Applied Population Ecology

Home/ Applied Population Ecology
Course TypeCourse CodeNo. Of Credits
Foundation ElectiveSHE2ED3042

Semester to which offered (I/ III/ V) :III semester

Course Title: Applied Population Ecology

Credits: 2 Credits

Course Code (new): SHE2ED304

Type of Course: Elective: Yes Cohort MAED

Course Coordinator and Course Faculty: Dr. Suresh Babu (CC); Dr. Monica Kaushik (Visiting Assistant Professor)

Email of course coordinator:

Pre-requisites: Students who successfully complete the core course ‘Ecology, Ecosystem and Biodiversity (EEB)’ and ‘Ecological Statistics (ES)’ can opt for this course.


Population ecology is the study of patterns and causes of changes in population sizes across spaces and time of one or more species. Management, conservation and monitoring of species are dependent on the population parameters. Population assessment can also help identify threats and evaluates the performance of conservation initiatives. Thus, study of biological population is crucial for most wildlife conservation and research programs.

A wide variety of estimators can be used to monitor populations, provided they are reliable and replicable. In absence of robust estimators, it becomes difficult to infer whether the change (or lack of it) in the estimator is due to the real populations’ changes or some other factor viz. variation in methodology, field personnel, experience, season etc. Empirical estimation of the probability of detection of the species of interest has undergone most if the recent development in the field of population ecology.

We will be using software platforms in this class. Students will be informed about the practical session and the computer-based exercises will be done using personal laptops or the computer lab facility.

Course content



Module description



Basic question, statistics and modelling



(i)Asking right questions in monitoring and assessment



(ii) Statistical distribution and sampling



(iii) Modelling basics and information theoretic approach



Estimating population



(i) Distance Sampling



(ii) Occupancy sampling



(iii) Mark-recapture



Population models for conservation (PVA)



Species distribution models (SDM)



Long-term monitoring (citizen science data)


Learning Objectives

  1. To critically analyze key concepts in designing population assessment and monitoring studies.
  2. To identify the appropriate sampling methods used for answering different management and research objectives.
  3. To identify properties that make a monitoring program an effective one based on the property of interest to be monitored as per the requirement of diverse stakeholders.

Course outcomes:

On successful completion of this course, students will be able to:

  1. Understand the difference between ecological population from ecological communities.
  2. Understanding of diverse methods for estimating population size of the candidate species using the knowledge gained through the theoretical and practical learnings.
  3. Ability to analyze population data, evidences and representations and ability tocomment/draw independent conclusions supported by lines of reasoning andevidence.
  4. Ability to analyze data using appropriate custom software, andvisualizing and communicating information.
  5. Ability to do an independent ecological study revolving around estimation and monitoring of population size/distribution, starting from a study design, tosurvey, to compilation and analysis of data and take a project to its logicalconclusion.

Indicative reading list

  • Boyce, M. S. (1992). Population viability analysis. Annual Review of Ecology and Systematics, 23(1), 481–497.
  • Conrad, C. C., &Hilchey, K. G. (2011). A review of citizen science and community-based environmental monitoring: issues and opportunities. Environmental Monitoring and Assessment, 176(1–4), 273–291.
  • Efford, M. G., & Dawson, D. K. (2012). Occupancy in continuous habitat. Ecosphere, 3(4), 1–15.
  • Elith, J., &Leathwick, J. R. (2009). Species distribution models: ecological explanation and prediction across space and time. Annual Review of Ecology, Evolution, and Systematics, 40, 677–697.
  • Ferrier, S., &Guisan, A. (2006). Spatial modelling of biodiversity at the community level. Journal of Applied Ecology, 43(3), 393–404
  • Hutto, R. L., & Young, J. S. (2002). Regional landbird monitoring: perspectives from the northern Rocky Mountains. Wildlife Society Bulletin, 738–750.
  • Krebs, C. J. (1989). Ecological methodology. Harper & Row New York.
  • Lindenmayer, D. B., & Likens, G. E. (2010). The science and application of ecological monitoring. Biological Conservation, 143(6), 1317–1328.
  • MacKenzie, D. I., & Nichols, J. D. (2004). Occupancy as a surrogate for abundance estimation. Animal Biodiversity and Conservation, 27(1), 461–467.
  • Nichols, J. D., & Williams, B. K. (2006). Monitoring for conservation. Trends in Ecology & Evolution, 21(12), 668–673.
  • Qureshi, Q., Gopal, R., &Jhala, Y. V. (2018). Twisted tale of the tiger: the case of inappropriate data and deficient science. PeerJ Preprints.
  • Rodríguez, J. P., Brotons, L., Bustamante, J., &Seoane, J. (2007). The application of predictive modelling of species distribution to biodiversity conservation. Diversity and Distributions, 13(3), 243–251.

Assessment methodology

Class will be a mixture of discussion, lecture, and computer demonstrations. Students will be assessedbased on two short quizzes one after the module 2nd and one after the 4th module. An exercise on distance sampling would be carried in groups including data collection from two field techniques and their comparison through collected data. This would be a group exercise and would be marked based on an overall assessment for the entire group. There will be assignments for the modeling basic, occupancy sampling and species distribution modeling. Each of these assignments will be carry 20% of the marks.