BI7138 - Biodiversity Informatics

Postgraduate course, , 2018


This module provides students with an introduction to graduate-level approaches to biodiversity data analysis, and introduce two important software platforms for statistical exploration, simulation and spatial data analysis. The first half of this module uses R to teach data exploration and statistical analysis. The second half of this module introduces geographic information systems and their use in the analysis of spatially-explicit biological data, including raster and vector data.

Learning Outcomes

At the end of this module students should be able to:

  • Use the “R” computing environment to design experiments, statistically test and simulate patterns in biological systems
  • Explain and use statistical analysis in the context of conservation biology including simple statistical tests, linear and non-linear regression and ordination.
  • Demonstrate an ability to create, manage and manipulate spatial data through the ArcGIS computing platform;
  • Transform vector and raster data into biologically relevant information;
  • Interpret and manipulate remotely sensed spatially explicit data to elucidate underlying patterns and drivers of biodiversity distributions;

Module content

This module provides learners with a graduate-level overview of the following topics in biostatistics, geographic information systems (GIS) and remote sensing:

  • Introduction to the “R” platform
  • Basic statistical methods
  • Experimental design and exploring biological data
  • Advanced statistical methods – GLM and GLMM
  • Introduction to spatial dataand its management
  • Vector data analysis
  • Raster data analysis
  • Remote-sensing