MSc Environmental Monitoring, Modelling and Reconstruction

Year of entry: 2023

Course unit details:
Spatial Ecology

Course unit fact file
Unit code GEOG71922
Credit rating 15
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Semester 2
Offered by
Available as a free choice unit? No

Overview

This module will explore the theory and principles of landscape ecology and the spatial techniques available to test, demonstrate and put into practice these principles.

Students will explore ecological data (habitat, species and topographic) across a range of spatial contexts and explore the effect of landscape configuration, land-use and land-cover combinations, on biogeographical patterns, ecological functions and species distribution. This will be done through the application of spatial techniques such as density functions, multi-spectral image classification, as well as through computational landscape ecology metrics and network analyses.

Aims

Equip students with knowledge on the theory of spatial ecology, primarily focused on landscape-ecological methods and principles

Learning outcomes

See below.

Knowledge and understanding

  • Key concepts in spatial ecology, knowledge of landscape ecological processes and reflecting on their importance across a range of contexts.
  • Use of spatial, ecological and geo-statistical techniques such as networks, density functions, species distribution models, buffers and landscape ecology metrics.
  • Accessing, interpreting and analysing large spatial datasets such as multi-spectral imagery, land-use datasets and species record data.

 

Evaluating the suitability of different spatial metrics and techniques for modelling ecological processes across scales.

Intellectual skills

  • Identifying key spatial components of ecological systems
  • The ability to critically evaluate the opportunities and limitations of applying spatial data and techniques to the analysis of complex systems.
  • How critical analytical factors such as scale and spatial context influence analytical merit and interpretability.
  • How ecological processes combine spatially to deliver critical benefits to society.

 

Practical skills

  • Use of GIS software including ArcGIS, QGIS, Fragstats, MaxEnt.
  • Statistical analysis software (SPSS and R)
  • Programmatic geo-computation skills (Python)

 

Transferable skills and personal qualities

  • Ability to express complex ideas related to spatial ecological processes both verbally and in written form.
  • Experience of project design and report-writing.
  • Ability to communicate knowledge and reasoned arguments on complex topics and debates.

The ability to source, manage and operationalise spatial data and techniques to explore real-world problems

Assessment methods

Method Weight
Written assignment (inc essay) 60%
Practical skills assessment 40%

Feedback methods

Verbal and written feedback to students – Week 10 (A1)

Verbal and written feedback to students – late May (2 weeks following submission – A2)

Recommended reading

Reading Lists should normally be managed through the JRUL 'Link2Lists' facility. This field will generically contain the URL address for the 'Link2Lists' facility, but you can amend this as you wish (either entering a different URL in this field, to the specific reading list for the course unit), or by entering supplementary free text details of the reading list.
It is although advised that the 'Link2Lists' functionality is utilised as standard.

Study hours

Scheduled activity hours
Lectures 33
Independent study hours
Independent study 117

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