Learning outcomes of the course unit
In this course students learn to conceive, build, test and interpret basic ecological models, in the various contexts of application. Particular emphasis is given to the understanding of cause and effect mechanisms in complex systems such as ecological communities and ecosystems.
No formal pre-requisit, but it is good be familiar with the R software learned in the Abilità Informatiche and Analisi di Dati Ecologici courses. It is important to have a minimal background in mathematics and matrix algebra
Course contents summary
Dynamics of species interactions. Analysis of ecological networks.
+Models in Ecology
-Why to use models in ecology?
+Density independent models
-Continuous and discrete growth
-Assumptions of density independent models
-Example of a stochastic simulation
+Density dependent models
-Density dependent discrete growth
-Density dependent continuous growth
-Sustainable exploitation of populations
+Age or dimension structured models
-Age structured models
-Dynamics of age or dimension structured models
-Dimension structured models
-Some important parameters
-Stochastic simulation of masting
+Density dependence models
-Age continuous model
-The Lotka-Volterra competition model.
-Prey-Predator Lotka Volterra model.
Qualitative modelling o complex systems.
Quantitative vs qualitative models.
The response of communities to pertrubations. Moving equlibrium.
Systems far from equilibrium: the time averaging.
A Primer of Ecology with R di M. Henry H. Stevens, Springer-Verlag 2009 Edizione (15 luglio 2009) Collana: Use R Lingua: Inglese ISBN-13: 978-038789881
M. Gatto: Introduzione all’Ecologia delle Popolazioni. Clup, Milano 1985.
A. Bodini, C. Bondavalli, S.Allesina: L'ecosistema e le sue relazioni. Franco Angeli 2007.
Teaching is done mainly as frontal lessons. Teaching material in the form of ppt slides, scientific papers of book chapters will be distributed in advance so that students can follow up with the lectures. Computer exercises and simulations will integrate constantly the lectures. This allows the student to conduct true experiments on model and verify his/her comprehension and if his/her predictions are true. Strong emphasis is given on applications of acquired modeling knowledge and on methods to build autonomous judging based essentially on closeness of data to models and hypothesis and not on opinions and prejudices.
Assessment methods and criteria
A written exam to be allowed to sustain the oral exam.
The oral exam is based on a presentation about a ecological modeling scientific paper.
In both trials the evaluation is based upon an assessment scheme whose pillars are: knowledge of the topics developed during the course; competence in using the tool presented in the course; skill in organizing and elaborating the concepts in an integrated fashion; fluency and appropriateness in using the teaching language of the course (Italian) and the ancillary languages (mathemetical langage and english).