Allocating Foraging Effort Across Multiple Time Scales: Behavioral Responses to Environmental Conditions by Harlequin Ducks Wintering at Cape St. Mary's, Newfoundland

Waterbirds ◽  
2008 ◽  
pp. 71 ◽  
Keyword(s):  
Time Scales ◽  
Environmental Conditions ◽  
Behavioral Responses ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Foraging Effort ◽  
Harlequin Ducks

SOME REMARKS ON THE MULTIPLE TIME SCALES OF DIFFUSION IN MINERALS AND MELTS

2018 ◽  
Author(s):  
Yan Liang ◽  
◽  
Daniele J. Cherniak ◽  
Chenguang Sun
Keyword(s):  
Time Scales ◽  
Multiple Time Scales ◽  
Multiple Time

scholarly journals Are We Doing ‘Systems’ Research? An Assessment of Methods for Climate Change Adaptation to Hydrohazards in a Complex World

2019 ◽  
Vol 11 (4) ◽  
pp. 1163 ◽  
Author(s):  
Melissa Bedinger ◽  
Lindsay Beevers ◽  
Lila Collet ◽  
Annie Visser
Keyword(s):  
Climate Change ◽  
Human Nature ◽  
Climate Change Adaptation ◽  
Time Scales ◽  
Spatial Scales ◽  
Local Context ◽  
Multiple Time Scales ◽  
Future Research ◽  
Multiple Time ◽  
Systems Research

Climate change is a product of the Anthropocene, and the human–nature system in which we live. Effective climate change adaptation requires that we acknowledge this complexity. Theoretical literature on sustainability transitions has highlighted this and called for deeper acknowledgment of systems complexity in our research practices. Are we heeding these calls for ‘systems’ research? We used hydrohazards (floods and droughts) as an example research area to explore this question. We first distilled existing challenges for complex human–nature systems into six central concepts: Uncertainty, multiple spatial scales, multiple time scales, multimethod approaches, human–nature dimensions, and interactions. We then performed a systematic assessment of 737 articles to examine patterns in what methods are used and how these cover the complexity concepts. In general, results showed that many papers do not reference any of the complexity concepts, and no existing approach addresses all six. We used the detailed results to guide advancement from theoretical calls for action to specific next steps. Future research priorities include the development of methods for consideration of multiple hazards; for the study of interactions, particularly in linking the short- to medium-term time scales; to reduce data-intensivity; and to better integrate bottom–up and top–down approaches in a way that connects local context with higher-level decision-making. Overall this paper serves to build a shared conceptualisation of human–nature system complexity, map current practice, and navigate a complexity-smart trajectory for future research.

scholarly journals A multistate model incorporating estimation of excess hazards and multiple time scales

2021 ◽  
Vol 40 (9) ◽  
pp. 2139-2154
Author(s):  
Caroline E. Weibull ◽  
Paul C. Lambert ◽  
Sandra Eloranta ◽  
Therese M. L. Andersson ◽  
Paul W. Dickman ◽  
...  
Keyword(s):  
Time Scales ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Multistate Model

scholarly journals Scale-dependent intrinsic entropies of complex time series

2016 ◽  
Vol 374 (2065) ◽  
pp. 20150204 ◽  
Author(s):  
Jia-Rong Yeh ◽  
Chung-Kang Peng ◽  
Norden E. Huang
Keyword(s):  
Time Series ◽  
Time Scales ◽  
Spatial Scales ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Complex Time ◽  
Multi Scale ◽  
Mode Decomposition ◽  
Simulated Time ◽  
Simulated Time Series

Multi-scale entropy (MSE) was developed as a measure of complexity for complex time series, and it has been applied widely in recent years. The MSE algorithm is based on the assumption that biological systems possess the ability to adapt and function in an ever-changing environment, and these systems need to operate across multiple temporal and spatial scales, such that their complexity is also multi-scale and hierarchical. Here, we present a systematic approach to apply the empirical mode decomposition algorithm, which can detrend time series on various time scales, prior to analysing a signal’s complexity by measuring the irregularity of its dynamics on multiple time scales. Simulated time series of fractal Gaussian noise and human heartbeat time series were used to study the performance of this new approach. We show that our method can successfully quantify the fractal properties of the simulated time series and can accurately distinguish modulations in human heartbeat time series in health and disease.

