Short Term Minutes-timescale Temporal Variation Statistics of Sodium Layer Dynamics

Shallow fluvial lakes are heterogeneous ecosystems in which marked spatio-temporal variation renders difficult the analysis of key ecological processes, such as growth. In this study, we used generalized additive modelling of the RNA/DNA ratio, an index of short-term growth, to investigate the influence of environmental variables and spatio-temporal variation on growth of yellow perch (Perca flavescens) in Lake St. Pierre, Quebec, Canada. Temperature and water level had seemingly stronger effects on short-term growth than seasonal change or spatial variation between and along the lakeshores. Consistent with previous studies, the maximum RNA/DNA ratio was found at 20.5 °C, suggesting that our approach provides a useful tool for estimating thermal optima for growth in the field. The RNA/DNA ratio showed a positive relationship with water level, as predicted by the flood pulse concept, a finding with implications for ecosystem productivity in fluvial lakes. The RNA/DNA ratio was more variable along the north than the south shore, possibly reflecting exposure to more differentiated water masses. The negative influence of both high temperatures and low water levels on growth points to potential impacts of climatic change on fish production in shallow fluvial lakes.

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Short term spatial and temporal variation of phytoplankton in a shallow tropical oligotrophic reservoir, southeast Brazil

Hydrobiologia ◽

10.1007/s10750-004-8332-z ◽

2005 ◽

Vol 542 (1) ◽

pp. 235-247 ◽

Cited By ~ 69

Author(s):

Maria Rosélia Marques Lopes ◽

Carlos E. de M. Bicudo ◽

M. Carla Ferragut

Keyword(s):

Temporal Variation ◽

Spatial And Temporal Variation ◽

Short Term ◽

Southeast Brazil

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Short-term spatial and temporal variation of sediment oxygen dynamics in a tropical tidal salt flat

Wetlands Ecology and Management ◽

10.1007/s11273-011-9223-5 ◽

2011 ◽

Vol 19 (5) ◽

pp. 389-395 ◽

Cited By ~ 2

Author(s):

Vinícius Peruzzi de Oliveira ◽

Luiz Fernando Jardim Bento ◽

Alex Enrich Prast

Keyword(s):

Temporal Variation ◽

Spatial And Temporal Variation ◽

Short Term ◽

Salt Flat ◽

Oxygen Dynamics

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Removing Time Variation with the Anti-Hebbian Differential Synapse

Neural Computation ◽

10.1162/neco.1991.3.3.312 ◽

1991 ◽

Vol 3 (3) ◽

pp. 312-320 ◽

Cited By ~ 42

Author(s):

Graeme Mitchison

Keyword(s):

Temporal Variation ◽

Time Variation ◽

Synaptic Weight ◽

Receptive Fields ◽

Learning Rule ◽

Temporal Changes ◽

Short Term ◽

Conservation Condition ◽

Rule Changes ◽

Synaptic Learning

I describe a local synaptic learning rule that can be used to remove the effects of certain types of systematic temporal variation in the inputs to a unit. According to this rule, changes in synaptic weight result from a conjunction of short-term temporal changes in the inputs and the output. Formally, This is like the differential rule proposed by Klopf (1986) and Kosko (1986), except for a change of sign, which gives it an anti-Hebbian character. By itself this rule is insufficient. A weight conservation condition is needed to prevent the weights from collapsing to zero, and some further constraint—implemented here by a biasing term—to select particular sets of weights from the subspace of those which give minimal variation. As an example, I show that this rule will generate center-surround receptive fields that remove temporally varying linear gradients from the inputs.

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Short-term variation in near-highway air pollutant gradients on a winter morning

Atmospheric Chemistry and Physics ◽

10.5194/acp-10-8341-2010 ◽

2010 ◽

Vol 10 (17) ◽

pp. 8341-8352 ◽

Cited By ~ 35

Author(s):

J. L. Durant ◽

C. A. Ash ◽

E. C. Wood ◽

S. C. Herndon ◽

J. T. Jayne ◽

...

