First cycle
degree courses
Second cycle
degree courses
Single cycle
degree courses
School of Science
NATURAL SCIENCE
Course unit
METHODS OF FAUNA, FLORA AND VEGETATION SURVEY
SCO2045690, A.A. 2018/19

Information concerning the students who enrolled in A.Y. 2017/18

Information on the course unit
Degree course Second cycle degree in
NATURAL SCIENCE
SC1178, Degree course structure A.Y. 2014/15, A.Y. 2018/19
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Number of ECTS credits allocated 12.0
Type of assessment Mark
Course unit English denomination METHODS OF FAUNA, FLORA AND VEGETATION SURVEY
Website of the academic structure http://scienzenaturali.scienze.unipd.it/2018/laurea_magistrale
Department of reference Department of Biology
E-Learning website https://elearning.unipd.it/biologia/course/view.php?idnumber=2018-SC1178-000ZZ-2017-SCO2045690-N0
Mandatory attendance
Language of instruction Italian
Branch PADOVA
Single Course unit The Course unit can be attended under the option Single Course unit attendance
Optional Course unit The Course unit can be chosen as Optional Course unit

Lecturers
Teacher in charge LUCIO BONATO BIO/05
Other lecturers GIORGIO CELANT SECS-S/01
MARIACRISTINA VILLANI 000000000000

ECTS: details
Type Scientific-Disciplinary Sector Credits allocated
Educational activities in elective or integrative disciplines SECS-S/01 Statistics 4.0
Core courses BIO/02 Systematic Botanics 4.0
Core courses BIO/05 Zoology 4.0

Course unit organization
Period Annual
Year 2nd Year
Teaching method frontal

Type of hours Credits Teaching
hours
Hours of
Individual study
Shifts
Practice 1.5 18 19.5 No turn
Laboratory 2.5 40 22.5 No turn
Lecture 8.0 64 136.0 No turn

Calendar
Start of activities 01/10/2018
End of activities 28/06/2019
Show course schedule 2018/19 Reg.2014 course timetable

Examination board
Board From To Members of the board
7 METODI DI INDAGINE FAUNISTICA, FLORISTICA E VEGETAZIONALE 2018-2019 01/10/2018 30/11/2019 BONATO LUCIO (Presidente)
VILLANI MARIACRISTINA (Membro Effettivo)
CELANT GIORGIO (Supplente)
6 METODI DI INDAGINE FAUNISTICA, FLORISTICA E VEGETAZIONALE 2017/2018 01/10/2017 25/11/2018 BONATO LUCIO (Presidente)
VILLANI MARIACRISTINA (Membro Effettivo)
CELANT GIORGIO (Supplente)

Syllabus
Prerequisites: Basic knowledge on the fauna, flora and vegetation. Strongly suggested is therefore having attended the course on “Flora, Vegetazione e Fauna regionali” (regional flora, vegetation and fauna).
For the statistics: elementary knowledge of descriptive and inferential statistics; it is suggested to have already attended a statistical elementary course.
Target skills and knowledge: Knowledge to acquire:
- main methods for the detection and the identification of plants and animals
- main methods of statistical analysis appliable to floro-faunistic data
Abilities to develop:
- to design, plan and carry out scientific investigations on fauna, flora or vegetation of an area
- to conduct some widely used statistical analyses
- to understand the results of computer-assisted statistical analyses
Examination methods: Three oral examinations, one for each of the three parts (faunistic methods, floristic and vegetational methods, statistical methods), with the respective teachers. Each examination will comprise open questions, on at least five different topics chosen by the teacher within the program, for a total duration of about 30 minutes. In addition, a test of data analysis (pertinent to faunistic, floristic or vegetational surveys), that the student will perform using the software R.
The overall score will be calculated as the average of the three partial scores of the three teachers, each for the part of his competence.
Assessment criteria: - knowledge and understanding of the methods that have been thought and applied
- ability to undertake the scientific reasoning
- competence on the technical language of the disciplines
Course unit contents: - methods for animal and plant detection, main diagnostic characters, approaches and tools for identification for each of the main ecological groups of fauna and flora inhabiting terrestrial habitat and freshwater (particularly: freshwater fish, amphibians and reptiles, birds, mammals, soil arthropods, freshwater macroinvertebrates, beetles, butterflies, dragonflies, algae, vascular plants, lichens);
- methods for vegetation survey;
- designing and planning surveys on fauna, flora and vegetation of an area; methods for bibliographic search; conventions and standard for communication of the results;
- methods of statistical data analysis: concepts and elementary methods, sampling theory, observational and experimental studies, statistical tests (hypothesis testing, interpretation of the p-value), confidence intervals, inference on means and proportions, comparions of two proportions or two means, multivariate methods (analysis of variance, linear regression, cluster analysis);
- guided experience in the field: detection of animals and plants, species identification, identification of phytosociological assemblages, data analysis and presentation of results.
Planned learning activities and teaching methods: - indoor lessons, with support of multimedia tools, which will be available as PDF to the student;
- seminal lessons and meeting with expert professionists with expertise on selected animal groups or habitats;
- direct experience in the field to apply methods on the fauna, flora and vegetation, in representative sites and habitats, guided by teachers and experts;
- exercizes for statistical analysis of data, based on real dataset obtained in faunistic, floristic or vegetational surveys;
- informatic laboratory with R statistical software.
Additional notes about suggested reading: For the parts on faunistic, floristic and vegetational methods, there are no specific books. The teachers will provide bibliographic references and the electronic teaching material used during the course.
For the part on statistical methods, the teacher will provide a dedicated manual.
In order to develop or consolidate basic knowledge on descriptive and inferential statistics, the following manual is suggested:
Whitlock & Schluter, 2010 - Analisi statistica dei dati biologici. Zanichelli.
For the R software, the following manual is suggested:
Crawley, 2007 - The R Book. Wiley
Textbooks (and optional supplementary readings)

Innovative teaching methods: Teaching and learning strategies
  • Lecturing
  • Case study
  • Interactive lecturing
  • Working in group
  • Loading of files and pages (web pages, Moodle, ...)

Innovative teaching methods: Software or applications used
  • Moodle (files, quizzes, workshops, ...)

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