AIMS AND CONTENT

LEARNING OUTCOMES

The teaching aims to provide students the fundamental knowledge for the organization and study of ecological data, the structuring of an experimental design in ecology and the choice and use of the main univariate and multivariate analysis techniques. Students will also be introduced to the use of the open source software R for the creation of graphs, data exploration and statistical analysis of univariate and multivariate data.

AIMS AND LEARNING OUTCOMES

Attendance and active participation in the proposed training activities, which include lectures and practical sessions (in the field and with the software R), will allow the student to:

- learn how to structure an experimental design in the ecological field;

- organize and explore the data collected through an experiment;

- choose and use the correct uni or multivariate analysis techniques to test hypotheses;

- use the open-source software R for the creation of graphs, data exploration and statistical analysis on univariate and multivariate data;

- interpret and comment on the results of a statistical test.

TEACHING METHODS

The teaching consists of lectures and applied lessons (in the computer room or with personal computers) where students will learn how to design an experiment and to apply data analysis techniques using the R software.

Lectures are delivered through multimedia presentations, video, quiz and individual or team practice exercises, which can be performed both in the classroom or on-line.

Seminars will complete the teaching with focus on specific topics.

Please refer to AulaWeb application specific for the teaching for potential updates due to changes in the health and epidemiological situation.

Attendance at classes is strongly recommended, while attendance at practical and laboratory activities is mandatory at 75%.

Students with a physical disability or learning disability certification submitted to the University can find information on support services on the webpage https://unige.it/disabilita-dsa, prepared by the “Office for Inclusion Services for Students with Disabilities and SLD”.

Students may also contact Professor Cristina Carbone (cristina.carbone@unige.it), the DISTAV disability contact person.

SYLLABUS/CONTENT

INTRODUCTION TO QUANTITATIVE ECOLOGY:

1) The experimental design in ecology, the hypothetical deductive method

2) Parameters of a population, statistical inference

UNIVARIATE ANALYSIS

1) Frequency distributions, asymmetry and kurtosis

2) The Analysis of Variance: algebraic distribution of variability, the linear model, parametric and non parametric tests

3) Multi-factorial, hierarchical and orthogonal designs

4) Multi-factorial designs for impact assessment: BACI and beyond BACI 

5) Correlation and linear regression, introduction to multiple regressions

MULTIVARIATE ANALYSIS

1) Similarity coefficients and cluster analysis

2) PCA and MDS orders

3) Multivariate tests (ANOSIM, PERMANOVA)

SOFTWARE R

1) Introduction to the use of R software

2) Frequency distributions

3) Data exploration

4) Univariate analyses

5) Multivariate analyses

RECOMMENDED READING/BIBLIOGRAPHY

Available (downloadable from the AulaWeb or Teams) presentations, videos and all material of the lessons. The provided material is sufficient for the exam preparation.

Suggested reading:

Fowler, Cohen. Statistics for Ornithologists and Naturalists. Natural Sciences Texts, Franco Muzzio Editore, 2010.

Dytham, Calvin. Choosing and using statistics: a biologist's guide. John Wiley & Sons, 2011.

D. Borcard et al., Numerical Ecology with R, Use R, 1 DOI 10.1007/978-1-4419-7976-6_1, © Springer Science+Business Media, LLC 2011

Underwood A.J., 1997. Experiments in ecology. Cambridge University Press

Gambi M.C., Dappiano M., 2003. Handbook of sampling methodology and study of Mediterranean marine benthos. Marine Mediterranean Biology, vol 10 (Suppl.).

Legendre, Pierre & Louis Legendre. 1998. Numerical ecology. 2nd English edition. Elsevier Science BV, Amsterdam. xv + 853 pages.

TEACHERS AND EXAM BOARD

Exam Board

VALENTINA ASNAGHI (President)

PAOLO VASSALLO (President Substitute)

LESSONS

LESSONS START

For lessons start and timetable visit:  https://easyacademy.unige.it/portalestudenti/

Class schedule

The timetable for this course is available here: Portale EasyAcademy

EXAMS

EXAM DESCRIPTION

The exam consists of an written and oral test concerning the topics covered in the course. The exam is passed if the student has obtained a grade greater than or equal to 18/30.

Four appeals will be available in the winter session (January-February) and 3 calls in the summer session  (June-July-September) .

Please refer to AulaWeb application specific for the teaching for potential updates due to changes in the health and epidemiological situation.

The grade of the MARINE QUANTITATIVE ECOLOGY sub-module will be averaged with the grade of the LANDSCAPE ECOLOGY sub-module to obtain the final grade of the MARINE ECOLOGY AND ANALYSIS module.

ASSESSMENT METHODS

Details on how to prepare for the exam and the degree of detail required for each topic will be provided during the lessons. The written exam will mainly focus on the topics covered during the lectures and will aim to evaluate the achievement of the adequate level of knowledge. The ability to present the topics clearly and with correct terminology will also be assessed. The oral exam starts from the discussion of the written exam replies. questions aimed at verifying the complete understanding of the main topics of the teaching will follow.

FURTHER INFORMATION

The topics covered, the numerous examples discussed in class and high number of practical activities encourage assiduous attendance.