QUANTITATIVE ECOLOGY

QUANTITATIVE ECOLOGY

_
iten
Code
94745
ACADEMIC YEAR
2019/2020
CREDITS
6 credits during the 2nd year of 10723 MARINE BIOLOGY AND ECOLOGY (LM-75) GENOVA
SCIENTIFIC DISCIPLINARY SECTOR
BIO/07
LANGUAGE
Italian
TEACHING LOCATION
GENOVA (MARINE BIOLOGY AND ECOLOGY)
semester
2° Semester
modules
This unit is a module of:
Teaching materials

AIMS AND CONTENT

AIMS AND LEARNING OUTCOMES

The subject aims to provide the basics of experimental design in biological, environmental and natural sciences and analysis techniques to test hypotheses.

Students will be provided with uni and multivariate analysis tools to be applied both in the context of analysis of variance and correlations / regressions.

Teaching methods

The course consists of lectures and lessons applied in the computer room where students will learn to use data analysis techniques using the R.

Lectures in the classroom are delivered through multimedia presentations.

SYLLABUS/CONTENT

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

2) Parameters of a population, statistical inference, estimate of the volume of a population

UNIVARIATE ANALYSIS

1) Frequency distributions, asymmetry and kurtosis

2) The Analysis of Variance: algebraic distribution of variability, the linear model

3) Multi-factorial, hierarchical and orthogonal designs

4) BACI and beyond BACI drawings

5) Correlation and linear regression

MULTIVARIATE ANALYSIS

1) Similarity coefficients and cluster analysis

2) PCA and MDS orders

3) Multivariate tests (ANOSIM, PERMANOVA)

RECOMMENDED READING/BIBLIOGRAPHY

Available (downloadable from the WEB Room) Power Point of the lessons.

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.).

Camussi A., Möller F., Ottaviano E., Sari Gorla M., 1995. Statistical methods for biological experimentation. Zanichelli.

Zar J.H., 1999. Biostatistical Analysis. Fourth Editino. Prentice Hall, Upper Saddle River, New Jersey 07458.

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

DC Schneider Quantitative Ecology, 2nd edn, 2009. London: Academic Press. 432 pp.

A.F. Zuur, E.N. Ieno, G. M. Smith. Analysing Ecological Data. Statistics for Biology and Health. Springer, 2007

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

TEACHERS AND EXAM BOARD

Ricevimento: The reception of the students will be arranged directly with the teacher.

Exam Board

IVANO GIANLUIGI REPETTO (President)

MARIACHIARA CHIANTORE (President)

VALENTINA ASNAGHI (President)

LESSONS

Teaching methods

The course consists of lectures and lessons applied in the computer room where students will learn to use data analysis techniques using the R.

Lectures in the classroom are delivered through multimedia presentations.

LESSONS START

The lessons of the first semester will start from September 23, 2019, and will be completed by January 17, 2020. The lessons of the second semester will start from February 17, 2020 and will be completed by June 12, 2020. Refer to the detailed timetable below link: https://easyacademy.unige.it/portalestudenti/

 

EXAMS

Exam description

The exam consists of an 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.

Five appeals will be available in the summer session (June, July, September) and 2 calls in the winter session (January-February).

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 exam will verify the actual acquisition of knowledge, which the student will have to be able to connect and integrate. The ability to synthesize and recognize the main aspects of the topic will be evaluated and the ability to expose the arguments clearly and with correct terminology will also be considered.

 

FURTHER INFORMATION

Frequency is recommended.