Early snowmelt and warmer, drier summers shrink postflowering transition times in subalpine wildflowers

Ecology ◽  
2020 ◽  
Vol 101 (12) ◽  
Author(s):  
Meera Lee Sethi ◽  
Elli J. Theobald ◽  
Ian Breckheimer ◽  
Janneke Hille Ris Lambers
Keyword(s):  
Early Snowmelt ◽  
Transition Times

Transition Times in Memory

2018 ◽  
Author(s):  
Donatella della Porta ◽  
Massimiliano Andretta ◽  
Tiago Fernandes ◽  
Eduardo Romanos ◽  
Markos Vogiatzoglou
Keyword(s):  
Theoretical Model ◽  
Social Movement ◽  
Transition Period ◽  
Two Dimensions ◽  
Democratic Regime ◽  
Organizational Models ◽  
Different Types ◽  
Transition Times ◽  
Movement Participation

The second chapter covers the main characteristics of transition time in the four countries: Italy, Greece, Spain, and Portugal. After developing the theoretical model on paths of transition, with a focus on social movement participation, the chapter looks at social movements and protest events as turning points during transition, covering in particular the specific movement actors, their organizational models, and their repertoires of action and frames. The chapter focuses on two dimensions: the role of mobilization in the transition period, which implies the analysis of how elites and masses interact, ally, or fight with each other in the process, and the outcome of transitions as continuity versus rupture of the democratic regime vis-à-vis the old one. It concludes by elaborating some hypotheses on how different modes of transition may produce different types and uses of (transition) memories.

scholarly journals Past and future snowmelt trends in the Swiss Alps: the role of temperature and snowpack

2021 ◽  
Vol 165 (3-4) ◽  
Author(s):  
Maria Vorkauf ◽  
Christoph Marty ◽  
Ansgar Kahmen ◽  
Erika Hiltbrunner
Keyword(s):  
Snow Depth ◽  
Growing Season ◽  
High Elevation ◽  
Alpine Plants ◽  
Swiss Alps ◽  
Climate Change Scenarios ◽  
Freezing Damage ◽  
Strong Shift ◽  
Air Temperatures ◽  
Early Snowmelt

AbstractThe start of the growing season for alpine plants is primarily determined by the date of snowmelt. We analysed time series of snow depth at 23 manually operated and 15 automatic (IMIS) stations between 1055 and 2555 m asl in the Swiss Central Alps. Between 1958 and 2019, snowmelt dates occurred 2.8 ± 1.3 days earlier in the year per decade, with a strong shift towards earlier snowmelt dates during the late 1980s and early 1990s, but non-significant trends thereafter. Snowmelt dates at high-elevation automatic stations strongly correlated with snowmelt dates at lower-elevation manual stations. At all elevations, snowmelt dates strongly depended on spring air temperatures. More specifically, 44% of the variance in snowmelt dates was explained by the first day when a three-week running mean of daily air temperatures passed a 5 °C threshold. The mean winter snow depth accounted for 30% of the variance. We adopted the effects of air temperature and snowpack height to Swiss climate change scenarios to explore likely snowmelt trends throughout the twenty-first century. Under a high-emission scenario (RCP8.5), we simulated snowmelt dates to advance by 6 days per decade by the end of the century. By then, snowmelt dates could occur one month earlier than during the reference periods (1990–2019 and 2000–2019). Such early snowmelt may extend the alpine growing season by one third of its current duration while exposing alpine plants to shorter daylengths and adding a higher risk of freezing damage.

scholarly journals Seeds and Seedlings in a Changing World: A Systematic Review and Meta-Analysis from High Altitude and High Latitude Ecosystems

Plants ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 768
Author(s):  
Jerónimo Vázquez-Ramírez ◽  
Susanna E. Venn
Keyword(s):  
Climate Change ◽  
High Altitude ◽  
High Latitude ◽  
Seedling Establishment ◽  
Early Life History ◽  
Life Stages ◽  
Qualitative And Quantitative Analysis ◽  
Qualitative And Quantitative ◽  
Life History Stages ◽  
Early Snowmelt

The early life-history stages of plants, such as germination and seedling establishment, depend on favorable environmental conditions. Changes in the environment at high altitude and high latitude regions, as a consequence of climate change, will significantly affect these life stages and may have profound effects on species recruitment and survival. Here, we synthesize the current knowledge of climate change effects on treeline, tundra, and alpine plants’ early life-history stages. We systematically searched the available literature on this subject up until February 2020 and recovered 835 potential articles that matched our search terms. From these, we found 39 studies that matched our selection criteria. We characterized the studies within our review and performed a qualitative and quantitative analysis of the extracted meta-data regarding the climatic effects likely to change in these regions, including projected warming, early snowmelt, changes in precipitation, nutrient availability and their effects on seed maturation, seed dormancy, germination, seedling emergence and seedling establishment. Although the studies showed high variability in their methods and studied species, the qualitative and quantitative analysis of the extracted data allowed us to detect existing patterns and knowledge gaps. For example, warming temperatures seemed to favor all studied life stages except seedling establishment, a decrease in precipitation had a strong negative effect on seed stages and, surprisingly, early snowmelt had a neutral effect on seed dormancy and germination but a positive effect on seedling establishment. For some of the studied life stages, data within the literature were too limited to identify a precise effect. There is still a need for investigations that increase our understanding of the climate change impacts on high altitude and high latitude plants’ reproductive processes, as this is crucial for plant conservation and evidence-based management of these environments. Finally, we make recommendations for further research based on the identified knowledge gaps.

scholarly journals Adaptive Method for Modeling of Temporal Dependencies between Fields of Vision in Multi-Camera Surveillance Systems

