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Courses are offered to students over two semesters per year, covering a vast range of topics such as animal behaviour, evolutionary biology, biogeography, community ecology, theoretical and quantitative ecology.

Centre for Ecological Sciences (Courses 2024 - 2025)

AUGUST SEMESTER 

EC 202 (AUG) 2:1

Ecology: Pattern and Process

History of ecology; interactions between organisms and the environment; ecological niche; distribution of species and communities; basic population biology; interspecific interactions; community assembly; diversity, richness and abundance; ecosystem structure and function; species concepts; ecological and evolutionary processes (dispersal and diversification); island biogeography; meta-population biology; macroecology.

Umesh Srinivasan

References:

• A.E. Magurran, Measuring Biological Diversity, Blackwell Publishing, 2004.
• J.H. Brown and M.V. Lomolino, Biogeography (Second Edition), Sinauer Associates, 1998.
• Pianka, E.R. Evolutionary Ecology. Eric R. Pianka, e-book, 2011.

EC 301 (AUG) 2:1

Animal Behaviour: Mechanisms and Evolution

History and classical ethology; sensory processing and neural maps; learning and memory; hormones and behavior; behavioral genetics; navigation and communication; optimality approaches and evolutionary models to understand strategies for foraging, competition, group living, sexual selection and mate choice, parental care, predator-prey interactions. 

Rohini Balakrishnan and Kavita Isvaran

References:

• Animal Behavior (Second Edition). Michael D. Breed, Janice Moore (2016) Elsevier
• Neuroethology – J. M. Camhi (1984) Sinauer Associates, Sunderland.
• Behavioural Ecology: An Evolutionary Approach. J. R. Krebs & N. B. Davies (1991) Blackwell Press, Oxford University Press.
• An Introduction to Behavioural ecology.  J. R. Krebs, N. B. Davies and S. A. West (2012) Blackwell Press, Oxford University Press.

EC 305 (AUG) 2:1

Quantitative Ecology: Research Design and Inference

This course will focus on study design and statistical modelling in ecology. We will examine elements of effective study design, common pitfalls in study design and data collection, and the confrontation of ecological hypotheses with data using different statistical approaches and frameworks of inference. Throughout, we will examine concepts using examples from ecology, animal behaviour and evolution. The course will aim to provide proficiency to carry out various statistical techniques commonly used in ecology using the software R. The main topics that will be covered are: The scientific process in ecology; framing ecological questions; elements of study design; confronting ecological models with data; understanding the nature of data; statistical hypothesis testing; linear models, regression, ANOVA; generalised linear models; statistical modelling strategies

Pre-requisites: A background in ecology, behaviour or evolution, either in the form of courses taken, or projects done, or projects that you propose to do in ecology/behaviour/evolution

Kartik Shanker

References:

• Gotelli NJ and Ellison AM (2013) A Primer of Ecological Statistics. Sinauer

• Zuur A, Ieno EN and GM Smith 2007 Analysing ecological data. Springer 

DB 202 (AUG) 2:0

General Biology

Biology and the natural sciences; Growth of biological thought; Matter and life; Origin of life; History of life on earth; Bacteria and Protists; Fungi and other primitive plants; Seed bearing plants; Animals without backbones; Insects, Vertebrates, Phylogeny and Systematics; Mechanisms of  Evolution; Chemical basis of life; Cellular basis of  life; Selected topics in plant and animal physiology; Selected topics in plant and animal ecology; Selected topics in sensory biology and neurobiology; Behavioral ecology and sociobiology; Biological diversity on earth; Complexity; Molecular versus Organismal approaches to solving problems in Science.

Kartik Sunagar and Saskya van Nouhuys

References:

• Peter Medawar (1984). Pluto’s Republic: Incorporating The Art of the Soluble and Induction and Intuition in Scientific Thought
• D’Arcy Wentworth Thompson (1942). On Growth and Form (Edited and Abridged by John Tyler Bonner, 1992).

BE 207: (AUG) 3:0

Mathematical Methods for Bioengineers

Mohit Kumar Jolly and Vishwesha Guttal

(Content will be updated soon)

EC 207 (AUG) 2:0

Scientific writing for ecologists

Over the course of the semester we will progress through the steps of writing a scientific paper. We will cover the concept of a story, and what is needed to draw readers in, keep them engaged, and educate them about the topic. We will also study the structure of a paper, and the purpose of each section in a paper, as well as the structure and purpose of individual paragraphs and sentences.

Saskya van Nouhuys

(only for upper level PhD students. Not for RTP credit)

References:

• Schimel, Joshua. Writing science: how to write papers that get cited and proposals that get funded. OUP USA, 2012.

JANUARY SEMESTER

EC 101 (JAN) 1:0

Process of Scientific Thinking (Compulsory course)

Approaches of scientific practice and research conduct. Historical perspective of various philosophies of science and the process of scientific thinking (e.g. deduction, induction and Inference by Best Explanation). Ethics in conducting, writing, and publishing science (including plagiarism), best practices for replicable research. How to read and review scientific literature critically.

Maria Thaker

References:

• Samir Okasha. 2016. Philosophy of Science: a very short introduction. Oxford University Press

EC 204 (JAN) 2:1

Evolutionary Biology

This course offers an in-depth, hands-on look at the basic principles of evolutionary biology, and discusses the recent advancements and the major ideas in the field. The course has a special emphasis on phylogenetics, population genetics, molecular evolution, genome evolution, and offers exposure to a wide range of theoretical and practical aspects for understanding the micro- and macroevolutionary processes that shape the diversity of life on earth.

Praveen Karanth and Kartik Sunagar

References:

• Futuyma,D. J.,Evolutionary Biology (Third Edition),Sinauer Associates,1998.Li

EC 206 (JAN) 2:1

Evolutionary Genetics

This course will emphasise teaching genetic principles and evolutionary mechanisms that generate the stupendous complexity in nature. The course will begin with discussions on evolutionary cosmology, including the origin of the Universe, Solar System, Earth, and life on our planet as we know it. Following this would be a series of lectures explaining the genetic mechanisms that generate variation in nature and how evolution operates on it. The course will then introduce various tools of the trade, including ‘omics’ technologies and associated bioinformatics, that have made it possible to address broad, interesting, and challenging questions in diverse fields of biology, including ecology, evolutionary biology, genetics, and biomedical research. This course will end with discussions on other interesting topics, including evolutionary development, evolutionary medicine, human evolution, and broader applications of evolutionary reasoning.

The course will consist of lectures, discussions and hands-on bioinformatic practical sessions. Practical sessions will introduce students to various aspects of data acquisition, processing, and analyses, while theory classes will provide in-depth knowledge of the underlying principles. At the end of the course, a final examination will be conducted to evaluate student performances.

Kartik Sunagar

References:

• Evolutionary biology. Douglas J. Futuyma (1998). 3rd Sinauer Associates Inc, Publishers, Sunderland.
• Evolutionary Analysis, Fifth Edition by Jon Herron Scott Freeman.
• Bioinformatics and Functional Genomics, Pevsner (3rd edition).
• Practical Computing for Biologists, Haddock and Dunn.

Pre-requisites: A basic understanding of genetics and molecular biology is desirable but not mandatory.

EC 201 (JAN) 2:1

Theoretical and Mathematical Ecology

This course will introduce students to the following topics: Basic elements of theoretical ecology, building and analyzing mathematical models of ecological systems, generating new ecological insights and hypotheses. Discrete and continuous population models; nonlinear dynamics and bifurcations in ecological models; incorporating stochasticity and space;random walks in ecology and evolution; game theory and ESS; Price equation and levels of selection.

Vishwesha Guttal