- Docente: Andrea Pasteris
- Credits: 6
- SSD: BIO/07
- Language: Italian
- Teaching Mode: In-person learning (entirely or partially)
- Campus: Ravenna
- Corso: Second cycle degree programme (LM) in Environmental Assessment and Management (cod. 8418)
Learning outcomes
After completing this course, the student should have the theoretical knowledge and practical skills required to measure and predict the effects of human activities on populations, communities and ecosystems and to integrate this information in ways relevant to environmental management.
The student should be able to:
- implement bioassessment methods based on structural and functional characteristics of populations, communities, ecosystems;
- assess ecotoxicity;
- integrate information of different nature, using "weight of evidence” approaches;
- perform ecological risk assessment, both predictive and retrospective, in particular the analysis of the ecological effects of contaminants and other stressors;
- discriminate between natural variability and anthropogenic alteration and assess the impact of human activities on ecological systems, using appropriate sampling designs.
Course contents
Basic
principles of experimental and samplingdesign ,
applied to the
assessment of the impact of human activities on
ecological systems:
- objectives
and hypotheses;
- replication;
- sampling
- control
- interspersione
Biomonitoring methods and indices of ecological quality based on the
structure of the in situ assemblages:
- the reference condition;
- RIVPACS and BEAST;
- the multimetric
approach, indices of biological integrity;
- The extended biotic index (EBI);
- The MacrOper system
The experimental
measurement of
ecotoxicity:
- toxicity
testing;
- analysis of the exposure-response
relationship;
- toxicity values (EC50,
NOEC, LOEC).
Assess the likelihood that one or more stressors are causing or likely to cause adverse
ecological effects:
the ecological risk
assessment (ERA):
- the
USEPA
framework;
- predictive, retrospective, site-specific ERA;
- case studies;
- extrapolation
of laboratory
data;
- the sediment quality triad and
other weight of
evidence approaches.
Readings/Bibliography
Copies of the slides
of the lectures.
Audio recordings of the
lectures.
Papers from scientific
journals and chapters from books
or technical
reports relating to
specific case studies.
Teaching methods
Lectures.
Data analysis classes in computer room.
Both
during the lectures and during the
data analysis
laboratories student-teacher interaction and
discussion between students is actively encouraged.
Assessment methods
The learning assessment aims at a complete and balanced evaluation
of the degree of achievement of all the objectives defined in the
"learning outcomes" section.
The assessment is expressed as a grade up to thirty cum
laude.
The final grade is a weighted average of:
grade allocated to all of the documents produced by the student
during the laboratory classes (weight: 1);
grades achieved in an oral examination lasting approximately 45
minutes (weight: 5).
The weight given to the two tests is proportional to the number of
credits which are respectively dedicated to laboratory activities
(1 cfu) and to lectures (5 cfu).
For a complete and balanced evaluation of the achievement of the
learning objectives, the oral examination is divided into three
questions, each relating to one of the three fields ors which make
up the contents of the course:
- basic principles of experimental and sampling design, applied to
the measurement of the impact of human activities on ecological
systems;
- biomonitoring methods
and ecological quality indices based on the structure of the in
situ assemblages;
- experimental measurement of ecotoxicity and ecological risk
assessment (ERA).
Again for a complete and balanced evaluation of the achievement of
the learning objectives, laboratory classes are based on
computations, statistical tests and indices which are used in the
three fields previously reported.
Upon request, the opportunity to take a replacement test is given
to students who were unable to attend the laboratory
classes.
Teaching tools
Classroom with computer connected to video projector.
Computer room for data analysis classes.
Office hours
See the website of Andrea Pasteris