Keyword(s):

Boundary Layer ◽

Wind Speed ◽

Temporal Variation ◽

Traffic Flow ◽

Organic Compounds ◽

Temporal Variations ◽

Surface Boundary ◽

Short Term ◽

Surface Boundary Layer ◽

Near Highway

Abstract. Quantification of exposure to traffic-related air pollutants near highways is hampered by incomplete knowledge of the scales of temporal variation of pollutant gradients. The goal of this study was to characterize short-term temporal variation of vehicular pollutant gradients within 200–400 m of a major highway (>150 000 vehicles/d). Monitoring was done near Interstate 93 in Somerville (Massachusetts) from 06:00 to 11:00 on 16 January 2008 using a mobile monitoring platform equipped with instruments that measured ultrafine and fine particles (6–1000 nm, particle number concentration (PNC)); particle-phase (>30 nm) NO3−, SO42−, and organic compounds; volatile organic compounds (VOCs); and CO2, NO, NO2, and O3. We observed rapid changes in pollutant gradients due to variations in highway traffic flow rate, wind speed, and surface boundary layer height. Before sunrise and peak traffic flow rates, downwind concentrations of particles, CO2, NO, and NO2 were highest within 100–250 m of the highway. After sunrise pollutant levels declined sharply (e.g., PNC and NO were more than halved) and the gradients became less pronounced as wind speed increased and the surface boundary layer rose allowing mixing with cleaner air aloft. The levels of aromatic VOCs and NO3−, SO42− and organic aerosols were generally low throughout the morning, and their spatial and temporal variations were less pronounced compared to PNC and NO. O3 levels increased throughout the morning due to mixing with O3-enriched air aloft and were generally lowest near the highway reflecting reaction with NO. There was little if any evolution in the size distribution of 6–225 nm particles with distance from the highway. These results suggest that to improve the accuracy of exposure estimates to near-highway pollutants, short-term (e.g., hourly) temporal variations in pollutant gradients must be measured to reflect changes in traffic patterns and local meteorology.

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On the temporally flexible structure of plant-pollinator interaction networks

10.1101/2020.04.11.037366 ◽

2020 ◽

Author(s):

Paul J. CaraDonna ◽

Nickolas M. Waser

Keyword(s):

Temporal Variation ◽

Network Structure ◽

Species Interactions ◽

Interspecific Interactions ◽

Activity Period ◽

Individual Species ◽

Ecological Communities ◽

Short Term ◽

Temporal Flexibility ◽

Plant Pollinator

AbstractEcological communities consist of species that are joined in complex networks of interspecific interaction. The interactions that networks depict often form and dissolve rapidly, but this temporal variation is not well integrated into our understanding of the causes and consequences of network structure. If interspecific interactions exhibit temporal flexibility across time periods over which organisms co-occur, then the emergent structure of the corresponding network may also be temporally flexible, something that a temporally-static perspective would miss. Here, we use an empirical system to examine short-term flexibility in network structure (connectance, nestedness, and specialization), and in individual species interactions that contribute to that structure. We investigated weekly plant-pollinator networks in a subalpine ecosystem across three summer growing seasons. To link the interactions of individual species to properties of their networks, we examined weekly temporal variation in species’ contributions to network structure. As a test of the potential robustness of networks to perturbation, we also simulated the random loss of species from weekly networks. We then compared the properties of weekly networks to the properties of cumulative networks that aggregate field observations over each full season. A week-to-week view reveals considerable flexibility in the interactions of individual species and their contributions to network structure. For example, species that would be considered relatively generalized across their entire activity period may be much more specialized at certain times, and at no point as generalized as the cumulative network may suggest. Furthermore, a week-to-week view reveals corresponding temporal flexibility in network structure and potential robustness throughout each summer growing season. We conclude that short-term flexibility in species interactions leads to short-term variation in network properties, and that a season-long, cumulative perspective may miss important aspects of the way in which species interact, with implications for understanding their ecology, evolution, and conservation.

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