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Your search keyword '"Petrovskii, Sergei V."' showing total 170 results
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170 results on '"Petrovskii, Sergei V."'

3. Stability of a planetary climate system with the biosphere competing for resources

Author

Vakulenko, Sergey A., Sudakov, Ivan, Petrovskii, Sergei V., and Lukichev, Dmitry V.

Subjects
Nonlinear Sciences - Chaotic Dynamics, Physics - Atmospheric and Oceanic Physics, 37H20, 37C10, 86A05
Abstract

With the growing number of discovered exoplanets, the Gaia concept finds its second wind. The Gaia concept defines that the biosphere of an inhabited planet regulates a planetary climate through feedback loops such that the planet remains habitable. Crunching 'Gaia' puzzle has been a focus of intense empirical research. Much less attention has been paid to the mathematical realization of this concept. In this paper, we consider the stability of a planetary climate system with the dynamic biosphere by linking a conceptual climate model to a generic population dynamics model with random parameters. We first show that the dynamics of the corresponding coupled system possesses multiple timescales and hence falls into the class of slow-fast dynamics. We then investigate the properties of a general dynamical system to which our model belongs and prove that the feedbacks from the biosphere dynamics cannot break the system's stability as long as the biodiversity is sufficiently high. That may explain why the climate is apparently stable over long time intervals. Interestingly, our coupled climate-biosphere system can lose its stability if biodiversity decreases; in this case, the evolution of the biosphere under the effect of random factors can lead to a global climate change., Comment: Submitted

Published
2019
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4. Mathematical Bases for 2D Insect Trap Counts Modelling

Author

Ahmed, Danish A., Bailey, Joseph D., Petrovskii, Sergei V., Bonsall, Michael B., Crippen, Gordon, Advisory Editor, Dress, Andreas, Editor-in-Chief, Giegerich, Robert, Editorial Board Member, Kelso, Janet, Editorial Board Member, Linial, Michal, Editor-in-Chief, Felsenstein, Joseph, Advisory Editor, Troyanskaya, Olga, Editor-in-Chief, Gusfield, Dan, Advisory Editor, Myers, Gene, Editorial Board Member, Istrail, Sorin, Advisory Editor, Pevzner, Pavel, Editorial Board Member, Vingron, Martin, Editor-in-Chief, Lengauer, Thomas, Advisory Editor, McClure, Marcella, Advisory Editor, Nowak, Martin, Advisory Editor, Sankoff, David, Advisory Editor, Shamir, Ron, Advisory Editor, Steel, Mike, Advisory Editor, Stormo, Gary, Advisory Editor, Tavaré, Simon, Advisory Editor, Warnow, Tandy, Advisory Editor, Welch, Lonnie, Advisory Editor, Pham, Tuan D., editor, Yan, Hong, editor, Ashraf, Muhammad W., editor, and Sjöberg, Folke, editor

Published
2021
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5. Assessing Invasion Risk

Author

Lewis, Mark A., Petrovskii, Sergei V., Potts, Jonathan R., Antman, S.S, Editor-in-chief, Durrett, R., Series editor, Greengard, L., Editor-in-chief, Glass, L., Series editor, Holmes, P.J., Editor-in-chief, Goriely, Alain, Series editor, Kohn, R., Series editor, Krishnaprasad, P. S., Series editor, Murray, J.D., Series editor, Peskin, C., Series editor, Sastry, S.S., Series editor, Sneyd, J., Series editor, Lewis, Mark A., Petrovskii, Sergei V., and Potts, Jonathan R.

Published
2016
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6. A User’s Guide to Integrodifference Models for Invasive Spread

Author

Lewis, Mark A., Petrovskii, Sergei V., Potts, Jonathan R., Antman, S.S, Editor-in-chief, Durrett, R., Series editor, Greengard, L., Editor-in-chief, Glass, L., Series editor, Holmes, P.J., Editor-in-chief, Goriely, Alain, Series editor, Kohn, R., Series editor, Krishnaprasad, P. S., Series editor, Murray, J.D., Series editor, Peskin, C., Series editor, Sastry, S.S., Series editor, Sneyd, J., Series editor, Lewis, Mark A., Petrovskii, Sergei V., and Potts, Jonathan R.

Published
2016
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7. Stochastic Spread

Author

Lewis, Mark A., Petrovskii, Sergei V., Potts, Jonathan R., Antman, S.S, Editor-in-chief, Durrett, R., Series editor, Greengard, L., Editor-in-chief, Glass, L., Series editor, Holmes, P.J., Editor-in-chief, Goriely, Alain, Series editor, Kohn, R., Series editor, Krishnaprasad, P. S., Series editor, Murray, J.D., Series editor, Peskin, C., Series editor, Sastry, S.S., Series editor, Sneyd, J., Series editor, Lewis, Mark A., Petrovskii, Sergei V., and Potts, Jonathan R.

