BIOMETRICS APPLICATIONS
There are no prerequisites required, however
students should be familiar with basic
concepts of Zoology, Ecology, Behavioural
Ecology. Knowledge of English language is
recommended, as part of the technical
documentation is in English.
Knowledge acquired by students will be
verified at the end of the course by means of
an oral test consisting in the discussion of a
series of topics included (but not exclusively)
a topic arranged with the teachers, and based
on practical cases.
The evaluation will be expressed in thirtyths
and will take into account the scientific
mastering and the critical ability about the
topic discussed (30%), the organization and
the skills in presenting the topic (10%), the
ability to apply the concepts learned during
the course to the specific topic (60%).
The teaching aims to develop theoretical and
practical knowledge concerning data
acquisition, data management and analyses
of quantitative data in the field of wildlife
monitoring.
In particular, the objectives are to present the
most common specific techniques in the
context of wildlife monitoring, used to
estimate the distribution, abundance and
density of animal populations, with particular
emphasis on applied ecology in wildlife
management and conservation. Moreover,
techniques that are relevant for the
monitoring and conservation of biodiversity
EU directives will be studied and applied
within the framework of the EU directives
(Directive 92/43/CEE “Habitat”; 2009/147/CE
“Birds”, Regulation 1143/2014 on Invasive
Alien Species).
The course will not only treat the theory and
techniques of data gathering and analyses,
but will put emphasis on their practical
applications, considering statistical
techniques of modern biometry and their
practical application through case studies and
training in data management and data
analyses using the free software R. By the end of the course, the student should
have acquired the following capacities:
- data gathering, management and analyses
of quantitative data;
- programming and applying experimental
designs;
- using the most common techniques for the
analyses of wildlife data;
- using appropriate software for the
management and analyses of wildlife data, in
particular those on distribution and
abundance of animal populations, species
diversity, resource use and selection (home
ranges, diet), and animal behaviour.
The course will be divided into 4 main steps.
The first one will be an introduction to data
collection and management and statistical
programming. In particular during the course
will be presented the basics of using the R programming language for data management
and analysis. The language will be used during
the course to cover specific topics. The
theoretical basis for designing an
experimental design will be described, and
application cases will also be presented.
In the second phase, the main methods for
estimating the abundance of a population will
be covered. Both through the use of direct
and indirect methods. Capture-Mark Recapture (CMR) methods and statistical
models for estimating closed populations and
for open populations will be explored. Few
hours will be dedicated to explore the
"Occupancy" concept (the probability of a
species' presence in a given area). In addition,
analyses for density estimation through the
use of quadrat and aerial counts will be
explored. Finally, the main indices for
biodiversity assessment and evaluation will
be presented and tested.
The third phase we will cover topics related
to the study and analysis of environmental
resource use, both spatial and trophic. Thus,
the concepts of theoretical and realized
niche, environmental preferences and habitat
selection will be addressed. Then the main techniques for space-use analysis by means
of radio-telemetry techniques will be
described. The concept of homerange will
then be explored.
In the last part of the course we will focus on
quantitative measurement of behavioral
ecology of individuals. In particular, the
concept of personality in wildlife context will
be addressed, with special reference to the
use of the arena-test. The use of cowlog
software dedicated to behavioral analysis will
also be presented at this stage. Behavioral
data will then be analyzed through the use of
statistical models and mixed-models will be
explored.
The course objectives will be achieved
through classroom lessons for 48 hours in
total held by the teacher.
At students’ request, at the beginning of each
lesson the teacher will provide clarifications
and insights concerning topics discussed in
previous lessons. It will be also possible to ask for clarifications at any time during lessons.
Anyway, the use of e-learning platform
(forum, glossaries) is highly recommended for
the sharing of any requested issue among
students. Dedicated analysis programs will
also be used in order to facilitate in future the
use of such facilities and with the aim of
having immediate application feedback of
what is presented at the theoretical level.
There will be the opportunity to use the
personal lap-top