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Year 2019, Volume: 11, 11 - 15, 30.12.2019

Abstract

Project Number

0000-0001-7545-1824

References

  • Abbott, M. R., Phytoplankton patchiness: Ecological implications and observation methods, In Patch Dynamics, Springer, \textbf{96}(1993), 37--49.
  • Allegretto, W., Mocenni, C., Vicino, A., {\em Periodic solutions in modelling lagoon ecological interactions}, Journal of mathematical biology, \textbf{51}(2005), 367--388.
  • Edwards, A.M., Brindley, J., {\em Zooplankton mortality and the dynamical behaviour of plankton population models}, Bulletin of Mathematical Biology, \textbf{61}(1999), 303--339.
  • Fasham, M., {\em The statistical and mathematical analysis of plankton patchiness}, Oceanogr. Marine Biology Annual Rev., 16(1978), 43--79.
  • Guttal, V., Jayaprakash, C., {\em Changing skewness: An early warning signal of regime shifts in ecosystems}, Ecology letters, \textbf{11(5)}(2008), 450-460.
  • Hull, V., Mocenni, C., Falcucci, M., Marchettini, N., {\em A trophodynamic model for the lagoon of fogliano (italy) with ecological dependent modifying parameters}, Ecological modelling, \textbf{134}(2000), 153--167.
  • Mackas, D.L., Boyd, C.M., {\em Spectral analysis of zooplankton spatial heterogeneity}, Science, \textbf{204}(1979), 62--64.
  • Malchow, H., Petrovskii, S.V., Hilker, F.M., {\em Models of spatiotemporal pattern formation in plankton dynamics}, Nova Acta Leopoldina NF, \textbf{88}(2003), 325--340.
  • Malchow, H., Petrovskii, S.V., Venturino, E., Spatiotemporal patterns in ecology and epidemiology: theory, models, and simulation. Chapman \& Hall/CRC Press London, 2008.
  • Marchettini, N., Mocenni, C., Vicino, A., {\em Integrating slow and fast dynamics in a shallow water coastal lagoon}, Annali di chimica, \textbf{89}(1999), 505--514.
  • Medvinsky, A.B., et al., {\em Spatiotemporal complexity of plankton and fish dynamics}, SIAM Review., \textbf{44}(2002), 311--370.
  • Misra, A., {\em Modeling the depletion of dissolved oxygen in a lake due to submerged macrophytes}, Nonlinear Anal. Model. Cont., \textbf{15}(2010), 185--198.
  • Okubo, A., Diffusion and Ecological Problems: Mathematical Models, Springer-Verlag Berlin, Vol.10, 1980.
  • Petrovskii, S.V., Malchow, H., Mathematical Models of Marine Ecosystems. Mathematical Models, In: The Encyclopedia of Life Support Systems (EOLSS), EOLSS Publishers, Oxford UK, 2004.
  • Scheffer, M., Carpenter, S., Foley, J.A., Folke, C., Walker, B., {\em Catastrophic shifts in ecosystems}, Nature, \textbf{413(6856)}(2001), 591.
  • Scheffer, M., et.al., {\em Early-warning signals for critical transitions}, Nature, \textbf{461(7260)}(2009), 53.
  • Sekerci, Y., Petrovskii, S., {\em Mathematical modelling of plankton--oxygen dynamics under the climate change}, Bulletin of Mathematical Biology, \textbf{77(12)}(2015), 2325--2353.

Early Warning Signals of Oxygen-Plankton Dynamics: Mathematical Approach

Year 2019, Volume: 11, 11 - 15, 30.12.2019

Abstract

Any significant decrease in net oxygen production by phytoplankton is likely to result in the loss of atmospheric oxygen and the global extinction of living beings owing to more than half of the atmospheric oxygen provided by marine phytoplankton. The rate of oxygen production is known to depend on water temperature and hence can therefore be affected by global warming.  In this work, it is assumed that oxygen production varies with time under the effect of increasing temperature.  This ecological problem is addressed  theoretically by a couple of plankton-oxygen dynamics. A nonlinear mathematical model is considered to investigate the effect of temperature on oxygen-plankton dynamics. The model is analysed analytical and numerical ways, based on the behavior and complexity of the system's steady state. From the analysis of the model, it has been observed that as temperature level goes above the critical threshold of oxygen production rate  the equilibrium density of plankton population decrease due to a decrease in oxygen concentration. It has also been shown that the system can exhibit sustainable dynamics that can still lead to an environmental disaster, i.e. oxygen depletion and plankton extinction. In this case, extinction takes place after a considerable length  of time.

Supporting Institution

Amasya Universitesi

Project Number

0000-0001-7545-1824

Thanks

This research has been supported by Amasya University Scientific Research Projects Coordination Unit. Project Number: FBM-BAP 18-0337.

