MATHEMATICAL MODELLING IN ECOLOGY

Teaching in italian
MATHEMATICAL MODELLING IN ECOLOGY
Teaching
MATHEMATICAL MODELLING IN ECOLOGY
Subject area
SECS-S/02
Reference degree course
COASTAL AND MARINE BIOLOGY AND ECOLOGY
Course type
Master's Degree
Credits
6.0
Teaching hours
Frontal Hours: 48.0
2021/2022
Year taught
2021/2022
Course year
1
Language
ENGLISH
Curriculum
Curriculum E-Biodiversity and Ecosystem Sciences
Reference professor for teaching
Location
Lecce

Teaching description

Basic concepts of mathematics and statistics.

The main goal of the course is to provide basic tools for analyzing ecological data with focus on probabilistic and mathematical modeling issues. In particular the course deals with:

1) Introduction to statistics and probability;

2) Association and entropy measures;

3) Probability and statistical inference for Normal and not Normal populations;

4) Linear models and non linear models.

During the course, the statistical software R will be illustrated and the students will be able to elaborate their data using it.

The course aims at providing basic methodologies for analyzing ecological data and modeling their intrinsic variability.

Slides, exercises provided on the web page. Practical exercises with the statistical software R.

Written exam with R.

1. Introduction: why analyzing data in ecology?

2. Exploratory data analysis and graphics

3. Deterministic functions for ecological modelling

4. Probability and stochastic distribution of ecological modeling

5. Stochastic simulation and power analysis

6. Statistical inference

7. Linear regression model and generalized linear models

8. Non linear models

9. Modelling variance

10. Dynamic models

During the course, the statistical software R will be illustrated and the students will be able to elaborate their data using it.

B. Bolker (2007) Ecological models and Data with R, PRINCETON UNIVERSITY PRESS.

A. Zuur, E.N. Ieno, G.M. Smith (2007) Analyzing ecological data, Springer Ed.

Interesing web book: http://web.stanford.edu/class/bios221/book/introduction.html

Semester
Second Semester (dal 07/03/2022 al 10/06/2022)

Exam type
Compulsory

Type of assessment