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