Electronics ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1303
Author(s):  
Karol Lisowski ◽  
Andrzej Czyżewski
Keyword(s):  
Statistical Data ◽  
Input Parameter ◽  
Gaussian Mixture ◽  
Adaptive Method ◽  
Transition Time ◽  
Surveillance Systems ◽  
Modified Particle Swarm Optimization ◽  
Novel Approach ◽  
Transition Times ◽  
Temporal Dependencies

A method of modeling the time of object transition between given pairs of cameras based on the Gaussian Mixture Model (GMM) is proposed in this article. Temporal dependencies modeling is a part of object re-identification based on the multi-camera experimental framework. The previously utilized Expectation-Maximization (EM) approach, requiring setting the number of mixtures arbitrarily as an input parameter, was extended with the algorithm that automatically adapts the model to statistical data. The probabilistic model was obtained by matching to the histogram of transition times between a particular pair of cameras. The proposed matching procedure uses a modified particle swarm optimization (mPSO). A way of using models of transition time in object re-identification is also presented. Experiments with the proposed method of modeling the transition time were carried out, and a comparison between previous and novel approach results are also presented, revealing that added swarms approximate normalized histograms very effectively. Moreover, the proposed swarm-based algorithm allows for modelling the same statistical data with a lower number of summands in GMM.

scholarly journals Event Matching Classification Method for Non-Intrusive Load Monitoring

2021 ◽  
Vol 13 (2) ◽  
pp. 693
Author(s):  
Elnaz Azizi ◽  
Mohammad T. H. Beheshti ◽  
Sadegh Bolouki
Keyword(s):  
Energy Management ◽  
Low Frequency ◽  
Training Dataset ◽  
Mode Transition ◽  
Smart Meters ◽  
Available Energy ◽  
Consumption Values ◽  
Load Monitoring ◽  
Transition Times ◽  
Event Based

Nowadays, energy management aims to propose different strategies to utilize available energy resources, resulting in sustainability of energy systems and development of smart sustainable cities. As an effective approach toward energy management, non-intrusive load monitoring (NILM), aims to infer the power profiles of appliances from the aggregated power signal via purely analytical methods. Existing NILM methods are susceptible to various issues such as the noise and transient spikes of the power signal, overshoots at the mode transition times, close consumption values by different appliances, and unavailability of a large training dataset. This paper proposes a novel event-based NILM classification algorithm mitigating these issues. The proposed algorithm (i) filters power signals and accurately detects all events; (ii) extracts specific features of appliances, such as operation modes and their respective power intervals, from their power signals in the training dataset; and (iii) labels with high accuracy each detected event of the aggregated signal with an appliance mode transition. The algorithm is validated using REDD with the results showing its effectiveness to accurately disaggregate low-frequency measured data by existing smart meters.

scholarly journals Databased prediction and planning of order-specific transition times

Procedia CIRP ◽  
2020 ◽  
Vol 93 ◽  
pp. 885-890
Author(s):  
Günther Schuh ◽  
Andreas Gützlaff ◽  
Frederick Sauermann ◽  
Oliver Kaul ◽  
Nicolas Klein
Keyword(s):  
Transition Times

scholarly journals Spatial patterns of goose grubbing suggest elevated grubbing in dry habitats linked to early snowmelt

2013 ◽  
Vol 32 (1) ◽  
pp. 19719 ◽  
Author(s):  
Åshild Ø Pedersen ◽  
Ingunn Tombre ◽  
Jane U Jepsen ◽  
Pernille B Eidesen ◽  
Eva Fuglei ◽  
...  
Keyword(s):  
Spatial Patterns ◽  
Early Snowmelt

Chrysophycean Microfossils Provide New Insight into the Recent History of a Naturally Acidic Lake (Cone Pond, New Hampshire)

1987 ◽  
Vol 44 (9) ◽  
pp. 1584-1588 ◽  
Author(s):  
Katherine N. Gibson ◽  
John P. Smol ◽  
Jesse Ford
Keyword(s):  
New Hampshire ◽  
Early Spring ◽  
Recent Change ◽  
Fish Populations ◽  
Short Term ◽  
Acidic Lake ◽  
Lake Water Chemistry ◽  
History Of ◽  
Early Snowmelt ◽  
Insight Into

Cone Pond, New Hampshire, is an acidic (pH = 4.5) clearwater lake that is currently fishless. Historical records indicate declining fish populations between 1951 and 1966, but paleolimnological work using diatoms failed to find evidence for further recent acidification of this naturally acid site. We initiated new paleolimnological studies using mallomonadacean chrysophytes to further our understanding of Cone Pond's recent past. Our stratigraphic analyses indicate recent striking changes in the chrysophyte flora of this lake, with Mallomonas hindonii, a species only common in recently acidified lakes, replacing M. crassisquama, a cosmopolitan species that dominated the flora over the preceding 8000 yr; this recent change parallels the declines in fish populations. Because chrysophytes often bloom in early spring and are known, in other lakes, to experience changes in community composition before those expressed by the diatom community, a possibility is that chrysophytes track transient excursions of lake water chemistry associated with early snowmelt conditions. In this scenario, chrysophytes would respond to a constellation of specific short-term chemical changes including, but not restricted to, pH. Such pH associated changes could include changes in concentrations, speciation, or complexation of metals mobilized from the catchment or sediments, all of which are known to affect both chrysophytes and fish.

Heat Conduction and Finite Measures for Transition Times between Steady States

1991 ◽  
Vol 47 (2) ◽  
pp. 193-206 ◽  
Author(s):  
A. MCNABB ◽  
G. C. WAKE
Keyword(s):  
Heat Conduction ◽  
Steady States ◽  
Transition Times ◽  
Finite Measures
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