Using Ecological Modeling to Enhance Instruction in Population Dynamics and to Stimulate Scientific Thinking

ABSTRACT

Population dynamics has commonly been explored in high-school and undergraduate-level courses in ecology. The techniques used for teaching population dynamics can provide students with the required basic information for learning fundamental concepts in population ecology. However, population dynamics is a complex branch of population ecology that has an essentially quantitative nature. The effective assimilation of this topic should consider basic aspects of population theory, which involves the conceptual understanding of mathematical models. In this study, we propose an alternative methodology for teaching basic concepts of population ecology at the high-school and undergraduate levels, using mathematical models and numerical simulations on a microcomputer. We also show how an instructor or researcher can combine experimentation and theoretical ecology to produce simulations based on the ecology and biology of organisms. The study also suggests a way for teachers and professors to analyze population patterns with real data.

Population dynamics has commonly been explored in high-school and undergraduate-level courses in ecology. The techniques used for teaching population dynamics can provide students with the required basic information for learning fundamental concepts in population ecology. However, population dynamics is a complex branch of population ecology that has an essentially quantitative nature. The effective assimilation of this topic should consider basic aspects of population theory, which involves the conceptual understanding of mathematical models. In this study, we propose an alternative methodology for teaching basic concepts of population ecology at the high-school and undergraduate levels, using mathematical models and numerical simulations on a microcomputer. We also show how an instructor or researcher can combine experimentation and theoretical ecology to produce simulations based on the ecology and biology of organisms. The study also suggests a way for teachers and professors to analyze population patterns with real data.

KEYWORDS

Population Dynamics, Education, Alternative Methodology, Experimental Design, Mathematical Models

Population Dynamics, Education, Alternative Methodology, Experimental Design, Mathematical Models

Cite this paper

nullSerra, H. & Godoy, W. (2011). Using Ecological Modeling to Enhance Instruction in Population Dynamics and to Stimulate Scientific Thinking.*Creative Education, 2,* 83-90. doi: 10.4236/ce.2011.22012.

nullSerra, H. & Godoy, W. (2011). Using Ecological Modeling to Enhance Instruction in Population Dynamics and to Stimulate Scientific Thinking.

References

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[8] Cantrell, R. S., & Cosner, C. (2003). Spatial ecology via reaction- diffusion equations. Chichester: John Wiley and Sons.

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[10] Castanho, M. J. P., Magnago, K. F., Bassanezi, R. C., & Godoy, W. A. C. (2006). Fuzzy subset approach in coupled population dynamics of blowflies. Biological Research, 39, 341-352. doi:10.4067/S0716-97602006000200016

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[12] Eykhoff, P. (1974). System identification: Parameter and State Estimation. London: John Wiley & Sons.

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[14] Godoy, W. A. C., Reis, S. F., Von Zuben, C. J., & Ribeiro, O. B. (1993). Population dynamics of Chrysomya putoria (wied.) (dipt. calliphoridae). Journal of Applied Entomology, 116, 163-169. doi:10.1111/j.1439-0418.1993.tb01184.x

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[17] Hastings, A. (1997). Population biology. New York: Springer-Verlag.

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[20] Javidi, G. (2004). A comparison of traditional physical laboratory and computer simulated laboratory experiences in relation to engineering undergraduate students conceptual understandings of a communication systems topic. Ph. D. Thesis, Florida: University of South Florida. (last checked 20 December, 2010) http://scholarcommons.usf.edu/etd/2936.

[21] Lima, E. A. B. F., Ferreira, C. P., & Godoy, W. A. C. (2009). Ecological modeling and pest population management: A possible and necessary connection in a changing world. Neotropical Entomology, 38, 699-707. doi:10.1590/S1519-566X2009000600001

[22] Linhares, A. X. (1988). The gonotrophic cycle of chrysomya megacephala (diptera, calliphoridae) in the laboratory. Revista Brasileira de Entomologia, 32, 383-392.

[23] Murray, J. D. (2002). Mathematical biology. Washington: Springer, Seattle.

[24] Norris, D. (1994). Shortlist: A connectionist model of continuous speech recognition. Cognition, 52, 189-234. doi:10.1016/0010-0277(94)90043-4

[25] Prout, T., & McChesney, F. (1985). Competition among immatures affects their adult fertility: Population dynamics. American Naturalist, 126, 521-558. doi:10.1086/284436

[26] Roughgarden, J. (1998). Primer of ecological theory. Upper Saddle River, New Jersey: Prentice Hall.

[27] Royama, T. (1992). Analytical population dynamics. London: Chapman & Hall.

[28] Schowalter, T. (2006). Insect ecology. Orlando: Academic Press.

[29] Thompson, A., Simonson M., & Hardgrave, C. (1996). Educational technology: A review of the research (2nd ed.). Washington, DC: Association for Educational Communications and Technology.

[30] Varaki, B. S. (2006). Math modeling in educational research: An approach to methodological fallacies. Australian Journal of Teacher Education, 31, 29-35.

[31] Wu, J., & David, J. L. (2002). A spatially explicit hierarchical approach to modeling complex ecological systems: Theory and applications. Ecological Modeling, 153, 7-26. doi:10.1016/S0304-3800(01)00499-9

[1] Akpan, J. P., & Andre, T. (1999). The effect of a prior dissection simulation on middle school students’ dissection performance and understanding of the anatomy and morphology of the frog. Journal of Science Education and Technology, 8, 107-121. doi:10.1023/A:1018604932197

[2] Alessi, S. M., & Trollip, S. R. (1991). Computer based instruction: methods and development. Upper Saddle River, New Jersey: Prentice Hall.

