Applied methods for analysing capture-recapture (mark-recapture) data using spatially explicit and non-spatial techniques (MARK01)
2 September 2019 - 6 September 2019£275.00 - £550.00
Population demographic parameters (such as survival) and density of a target species are fundamental pieces of information highly desired by ecologists. This course will cover both capture-recapture analyses (CMR) analyses required to obtain estimates of demographic parameters and spatial capture-recapture analyses (SCR) required to obtain spatially-robust estimates of density. We will cover introductory concepts of both analytical approaches using hands-on demonstrations in class. Course content for both CMR and SCR will include data collection and survey design, data processing and formatting, importing data, different model structures and assessing goodness of fit, and interpreting outputs. Each day, we’ll reserve time for open work sessions where participants can receive mentoring and advice from lecturers while applying their newly acquired skills to analysing their own data sets.
Researchers interested in how to analyse capture-recapture data to estimate demographic parameters or density.
Venue – PR statistics head office, 53 Morrison Street, Glasgow, G5 8LB – Google map
Availability – 30 places
Duration – 5 days
Contact hours – Approx. 35 hours
ECT’s – Equal to 3 ECT’s
Language – English
We offer COURSE ONLY and ACCOMMODATION PACKAGES;
• COURSE ONLY – Includes lunch and refreshments and welcome meal Monday evening.
• ACCOMMODATION PACKAGE (to be purchased in addition to the course only option) – Includes breakfast, lunch, refreshments and welcome dinner Monday evening. Self-catering facilities are available in the accommodation. Accommodation is approx. a 6 minute walk from the PR statistics head office. Accommodation is multiple occupancy (max 3-4 people) single sex en-suite rooms. Arrival Sunday 1st September (between 17:00-21:00) and departure Friday 6th September (accommodation must be vacated by 09:15).
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PLEASE READ – CANCELLATION POLICY: Cancellations are accepted up to 28 days before the course start date subject to a 25% cancellation fee. Cancellations later than this may be considered, contact firstname.lastname@example.org. Failure to attend will result in the full cost of the course being charged. In the unfortunate event that a course is cancelled due to unforeseen circumstances a full refund of the course fees (and accommodation fees if booked through PR statistics) will be credited. However, PR statistics will not be held responsible/liable for any travel fees, accommodation costs or other expenses incurred to you as a result of the cancellation. Because of this PR statistics strongly recommends any travel and accommodation that is booked by you or your institute is refundable/flexible and to delay booking your travel and accommodation as close the course start date as economical viable.
The teaching format will be very much “learning by doing”. Concepts will be explained in lectures with the aid of props and in-class demonstrations. Lectures will be followed by comprehensive computer practicals to reinforce learning of key concepts, thus ensuring participants will gain extensive hands-on experience analysing real data sets provided by the lecturers. Once foundation principals are grasped, time will be allocated to ensure participants can analyse their own data sets and access guideance from the lecturers.
Assumed Quantitative Knowledge
All concepts will be explained from first-principles, so little prior knowledge of CMR and SECR analyses is required. However, participants will greatly benefit from having working knowledge of how capture-recapture data is collected in the field.
Assumed computer background
Participants should have a working-knowledge of R, but all code will be provided, so even those participants with basic R knowledge should be able to follow along.
Equipment and software requirements
A laptop/personal computer with the latest version of the following software installed:
Program MARK: http://www.phidot.org/software/mark/downloads/ (for installation on a Mac, please see http://www.phidot.org/software/mark/rmark/linux/).
Requisite R packages include: dplyr, RMark, readOGR, camtrapR, secr, ggplot2.
Information of further R packages required for the practicals will be distributed before the workshop.
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Meet at Flat 2/1, 43 Cook Street, Glasgow G5 8JN at approx. 17:00 onwards
Monday 2nd and Tueaday 3rd – Classes from 09:30 to 17:30
On Day 1 and 2, aspects of non-spatial capture-recapture (CMR) analyses will be introduced. This will include using an in-class demonstration with props to demonstrate the simple Lincoln-Peterson estimator, and expanding on this concept to sampling over multiple time periods. The Cormack-Jolly-Seber model will be covered, and then moving on to more complicated survey designs and analysis (Pollock’s robust design). Day 2 will end with a discussion on using CMR analyses for estimating abundance, and why these estimators are not spatially robust (which will provide a bridge to spatial capture-recapture analyses to be introduced on Day 3).
Wednesday 4th and Thursday 5th – Classes from 09:30 to 17:30
On Day 3 and 4, spatially explicit capture-recapture (SCR) analyses will be introduced and used to estimate density. Again, in-class demonstration with props will be used to demonstrate the concept of SCR from first-principles. Discussion will focus on habitat masks (what are they, why are they needed and how to define them), detector types (e.g., proximity traps like camera traps), running analyses using the ‘secr’ library and interpreting output.
Friday 6th – Classes from 09:30 to 16:00
On Day 5, further principles in SCR will be discussed, a recap of the ‘take-home’ messages from the workshop, and additional consulting time for workshop participants will be provided by the lecturers.
SCR content will be taught in collaboration with David Borchers.
The instructors were excellent and clearly were the reasons for my previous comments. They both combined a deep understanding of statistics and ecology at the same level.Any questions or queries I’ve had, were thus first answered with an ecological point of view and then translated into statistical consideration thereby making much more sense on both side.In addition the course was very well organised, the course director and the two instructors were very friendly as well as professional. On the top of learning many useful things, I’ve also had a very good time during the week there.” Clement Garcia,
Spatial ecologist, Centre For Environment, Fisheries & Aquaculture Science (CEFAS), England
(Attended ADVR course)