[MARMAM] Intermediate distance sampling workshop St Andrews: early bird registration closing soon

Eric Rexstad er26 at st-andrews.ac.uk
Fri Jun 16 02:08:12 PDT 2017


Third announcement:

New information contained in this notice:
  - Early-bird registration closes 30 June 2017 (two weeks!)
  - A series (~7) of video lectures at this YouTube channel 
https://www.youtube.com/playlist?list=PL8k5p7gTuzQyvDreXY4F_oHSQ6ycovBw8 
These videos will serve as good background (and refresher) in 
preparation for this intermediate workshop.
  - For those unable to travel to St Andrews to attend the intermediate 
workshop, a limited number of spaces are available to attend the 
workshop via videoconference link.  Participants to the workshop via 
this medium will have reduced one-on-one interaction with instructors.  
Consequently, videoconference participants will receive a 25% discount 
to their registration.  Recognise the videoconference will be conducted 
in real time; if you are in time zones distant from Scotland, your sleep 
patterns will need to adjust for that week.

----

The Centre for Research into Ecological and Environmental Modelling 
(CREEM) is hosting an intermediate-level workshop in the summer of 2017 
in our purpose-built facilities at the University of St Andrews, 
Scotland.  The workshops are taught by leading researchers in the field, 
including Len Thomas (@len_thom) and Dave Miller (@millerdl), using 
industry-standard software (visit http://distancesampling.org for more 
details).

The five day workshop will start on Monday 31st July at 09:00, with 
registration from 08:45, at CREEM, and finish on Friday 4th August at 
17:00.

There are two pre-requisites for this workshop: a) understanding of 
conventional distance sampling and b) basic competence with the R 
programming language.  Pre-requisite (a) can be fulfilled by 
understanding of fundamental materials presented in Buckland et al. 
(2001, Chapters 1, 2, 4, 5 and 7) or Buckland et al. (2015, Chapters 1, 
2, 4, 5 and 6) — e.g., through previous training or by independent study.

Pre-requisite (b) can be achieved by either working through 
instructional materials in R available at https://www.datacamp.com , or 
by attending a free half-day tutorial preceding the workshop (30 July 
2017 1400-1700). (details available at the link below)

The first day of the workshop will review fundamental principles of 
distance sampling, analyses involving conventional distance sampling and 
survey design.  Subsequently, attention will turn to simulation of 
distance sampling surveys for design purposes (DSsim package), and to 
survey and analysis methods for dealing with imperfect detection on the 
trackline (double-observer methods) (MRDS package). Slightly more than 
two days will be devoted to spatial (density surface) modelling of 
distance sampling data (dsm package).  A blend of the latest version 
Distance 7 and the R computing language will be employed.  Throughout 
the workshop, there will be unstructured time, with instructors working 
with participants on their specific problems.

Further details and registration instructions can be found at

http://creem2.st-andrews.ac.uk/intermediate-level-distance-sampling-training-workshop-2017/ 



-- 
Eric Rexstad
Research Unit for Wildlife Population Assessment
Centre for Research into Ecological and Environmental Modelling
University of St. Andrews
St. Andrews Scotland KY16 9LZ
+44 (0)1334 461833
The University of St Andrews is a charity registered in Scotland : No 
SC013532

-- 
Eric Rexstad
Research Unit for Wildlife Population Assessment
Centre for Research into Ecological and Environmental Modelling
University of St. Andrews
St. Andrews Scotland KY16 9LZ
+44 (0)1334 461833
The University of St Andrews is a charity registered in Scotland : No SC013532

-- 
Eric Rexstad
Research Unit for Wildlife Population Assessment
Centre for Research into Ecological and Environmental Modelling
University of St. Andrews
St. Andrews Scotland KY16 9LZ
+44 (0)1334 461833
The University of St Andrews is a charity registered in Scotland : No SC013532



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