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A FREE ACCESSIBLE INDIVIDUAL-BASED SIMULATOR ENABLING VIRTUAL EXPERIMENTS ON SOIL ORGANIC MATTER PROCESSES IN CLASSROOM

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Abstract (2. Language): 
This work addresses and aims to fulfil a very clear need in teaching biosystem engineering. When introducing students to the complexity of soil processes, one of the frustrations that teachers ofen experience is the impossibility to demonstrate practically, in the lab, some of the concepts and processes discussed in class. Either the experiments take far longer than a typical laboratory session or they require access to specific equipment. To deal with this situation, it would be ideal for students to be able to do virtual experiments. The purpose of this work is to display the individual-based simulation model INDISIM-SOM, available free from a website, and to show how it can be used in experiments or as a teaching-learning instrument in the classroom. The computational model has been designed specifically for the study of soil organic matter and is based mainly on the activity conducted by two diferent prototypes of microorganisms. One option of using INDISIMSOM is as a way to introduce the individual-based model as a methodology to improve understanding of the agents involved in soil microbial system and their processes. Another option is to develop the ability to work with simulators by connecting concepts and helping students in the development of modelling competence. Virtual experiments were carried out as an example of what may be expected from using the INDISIM-SOM web simulator. Temporal evolutions of five virtual soils with diferent organic C content and proportional content in organic N, easily hidrolyzable N, nitrate and ammonia were generated and discussed.
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REFERENCES

References: 