[3] Amabis, J. M., & Martho, G. R. (2005). Biologia de popula??es: genética, evolu??o e ecologia. S?o Paulo: Ed. Moderna.

[4] Baumgartner, D. L., & Greenberg, B. (1984). The genus Chrysomya (diptera: Calliphoridae) in the new World. Journal of Medical Entomology, 21, 105-113.

[5] Bell, R. L., Smetana, L., & Binns, I. (2005) Simplifying inquiry instruction. The Science Teacher, 72, 30-33.

[6] Bernstein, R. (2003). Population ecology: An introduction to computer simulations. Canada: John Wiley & Sons Canada, Ltd.

[7] Breithach, K., & Maltas, J. (2003). An integrated curriculum in Advanced mathematics/pre-calculus and physics. ULR (last checked 20 December, 2010) http://www.pls.uni. edu/couch/integrated philosophy.htm

[8] Cantrell, R. S., & Cosner, C. (2003). Spatial ecology via reaction- diffusion equations. Chichester: John Wiley and Sons.

[9] Case, T. J. (2000). An illustrated guide of theoretical ecology. New York: Oxford University Press.

[10] Castanho, M. J. P., Magnago, K. F., Bassanezi, R. C., & Godoy, W. A. C. (2006). Fuzzy subset approach in coupled population dynamics of blowflies. Biological Research, 39, 341-352. doi:10.4067/S0716-97602006000200016

[11] Edelstein-Keshet, L. (1988). Mathematical models in biology. New York: Random House.

[12] Eykhoff, P. (1974). System identification: Parameter and State Estimation. London: John Wiley & Sons.

[13] Godoy, W. A. C. (2007). Dynamics of blowfly populations. Functional Ecosystems and Communities, 1, 129-139.

[14] Godoy, W. A. C., Reis, S. F., Von Zuben, C. J., & Ribeiro, O. B. (1993). Population dynamics of Chrysomya putoria (wied.) (dipt. calliphoridae). Journal of Applied Entomology, 116, 163-169. doi:10.1111/j.1439-0418.1993.tb01184.x

[15] Gotelli, N. J. (2001). A primer of ecology (3rd ed.). Sunderland, Massachusetts: Sinauer Associates, Inc.

[16] Green, J. L., Hastings, A., Arzberger, P., Ayala, F. J., Cottingham, K. L., Cuddington, K., Davis, F., Dunne, J. A., Fortin, M. J., Gerber, L., & Neubert, M. (2005). Complexity in ecology and conservation: Mathematical, statistical, and computational challenges. BioScience, 55, 501-510. doi:10.1641/0006-3568(2005)055[0501:CIEACM]2.0.CO;2

[17] Hastings, A. (1997). Population biology. New York: Springer-Verlag.

[18] Hengeveld, R. (1989). Dynamics of biological invasions. New York: Chapman & Hall.

[19] Hilborn, R., & Mangel, M. (1997). The ecological detective: Monographs in population biology. Princeton, New Jersey: Princeton University Press.

[20] Javidi, G. (2004). A comparison of traditional physical laboratory and computer simulated laboratory experiences in relation to engineering undergraduate students conceptual understandings of a communication systems topic. Ph. D. Thesis, Florida: University of South Florida. (last checked 20 December, 2010) http://scholarcommons.usf.edu/etd/2936.

[21] Lima, E. A. B. F., Ferreira, C. P., & Godoy, W. A. C. (2009). Ecological modeling and pest population management: A possible and necessary connection in a changing world. Neotropical Entomology, 38, 699-707. doi:10.1590/S1519-566X2009000600001

[22] Linhares, A. X. (1988). The gonotrophic cycle of chrysomya megacephala (diptera, calliphoridae) in the laboratory. Revista Brasileira de Entomologia, 32, 383-392.

[23] Murray, J. D. (2002). Mathematical biology. Washington: Springer, Seattle.

[24] Norris, D. (1994). Shortlist: A connectionist model of continuous speech recognition. Cognition, 52, 189-234. doi:10.1016/0010-0277(94)90043-4

[25] Prout, T., & McChesney, F. (1985). Competition among immatures affects their adult fertility: Population dynamics. American Naturalist, 126, 521-558. doi:10.1086/284436

[26] Roughgarden, J. (1998). Primer of ecological theory. Upper Saddle River, New Jersey: Prentice Hall.

[27] Royama, T. (1992). Analytical population dynamics. London: Chapman & Hall.

[28] Schowalter, T. (2006). Insect ecology. Orlando: Academic Press.

[29] Thompson, A., Simonson M., & Hardgrave, C. (1996). Educational technology: A review of the research (2nd ed.). Washington, DC: Association for Educational Communications and Technology.

[30] Varaki, B. S. (2006). Math modeling in educational research: An approach to methodological fallacies. Australian Journal of Teacher Education, 31, 29-35.

[31] Wu, J., & David, J. L. (2002). A spatially explicit hierarchical approach to modeling complex ecological systems: Theory and applications. Ecological Modeling, 153, 7-26. doi:10.1016/S0304-3800(01)00499-9