Published
2016
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8. Stochasticity and Invasion Dynamics

Author

Lewis, Mark A., Petrovskii, Sergei V., Potts, Jonathan R., Antman, S.S, Editor-in-chief, Durrett, R., Series editor, Greengard, L., Editor-in-chief, Glass, L., Series editor, Holmes, P.J., Editor-in-chief, Goriely, Alain, Series editor, Kohn, R., Series editor, Krishnaprasad, P. S., Series editor, Murray, J.D., Series editor, Peskin, C., Series editor, Sastry, S.S., Series editor, Sneyd, J., Series editor, Lewis, Mark A., Petrovskii, Sergei V., and Potts, Jonathan R.

Published
2016
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9. Introduction

Author

Lewis, Mark A., Petrovskii, Sergei V., Potts, Jonathan R., Antman, S.S, Editor-in-chief, Durrett, R., Series editor, Greengard, L., Editor-in-chief, Glass, L., Series editor, Holmes, P.J., Editor-in-chief, Goriely, Alain, Series editor, Kohn, R., Series editor, Krishnaprasad, P. S., Series editor, Murray, J.D., Series editor, Peskin, C., Series editor, Sastry, S.S., Series editor, Sneyd, J., Series editor, Lewis, Mark A., Petrovskii, Sergei V., and Potts, Jonathan R.

Published
2016
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10. Long-Distance Dispersal and Spread

Author

Lewis, Mark A., Petrovskii, Sergei V., Potts, Jonathan R., Antman, S.S, Editor-in-chief, Durrett, R., Series editor, Greengard, L., Editor-in-chief, Glass, L., Series editor, Holmes, P.J., Editor-in-chief, Goriely, Alain, Series editor, Kohn, R., Series editor, Krishnaprasad, P. S., Series editor, Murray, J.D., Series editor, Peskin, C., Series editor, Sastry, S.S., Series editor, Sneyd, J., Series editor, Lewis, Mark A., Petrovskii, Sergei V., and Potts, Jonathan R.

Published
2016
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11. Dynamics of Biological Invasions

Author

Lewis, Mark A., Petrovskii, Sergei V., Potts, Jonathan R., Antman, S.S, Editor-in-chief, Durrett, R., Series editor, Greengard, L., Editor-in-chief, Glass, L., Series editor, Holmes, P.J., Editor-in-chief, Goriely, Alain, Series editor, Kohn, R., Series editor, Krishnaprasad, P. S., Series editor, Murray, J.D., Series editor, Peskin, C., Series editor, Sastry, S.S., Series editor, Sneyd, J., Series editor, Lewis, Mark A., Petrovskii, Sergei V., and Potts, Jonathan R.

Published
2016
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12. Responding to Invasions: Detection, Control, and Adaptation

Author

Lewis, Mark A., Petrovskii, Sergei V., Potts, Jonathan R., Antman, S.S, Editor-in-chief, Durrett, R., Series editor, Greengard, L., Editor-in-chief, Glass, L., Series editor, Holmes, P.J., Editor-in-chief, Goriely, Alain, Series editor, Kohn, R., Series editor, Krishnaprasad, P. S., Series editor, Murray, J.D., Series editor, Peskin, C., Series editor, Sastry, S.S., Series editor, Sneyd, J., Series editor, Lewis, Mark A., Petrovskii, Sergei V., and Potts, Jonathan R.

Published
2016
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13. Reaction–Diffusion Models: Single Species

Author

Lewis, Mark A., Petrovskii, Sergei V., Potts, Jonathan R., Antman, S.S, Editor-in-chief, Durrett, R., Series editor, Greengard, L., Editor-in-chief, Glass, L., Series editor, Holmes, P.J., Editor-in-chief, Goriely, Alain, Series editor, Kohn, R., Series editor, Krishnaprasad, P. S., Series editor, Murray, J.D., Series editor, Peskin, C., Series editor, Sastry, S.S., Series editor, Sneyd, J., Series editor, Lewis, Mark A., Petrovskii, Sergei V., and Potts, Jonathan R.

Published
2016
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14. Invasion in a Multispecies System

Author

Lewis, Mark A., Petrovskii, Sergei V., Potts, Jonathan R., Antman, S.S, Editor-in-chief, Durrett, R., Series editor, Greengard, L., Editor-in-chief, Glass, L., Series editor, Holmes, P.J., Editor-in-chief, Goriely, Alain, Series editor, Kohn, R., Series editor, Krishnaprasad, P. S., Series editor, Murray, J.D., Series editor, Peskin, C., Series editor, Sastry, S.S., Series editor, Sneyd, J., Series editor, Lewis, Mark A., Petrovskii, Sergei V., and Potts, Jonathan R.

