Distance workshops, December 2016

Distance logo

Update 28th November: The workshops are fully booked — although we have started a waiting list.  Please register using the link below if you wish to join the list.

A 6-day workshop, divided into two sessions, will be held on distance sampling. The workshop will involve practical field exercises and lab work, taking the student from basic concepts to design and analysis of a complete survey. Register with this link.

Scholarships that provide full or partial funding are available (funding comes from the UK Engineering and Physical Sciences Research Council Global Challenges fund). Each session costs $150, or $300 for both sessions, and full-board accommodation at Mkuru training camp will cost between $162 (dormitory) and $342 (single accommodation) for a full six days.

Session 1: Primer on distance sampling

3 days: December 5-7th 2016

Location: Mkuru Training Camp, 1 hour north of Arusha.

Instructor: Len Thomas, University of St Andrews, Scotland

This session provides a practical introduction to distance sampling surveys of wildlife density and abundance.  The emphasis is on how to design a good survey, how to collect good data, and how to do preliminary analyses using pen and paper, a calculator and a computer spreadsheet. 

Target audience:  

Any wildlife biologist who wants to design, collect or analyze distance sampling survey data. Complete beginners are very welcome.

Those with more experience may (i) benefit from the refresher, (ii) learn something from the detailed discussion of assumptions, how to meet them, and what happens if things go wrong, (iii) be able to use the material as a basis for teaching others.

Pre-requisites:

  • No prior knowledge of distance sampling or plot-based survey methods is assumed.  
  • High school level of maths required (e.g., ability to understand simple formulae and basic algebra).
  • Some familiarity with Excel or another spreadsheet application would be very useful.

Programme outline:

Day 1.  What methods are there for counting animals and plants?  What is a survey?  What makes a good survey?  Plot sampling (e.g., strip transects).  Survey design – how to choose sample plots.  Bias and variance.  Introduction to distance sampling ideas (line transects).  Collecting a little data.  Analyzing it by hand to get detection probability and abundance.  Assumptions of distance sampling and how to meet them.  Good field methods, and how they can help us meet the assumptions.

Day 2. Collect some real data.  Analyze it by hand, and using a computer spreadsheet.

Day 3. Discussion of lessons learnt.  Practical advice on real-world survey designs.  Point transects.  What to do about animals in groups.  Question and answer session.

Session 2: Distance sampling survey design and analysis

Instructor: Len Thomas, University of St Andrews, Scotland

Location: Mkuru Training Camp, 1 hour north of Arusha.

3 days: December 8-10 2016

This session is for people who already know something about distance sampling.  We focus on analysis of distance sampling data using the Distance software, and more complex aspects of survey design such as stratification.  There will be opportunities for participants to analyze and discuss their own data or study, if they have one.

Target audience:

Any wildlife biologist who wants to design a distance sampling survey or analyze distance sampling data using the Distance software, and who is already familiar with the concepts covered in Session 1.  This session is designed to follow on naturally from Session 1 so most people are advised to take both.

Pre-requisites:

  • Attendance on session 1, or familiarity with all of the concepts covered in that session.  
  • Familiarity with basic manipulation and analysis of data on Windows-based computers.
  • A laptop running Microsoft Windows, if you can. If not, we can provide one but need advance notice

Programme outline:

Day 1. Analysis of distance sampling data.
Detection function models.  Distance software.  Fitting detection functions in Distance.  Choosing truncation distances, and selecting detection function models.  When to stop.  Variance estimation.

Day 2. Analysis, and survey design in practice.
Further practice on analysis in Distance.  Stratification.  Split into groups and design a real-world survey.

Day 3. Consultation, survey design discussion, further analysis issues.
Discuss survey designs from yesterday.  Discuss and apply more advanced analysis methods.  Lots of time for consultations with individuals with different real-world survey issues while others are working on exercises; we may well also do some group consultations.