scholarly journals Release of a single neurotransmitter from an identified interneuron coherently affects motor output on multiple time scales

2013 ◽  
Vol 109 (9) ◽  
pp. 2327-2334 ◽  
Author(s):  
Andrew M. Dacks ◽  
Klaudiusz R. Weiss
Keyword(s):  
Time Scales ◽  
Motor Program ◽  
Gaba Release ◽  
Motor Output ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Intrinsic Properties ◽  
Buccal Ganglion ◽  
Motor Programs ◽  
Pattern Characteristic

Neurotransmitters can have diverse effects that occur over multiple time scales often making the consequences of neurotransmission difficult to predict. To explore the consequences of this diversity, we used the buccal ganglion of Aplysia to examine the effects of GABA release by a single interneuron, B40, on the intrinsic properties and motor output of the radula closure neuron B8. B40 induces a picrotoxin-sensitive fast IPSP lasting milliseconds in B8 and a slow EPSP lasting seconds. We found that the excitatory effects of this slow EPSP are also mediated by GABA. Together, these two GABAergic actions structure B8 firing in a pattern characteristic of ingestive programs. Furthermore, we found that repeated B40 stimulation induces a persistent increase in B8 excitability that was occluded in the presence of the GABA B receptor agonist baclofen, suggesting that GABA affects B8 excitability over multiple time scales. The phasing of B8 activity during the feeding motor programs determines the nature of the behavior elicited during that motor program. The persistent increase in B8 excitability induced by B40 biased the activity of B8 during feeding motor programs causing the motor programs to become more ingestive in nature. Thus, a single transmitter released from a single interneuron can have consequences for motor output that are expressed over multiple time scales. Importantly, despite the differences in their signs and temporal characteristics, the three actions of B40 are coherent in that they promote B8 firing patterns that are characteristic of ingestive motor outputs.

Application of an optimality-based model to operate at half-hourly timestep to implement plant acclimation within a land-surface modelling framework

2021 ◽  
Author(s):  
Giulia Mengoli ◽  
Anna Agustí-Panareda ◽  
Souhail Boussetta ◽  
Sandy P. Harrison ◽  
Carlo Trotta ◽  
...  
Keyword(s):  
Time Scales ◽  
Land Surface ◽  
Multiple Time Scales ◽  
Multiple Time ◽  
Extended Model ◽  
Test Model ◽  
Area Index ◽  
Surface Modelling ◽  
Plant Acclimation ◽  
Land Surface Modelling

<p>Vegetation and atmosphere are linked through the perpetual exchange of water, carbon and energy. An accurate representation of the processes involved in these exchanges is crucial in forecasting Earth system states. Although vegetation has become an undisputed key component in land-surface modelling (LSMs), the current generation of models differ in terms of how key processes are formulated. Plant processes react to environmental changes on multiple time scales. Here we differentiate a fast (minutes) and a slower (acclimated – weeks to months) response. Some current LSMs include plant acclimation, even though they require additional parameters to represent this response, but the majority of them represent only the fast response and assume that this also applies at longer time scales. Ignoring acclimation in this way could be the cause of inconsistent future projections. Our proposition is to include plant acclimation in a LSM schema, without having to include new plant-functional-type-dependent parameters. This is possible by using an alternative model development strategy based on eco-evolutionary theory, which explicitly predicts the acclimation of photosynthetic capacities and stomatal behaviour to environmental variations. So far, this theory has been tested only at weekly to monthly timescales. Here we develop and test an approach to apply an existing optimality-based model of gross primary production (GPP), the P model, at the sub-daily timestep necessary for use in an LSM, making an explicit differentiation between the fast and slow responses of photosynthesis and stomatal conductance. We test model performance in reproducing the diurnal cycle of GPP as recorded by flux tower measurements across different biomes, including boreal and tropical forests. The extended model requires only a few meteorological inputs, and a satellite-derived product for leaf area index or green vegetation cover. It is able to manage both timescales of acclimation without PFT-dependent photosynthetic parameters and has shown to operate with very good performance at all sites so far investigated. The model structure avoids the need to store past climate and vegetation states. These findings therefore suggest a simple way to include both instantaneous and acclimated responses within a LSM framework, and to do so in a robust way that does not require the specification of multiple parameters for different plant functional types.</p>

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