Published
2016
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16. Simulating capture efficiency of pitfall traps based on sampling strategy and the movement of ground‐dwelling arthropods

Author

Ahmed, Danish A., primary, Beidas, Ayah, additional, Petrovskii, Sergei V., additional, Bailey, Joseph D., additional, Bonsall, Michael B., additional, Hood, Amelia S. C., additional, Byers, John A., additional, Hudgins, Emma J., additional, Russell, James C., additional, Růžičková, Jana, additional, Bodey, Thomas W., additional, Renault, David, additional, Bonnaud, Elsa, additional, Haubrock, Phillip J., additional, Soto, Ismael, additional, and Haase, Peter, additional

Published
2023
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45. Spatiotemporal complexity of plankton and fish dynamics

Author

Medvinsky, Alexander B., Petrovskii, Sergei V., Tikhonova, Irene A., Malchow, Horst, and Li, Bai-Lian

Subjects
Fishes -- Genetic aspects, Biological systems -- Influence, Mathematics
Abstract

The complexity and disorder in the spatiotemporal arrangement of aquatic environments, and the influence of biological systems on this arrangement are investigated. It is shown with the help of results that modeling by reaction-diffusion equations method is considered suitable to examine basic processes of intricate spatiotemporal fish and plankton dynamics.

Published
2002

46. Revisiting Brownian motion as a description of animal movement: a comparison to experimental movement data

Author

Bearup, Daniel, Benefer, Carly M., Petrovskii, Sergei V., Blackshaw, Rod P., Bearup, Daniel, Benefer, Carly M., Petrovskii, Sergei V., and Blackshaw, Rod P.

Abstract

1) Characterization of patterns of animal movement is a major challenge in ecology with applications to conservation, biological invasions and pest monitoring. Brownian random walks, and diffusive flux as their mean field counterpart, provide one framework in which to consider this problem. However, it remains subject to debate and controversy. This study presents a test of the diffusion framework using movement data obtained from controlled experiments. 2) Walking beetles (Tenebrio molitor) were released in an open circular arena with a central hole and the number of individuals falling from the arena edges was monitored over time. These boundary counts were compared, using curve fitting, to the predictions of a diffusion model. The diffusion model is solved precisely, without using numerical simulations. 3) We find that the shape of the curves derived from the diffusion model is a close match to those found experimentally. Furthermore, in general, estimates of the total population obtained from the relevant solution of the diffusion equation are in excellent agreement with the experimental population. Estimates of the dispersal rate of individuals depend on how accurately the initial release distribution is incorporated into the model. 4) We therefore show that diffusive flux is a very good approximation to the movement of a population of Tenebrio molitor beetles. As such, we suggest that it is an adequate theoretical/modelling framework for ecological studies that account for insect movement, although it can be context specific. An immediate practical application of this can be found in the interpretation of trap counts, in particular for the purpose of pest monitoring.

Published
2016

49. Towards the Development of a More Accurate Monitoring Procedure for Invertebrate Populations, in the Presence of an Unknown Spatial Pattern of Population Distribution in the Field.

Author

Petrovskaya, Natalia B., Forbes, Emily, Petrovskii, Sergei V., and Walters, Keith F. A.

Subjects
INVERTEBRATE populations, STATISTICAL bootstrapping, RANDOM variables, POPULATION density, SPARSELY populated areas
Abstract

Studies addressing many ecological problems require accurate evaluation of the total population size. In this paper, we revisit a sampling procedure used for the evaluation of the abundance of an invertebrate population from assessment data collected on a spatial grid of sampling locations. We first discuss how insufficient information about the spatial population density obtained on a coarse sampling grid may affect the accuracy of an evaluation of total population size. Such information deficit in field data can arise because of inadequate spatial resolution of the population distribution (spatially variable population density) when coarse grids are used, which is especially true when a strongly heterogeneous spatial population density is sampled. We then argue that the average trap count (the quantity routinely used to quantify abundance), if obtained from a sampling grid that is too coarse, is a random variable because of the uncertainty in sampling spatial data. Finally, we show that a probabilistic approach similar to bootstrapping techniques can be an efficient tool to quantify the uncertainty in the evaluation procedure in the presence of a spatial pattern reflecting a patchy distribution of invertebrates within the sampling grid. [ABSTRACT FROM AUTHOR]

Published
2018
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