and help prepare for future models as one or more CLD replaces the ISS by 2030.

ISS↗
DOE OSTI2017

Higher climatological temperature sensitivity of soil carbon in cold than warm climates

The projected loss of soil carbon to the atmosphere resulting from climate change is a potentially large but highly uncertain feedback to warming. The magnitude of this feedback is poorly constrained by observations and theory, and is disparately represented in Earth system models (ESMs). In this study, to assess the climatological temperature sensitivity of soil carbon, we calculate apparent soil carbon turnover times that reflect long-term and broad-scale rates of decomposition. We show that the climatological temperature control on carbon turnover in the top metre of global soils is more sensitive in cold climates than in warm climates and argue that it is critical to capture this emergent ecosystem property in global-scale models. We present a simplified model that explains the observed high cold-climate sensitivity using only the physical scaling of soil freeze-thaw state across climate gradients. Current ESMs fail to capture this pattern, except in an ESM that explicitly resolves vertical gradients in soil climate and carbon turnover. An observed weak tropical temperature sensitivity emerges in a different model that explicitly resolves mineralogical control on decomposition. Lastly, these results support projections of strong carbon-climate feedbacks from northern soils and demonstrate a method for ESMs to capture this emergent behaviour.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Asymmetric winter warming advanced plant phenology to a greater extent than symmetric warming in an alpine meadow

1. The warming of terrestrial high-latitude ecosystems, while increasing, will likely be asymmetric across seasons—where winter non-growing seasons will warm more than summer-growing seasons. Asymmetric winter warming in temperature-sensitive ecosystems may delay spring phenological events by reducing the opportunity that a plants’ chilling requirement is met. Similarly, symmetric warming can advance spring phenology. 2. To explore the impact of asymmetric warming on plant phenology, we applied a year-round warming and a winter warming treatment to our experimental plots. Over a 2-year period, we monitored leaf-out and flowering phenology for 11 plant species. 3. There was variation among species, however, both winter and year-round warming, advanced the leaf-out day and the first flowering day relative to the control treatment. So, winter warming advanced leaf-out and flowering phenology by 11.1 (±2.4) and 12.6 (±2.9) days respectively. However, year-round warming had less of an impact advancing leaf-out and flowering phenology by 5.1 (±2.1) and 10.0 (±3.0) days respectively. 4. Our study provides direct evidence that asymmetric winter warming has a larger impact on plant phenology than symmetric year-round warming. Increasing soil temperature in the winter from below to above freezing temperatures advanced the spring phenology of alpine plants. Winter warming increased soil temperature more than year-round warming, which explains why phenology advanced under winter warming more than under year-round warming. In addition, early or mid-season flowering plant species displayed different phenology strategies in warmer winters. 5. Relative to other ecosystems, alpine ecosystems such as the Tibetan Plateau will likely respond to asymmetric warming given the higher amplitude of winter temperature increases due to climatic warming. Conclusively, our data indicate that seasonal variation in warming should be considered when predicting and modelling the response of alpine ecosystems to climatic change.

54 ENVIRONMENTAL SCIENCES↗