References

  • Abbott, M. R., Phytoplankton patchiness: Ecological implications and observation methods, In Patch Dynamics, Springer, \textbf{96}(1993), 37--49.
  • Allegretto, W., Mocenni, C., Vicino, A., {\em Periodic solutions in modelling lagoon ecological interactions}, Journal of mathematical biology, \textbf{51}(2005), 367--388.
  • Edwards, A.M., Brindley, J., {\em Zooplankton mortality and the dynamical behaviour of plankton population models}, Bulletin of Mathematical Biology, \textbf{61}(1999), 303--339.
  • Fasham, M., {\em The statistical and mathematical analysis of plankton patchiness}, Oceanogr. Marine Biology Annual Rev., 16(1978), 43--79.
  • Guttal, V., Jayaprakash, C., {\em Changing skewness: An early warning signal of regime shifts in ecosystems}, Ecology letters, \textbf{11(5)}(2008), 450-460.
  • Hull, V., Mocenni, C., Falcucci, M., Marchettini, N., {\em A trophodynamic model for the lagoon of fogliano (italy) with ecological dependent modifying parameters}, Ecological modelling, \textbf{134}(2000), 153--167.
  • Mackas, D.L., Boyd, C.M., {\em Spectral analysis of zooplankton spatial heterogeneity}, Science, \textbf{204}(1979), 62--64.
  • Malchow, H., Petrovskii, S.V., Hilker, F.M., {\em Models of spatiotemporal pattern formation in plankton dynamics}, Nova Acta Leopoldina NF, \textbf{88}(2003), 325--340.
  • Malchow, H., Petrovskii, S.V., Venturino, E., Spatiotemporal patterns in ecology and epidemiology: theory, models, and simulation. Chapman \& Hall/CRC Press London, 2008.
  • Marchettini, N., Mocenni, C., Vicino, A., {\em Integrating slow and fast dynamics in a shallow water coastal lagoon}, Annali di chimica, \textbf{89}(1999), 505--514.
  • Medvinsky, A.B., et al., {\em Spatiotemporal complexity of plankton and fish dynamics}, SIAM Review., \textbf{44}(2002), 311--370.
  • Misra, A., {\em Modeling the depletion of dissolved oxygen in a lake due to submerged macrophytes}, Nonlinear Anal. Model. Cont., \textbf{15}(2010), 185--198.
  • Okubo, A., Diffusion and Ecological Problems: Mathematical Models, Springer-Verlag Berlin, Vol.10, 1980.
  • Petrovskii, S.V., Malchow, H., Mathematical Models of Marine Ecosystems. Mathematical Models, In: The Encyclopedia of Life Support Systems (EOLSS), EOLSS Publishers, Oxford UK, 2004.
  • Scheffer, M., Carpenter, S., Foley, J.A., Folke, C., Walker, B., {\em Catastrophic shifts in ecosystems}, Nature, \textbf{413(6856)}(2001), 591.
  • Scheffer, M., et.al., {\em Early-warning signals for critical transitions}, Nature, \textbf{461(7260)}(2009), 53.
  • Sekerci, Y., Petrovskii, S., {\em Mathematical modelling of plankton--oxygen dynamics under the climate change}, Bulletin of Mathematical Biology, \textbf{77(12)}(2015), 2325--2353.
There are 17 citations in total.

Details

Primary Language English
Subjects Mathematical Sciences
Journal Section Articles
Authors

Yadigar Şekerci Fırat 0000-0001-7545-1824

Project Number 0000-0001-7545-1824
Publication Date December 30, 2019
Published in Issue Year 2019 Volume: 11

Cite

APA Şekerci Fırat, Y. (2019). Early Warning Signals of Oxygen-Plankton Dynamics: Mathematical Approach. Turkish Journal of Mathematics and Computer Science, 11, 11-15.
AMA Şekerci Fırat Y. Early Warning Signals of Oxygen-Plankton Dynamics: Mathematical Approach. TJMCS. December 2019;11:11-15.
Chicago Şekerci Fırat, Yadigar. “Early Warning Signals of Oxygen-Plankton Dynamics: Mathematical Approach”. Turkish Journal of Mathematics and Computer Science 11, December (December 2019): 11-15.
EndNote Şekerci Fırat Y (December 1, 2019) Early Warning Signals of Oxygen-Plankton Dynamics: Mathematical Approach. Turkish Journal of Mathematics and Computer Science 11 11–15.
IEEE Y. Şekerci Fırat, “Early Warning Signals of Oxygen-Plankton Dynamics: Mathematical Approach”, TJMCS, vol. 11, pp. 11–15, 2019.
ISNAD Şekerci Fırat, Yadigar. “Early Warning Signals of Oxygen-Plankton Dynamics: Mathematical Approach”. Turkish Journal of Mathematics and Computer Science 11 (December 2019), 11-15.
JAMA Şekerci Fırat Y. Early Warning Signals of Oxygen-Plankton Dynamics: Mathematical Approach. TJMCS. 2019;11:11–15.
MLA Şekerci Fırat, Yadigar. “Early Warning Signals of Oxygen-Plankton Dynamics: Mathematical Approach”. Turkish Journal of Mathematics and Computer Science, vol. 11, 2019, pp. 11-15.
Vancouver Şekerci Fırat Y. Early Warning Signals of Oxygen-Plankton Dynamics: Mathematical Approach. TJMCS. 2019;11:11-5.