CODE 94745 ACADEMIC YEAR 2023/2024 CREDITS 6 cfu anno 2 BIOLOGIA ED ECOLOGIA MARINA 10723 (LM-6) - GENOVA 6 cfu anno 2 BIOLOGIA ED ECOLOGIA MARINA 10723 (LM-75) - GENOVA 6 cfu anno 2 CONSERVAZIONE E GESTIONE DELLA NATURA 10589 (LM-60) - GENOVA SCIENTIFIC DISCIPLINARY SECTOR BIO/07 LANGUAGE Italian TEACHING LOCATION GENOVA SEMESTER 1° Semester MODULES Questo insegnamento è un modulo di: ANALYSIS OF ENVIRONMENTAL DATA TEACHING MATERIALS AULAWEB 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 exercises, 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; - interpret and comment on the results of a statistical test; - use the open-source software R for the creation of graphs, data exploration and statistical analysis on univariate and multivariate data. TEACHING METHODS The teaching consists of lectures and applied lessons (in the computer room) where students will learn 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. 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 6) Multiple regressions and Regression Trees 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.). 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 TEACHERS AND EXAM BOARD VALENTINA ASNAGHI Ricevimento: Students are received by appointment, agreed directly with the teacher by email (valentina.asnaghi@unige.it) or via Aulaweb. Exam Board VALENTINA ASNAGHI (President) MARIACHIARA CHIANTORE GIORGIO CHIARANZ (President Substitute) LESSONS LESSONS START https://corsi.unige.it/corsi/10723/studenti-orario Class schedule QUANTITATIVE ECOLOGY EXAMS EXAM DESCRIPTION The exam consists of an oral test concerning the topics covered in the course. The exam will start with the exposition of a scientific article provided by the lecturer or of student's choice (preferably exposed with a short digital presentation, e.g. in power point or similar), and will continue with other 2/3 questions asked by the lecturer on topics covered during classes.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). Please refer to AulaWeb application specific for the teaching for potential updates due to changes in the health and epidemiological situation. 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. The oral examination begins with a critical report on a scientific article (of student's choice or from those provided and available on Aulaweb/Teams) to assess the ability to understand a scientific text, identify objectives of the study, and interpret and comment on the results presented. Exam schedule Data appello Orario Luogo Degree type Note 17/01/2024 10:00 GENOVA Orale 31/01/2024 10:00 GENOVA Orale 14/02/2024 10:00 GENOVA Orale 23/02/2024 09:30 GENOVA Orale 19/06/2024 10:00 GENOVA Orale 10/07/2024 10:00 GENOVA Orale 18/09/2024 10:00 GENOVA Orale FURTHER INFORMATION The topics covered and the numerous examples discussed in class encourage assiduous attendance. Part of the lectures will also be conducted in the computer classroom to enable students to perform the analyses on the data themselves using excel and R.