Bravo, C., van Joolingen, W.R., & de Jong, T. (2009). Using Co-Lab to build system dynamics models: Student’s
ac tions and on line tutorial advice. Computers & Educaton, 53, 243-251.
http://dx.doi.org/10.1016/j.compedu.2009.02.005
Faraco, G., & Gabriele, L. (2007). Using LabVIEW for applying mathematical models in representing phenomena.
Computers & Educaton, 49, 856-872. http://dx.doi.org/10.1016/j.compedu.2005.11.025
Ginovart, M., López, D., & Valls, J. (2002) INDISIM, an individual based discrete simulation model to study
bacterial cultures. Journal of Theoretcal Biology, 214, 305-319. http://dx.doi.org/10.1006/jtbi.2001.2466
Ginovart, M, Gras, A, & López, D. (2005). Individual-based modelling of microbial activity to study
mineralization of C and N and nitrification process in soil. NonLinear Analysis: Real World Applicatons, 6, 773-
795. http://dx.doi.org/10.1016/j.nonrwa.2004.12.005
Ginovart, M., Prats, C., Portell, X., & Silbert, M. (2011). Analysis of the efect of inoculum characteristics on the
first stages of a growing yeast population in beer fermentations by means of an Individual-based Model.
Journal of Industrial Microbiology and Biotechnology, 38, 153-165. http://dx.doi.org/10.1007/s10295-010-
0840-4
Ginovart, M., Portell, X., Ferrer-Closas, P., & Blanco, M. (2012). Modelos basados en el individuo: una
metodologia alternativa y atractiva para el estudio de biosistemas. Enseñanza de las ciencias, 30, 93-108.
Gras, A., Cañadas, J.C., & Ginovart, M. (2010a). INDISIM-SOM: an individual-based simulator on a website for
experimenting and investigating diverse dynamics of Carbon and Nitrogen in mineral soils. In A. Mendez-Vilas,
Microorganisms in industry and environment. from scientfic and industrial research to consumer products
(pp.167-171). World Scientific Publishing Co.
Gras, A., Ginovart, M., Portell, X., & Baveye, P.C. (2010b). Individual-based modelling of carbon and nitrogen
dynamics in soils: Parameterization and sensitivity analysis of abiotic components. Soil Science, 175, 363-374.
http://dx.doi.org/10.1097/SS.0b013e3181eda507
Gras, A., Ginovart, M., Valls, J., & Baveye, P.C. (2011) Individual-based modelling of carbon and nitrogen
dynamics in soils: Parameterization and sensitivity analysis of microbial components. Ecological Modelling, 222,
1998-2010. http://dx.doi.org/10.1016/j.ecolmodel.2011.03.009
Grimm, V. & Railsback, S.F. (2005). Individual-based modelling and ecology. Princeton and Oxford: Princeton
University Press.
Grimm, V., Berger, U., Bastiansen, F., Eliassen, S., Ginot, V., Giske, J., et al. (2006). A standard protocol for
describing individual-based and agent-based models. Ecological modelling, 198, 115-126.
http://dx.doi.org/10.1016/j.ecolmodel.2006.04.023
Grimm, V., Berger, U., DeAngelis, D.L., Polhill, J.G., Giske, J., & Railsback, S.F. (2010). The ODD protocol: A
review and first update. Ecological Modelling, 221, 2760-2768.
http://dx.doi.org/10.1016/j.ecolmodel.2010.08.019
Hellweger, F.L., & Bucci, V. (2009). A bunch of tiny individuals-Individual-based modeling for microbes.
Ecological Modelling, 220, 8-22. http://dx.doi.org/10.1016/j.ecolmodel.2008.09.004
Jacobson, A.R., Militello, R., & Baveye, P.C. (2009). Development of computer-assisted virtual fields trips to
support multidisciplinary learning. Computers & Educa ton, 52, 571-580.
http://dx.doi.org/10.1016/j.compedu.2008.11.007
Justi, R. (2006). La enseñanza de ciencias basada en la elaboración de modelos. Enseñanza de las Ciencias, 24,
173-184.
Levy, S.T., & Wilensky, U. (2011). Mining students’ inquiry actions for understanding of complex systems.
Computers & Educaton, 56, 556-573. http://dx.doi.org/10.1016/j.compedu.2010.09.015
Manzoni, S, & Porporato, A. (2009). Soil carbon and nitrogen mineralization: Theory and models across scales.
Soil Biology & Biochemistry, 41, 1355-1379. http://dx.doi.org/10.1016/j.soilbio.2009.02.031 McLane, A.J., Semeniuk, C., McDermid, G.J., & Marceau, D.J. (2011). The role of agent-based models in wildlife
ecology and management. Ecological Modelling, 222, 1544-1556.
http://dx.doi.org/10.1016/j.ecolmodel.2011.01.020
Murray, J.D. (1990). Mathematcal biology. Berlin Heidelberg: Springer-Verlag.
Peck, S.L. (2004). Simulation as experiment: a philosophical reassessment for biological modelling. Trends in
Ecology and Evoluton, 19, 530-534. http://dx.doi.org/10.1016/j.tree.2004.07.019
Prats, C., Ferrer, J., Gras, A., & Ginovart, M. (2010). Individual-based modelling and simulation of microbial
processes: yeast fermentation and multi-species composting. Mathematcal and Computer Modelling of
Dynamical Systems, 16, 489-510. http://dx.doi.org/10.1080/13873954.2010.481809
Railsback, S.F. & Grimm, V. (2011). Agent-Based and Individual-Based Modeling: A Practcal Introducton.
Princeton and Oxford: Princeton University Press.
Schefer, M., Baveco, J.M., DeAngelis, D.L., Rose, K.A., & van Nes, E.H. (1995). Super-individuals a simple
solution for modelling large populations on an individual basis. Ecological Modelling, 80, 161-170.
http://dx.doi.org/10.1016/0304-3800(94)00055-M
Silva, R.G., Jorgensen E. E., Holub S. M., & Gonsoulin M. E. (2005) Relationships between culturable soil
microbial populations and gross nitrogen transformation processes in a clay loam soil across ecosystems.
Nutrient Cycling in Agroecosystems. New York, NY: Formerly Kluwer Academic Publishers. Springer Science and
Business Media B.V., 71, 259-270.
Thompson, K., & Reimann, P. (2010). Patterns of use of an agent-based model and a system dynamics model:
The application of patterns of use and the impacts on learning outcomes. Computers & Educaton, 54, 392-403.
http://dx.doi.org/10.1016/j.compedu.2009.08.020
Wilensky, U. & Reisman, K. (2006). Thinking Like a Wolf, a Sheep, or a Firefy: Learning Biology Through
Constructing and Testing Computational Theories - An Embodied Modeling Approach. Cogniton and
Instructon, 24, 171-209. http://dx.doi.org/10.1207/s1532690xci2402_1

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