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Management of Marine Protected Areas using Bayesian Belief Networks

This course focusses on integrating diverse data for effective environmental management – with examples focussing on Marine Protected Areas – but also suitable for any kind of environmental management problems. No knowledge of statistics (Bayesian or otherwise) is required. This is not an in-depth statistical course, but a guide to synthesising data and making robust decisions based on data and using simple and intuitive models embedded in Microsoft Excel worksheets.

Successful marine protected areas (MPAs) need to fulfil a wide range of functions, from protecting ecological indicators such as fish stocks or biodiversity through to maintaining stakeholder engagement and ensuring sufficient economic benefit can be obtained from the MPA and surrounding area. These functions are multidisciplinary, and in many cases, can be antagonistic in nature.

Data to support scientific and management decisions comes in a wide variety of formats, from conclusive outcomes of rigorous meta-analysis at one end of the scale, to anecdotal stories from local fishers at the other. Integrating multiple data sources to provide interdisciplinary information in a manner transparent manner to stakeholders may therefore seem an impossible challenge, yet through this online course you will be guided through how this can be done in a simple and easy to understand manner.

The training programme is run online by Bournemouth University with contributions from JNCC, the Marine Management Authority and Natural England. Places for 25 students will be offered free of charge thanks to funding of the course by NERC. This will include access to the full set of resources, and comprehensive online support and help throughout. Places will be prioritised for NERC funded PhD students (including those recently completed), however, applications will be considered from other applicants, including those with other PhD funding or working professionally. The course is accredited for delivery at postgraduate level, and successful completion will result in 20 level 7 credits.

Key information

Next start date:

1 December 2017 to 23 March 2018

Location:

Online

Required subjects:

No knowledge of statistics (Bayesian or otherwise) is required

Entry requirements:

PhD (current student, recently completed or post-Doc). We will also consider applications from those working in a relevant field or industry.  

If English is not your first language you'll need IELTS (Academic) 6.5 with a minimum of 5.5 in each component of writing, speaking, listening and reading. For more information check out our International entry requirements.

How you study

This course is delivered online using our virtual learning environment and discussion forums. The supported online study helps to prepare you for the academic assignment (equivalent to 5000 words), the specific subject matter and content of which is determined by your interests and professional context. On successful completion of this assignment you will be awarded 20 academic credits (level 7 - Masters/Postgraduate level).

Programme Specification

Programme specifications provide definitive records of the University's taught degrees in line with Quality Assurance Agency requirements. Every taught course leading to a BU Award has a programme specification which describes its aims, structure, content and learning outcomes, plus the teaching, learning and assessment methods used.

View the programme specification for Management of Marine Protected Areas using Bayesian Belief Networks (pdf 259kb)

Whilst every effort is made to ensure the accuracy of the programme specification, the information is liable to change to take advantage of exciting new approaches to teaching and learning as well as developments in industry. If you have been unable to locate the programme specification for the course you are interested in, it will be available as soon as the latest version is ready. Alternatively please contact us for assistance.

How to apply

For further information please contact the course leader, Dr Rick Stafford

Should you formally apply for a place on this course, you will need to supply the following information:

  • Current status e.g. PhD student, recently completed PhD, Post-doc, working in industry
  • Current funder (if in employment) e.g. NERC, ESRC, University funded, or other
  • When did you complete your PhD (if relevant)?
  • Country of residence
  • If English is not your first language, you will need to provide evidence that you can understand English to a satisfactory level
  • A brief (max 100 words) description of your academic or professional interest in the course.

Fees and funding

There are 25 places funded by NERC available for this course. All applicants are eligible to be considered for the funded places, although NERC will give priority to current or recently completed Doctoral students already funded by NERC.

The fee for self-funded applicants for this unit/short course is £600.00, with an additional fee of £200 if you wish to take the academic assessment. Additional funding help may sometimes be received from your employer given the relevance to your chosen career, if you are a previous student of BU you will receive a discount on your course fees, but other funding options are limited. See our fees and funding section for more information.