APPLY NOW!! UNTIL MARCH 5, 2019
This is the class to take if you want to get started at estimating population parameters from field biology data. If you have site-occupancy, capture-recapture or count data on a single-species or multi-species data set, sooner or later you will want to obtain some quantification of population size, species richness, survival probability or spatial distribution of your organisms. Such quantification requires extracting biological signal from inevitably noisy data, and hierarchical modeling is the best tool for the task. This course includes theoretical lectures and R-programming lab sessions to illustrate key concepts and statistical models. Depending on weather conditions there may be some field sampling for occupancy modeling. This is a beginners course, meant for people who so far had limited contact with hierarchical modeling and R-programming but who enjoy quantitative thinking and are keen on confronting abstract thoughts about population dynamics with empirical observations of organisms in the wild. The course will take place at the Estação Experimental Agronômica (EEA) of the Universidade Federal do Rio Grande do Sul, 60 km from downtown Porto Alegre, RS, Brazil. The EEA is an agronomic research facility with classrooms, dinning hall, and sleeping quarters with 6-8 bunk beds per room. The course provides food, accommodation and transportation from downtown Porto Alegre to the EEA and back. All students and course staff will be housed at the station and there is a R$385 (approximately US$100) fee per student to cover food and accommodation expenses. Lectures will be in Portuguese but we are used to hosting students from other countries—anyone who can get by in Portuguese or Spanish should be able to follow the course with no problem. The course has a considerable reading load, all in english.
TO APPLY: Send a CV and personal letter explaining your background and why you would like to take this course to goncalo.ferraz@ufrgs.br. You may right your letter in English, Spanish or Portuguese. Please send email no later than March 5, 2019. We will get back to you by March 15 with the result of your application. We will be able to accept a maximum of 25 students.
INTRODUCTION TO HIERARCHiCAL modeling
(Austral) Fall, 25-student, 6-day intensive course, ECP00142, 3 Cr.
This intensive course is the empirical complement to the semester-long theoretical Population Ecology class on the right. The course provides a sampling-design and statistical modeling basis for obtaining estimates of population parameters that are essential for testing population dynamics theory. Students will study the foundations of hierarchical modeling and its applications to site-occupancy, capture-recapture and count data analysis. Course contents include an overview of the treatment of uncertainty in ecology, generalized linear modeling, and basic principles of maximum-likelihood and Bayesian data analysis. Students will learn to program simple R functions to analyze simulated data.
This class is not a pre-requisite but it is recommended to UFRGS students who will take 'Population Ecology'. Both classes require R programing but this one contains more programing basics—if you want to take both, start with Hierarchical Modeling. If you are at UFRGS, it is also a very good idea—though not at all a requirement— to take Prof. Pablo Inchausti's Métodos Estatísticos Avançados em Ecologia e Evolução (ECP00140)—before taking this class. You can perfectly well take this class on its own too, and we welcome students from other schools in Brazil our abroad.
Note: Currently the formal Portuguese name of this class at UFRGS is Introdução à Modelagem Hierárquica.
Population Ecology
25-30 students, (Austral) Fall semester, ECP0055, 2 Cr.
This class offers an overview of the theoretical foundations of population dynamics. The course opens with a presentation of exponential growth and its simplifying assumptions as a null model of ecological population dynamics. Subsequently, we withdraw the assumptions one by one to study stochasticity, density-dependence, interspecific interactions, age-structure and spatial structure as they affect the demography of wild animal and plant populations (syllabus). Every topic will include readings of classic and contemporary papers, as well as an R practicum where students will implement numerical simulations of the population models.
This class has been offered 20 times to more than 500 students at INPA, USP, UFRJ, UFMT, and UFRGS. The contents have changed since the first edition, at INPA, in 2004, but there's been a consistent emphasis on the formulation of theoretical ideas that can be tested under the empirical approach taught in the companion 'Introduction to Hierarchical Modeling'.
Graduate Student mentorship
Graduate training at the Ferraz lab emphasizes quantitative reasoning, critical thinking, and breadth of understanding. Students are challenged to present their ideas in a mathematical framework, to question every scientific statement and to approach their research problems from a variety of perspectives. Ongoing lab projects center on the analysis of animal population responses to landscape change in the study area of the Biological Dynamics of Forest Fragments Project, near Manaus, in the Brazilian Amazon. Students can develop their projects around ongoing field work and/or analysis of existing Amazon data; students with research interests outside the scope of ongoing work are encouraged to develop original projects, conditional on funding availability. Prospective students are welcome to visit the lab in Porto Alegre, or send email with questions. If you know what you want from graduate school and think that this lab is the right place to get it, try composing a personal statement and send it to Gonçalo's Email.
Lab team at the 2014 retreat, with collaborators, graduate, and undergraduate students. From left to right: (standing) Gilberto J. Fernandez, Renata Ilha, Pâmela Friedemann, Pedro Martins, Alejandra Pizarro, Carolina Schuch; (seating) Bento C. Gonçalves, Murilo Guimarães, Gonçalo Ferraz, and Bianca Darski.