In August 2019, the Centre for Research into Ecological and Environmental Modelling (CREEM) is hosting a series of linked training workshops on distance sampling survey methods and analysis. The venue will be the purpose-built teaching facilities at the University of St Andrews, Scotland. The workshops are taught by leading researchers in the field and are a mix of lectures and practical sessions. For the first time, the focus will be on implementing the methods using the statistical programming language R (R Core Team 2018) rather than using Distance for Windows (Thomas et al. 2010). Recent developments in R packages for distance sampling has made functionality in R comparable with Distance for Windows. Using R for distance sampling analysis gives greater flexibility in data preparation, analysis and plotting.
To provide participants with the relevant R experience, the first workshop is a two-day ’Introduction to R (for Distance Sampling)’. For those wishing to learn about the basics of distance sampling, there is a free online course available (https://workshops.distancesampling.org/online-course/) but we realise that it can be difficult to devote the necessary time during a normal working day, therefore, we are holding an ‘Introduction to Distance Sampling (using R)’ workshop over 3 days. For those who are thinking of making the transition from Distance for Windows to R and are unfamiliar with R, we recommend taking both the ‘Introduction to R Workshop (for Distance Sampling)’ and the ‘Introduction to Distance Sampling (using R)’ workshops. For those wishing to learn more advanced methods, or indeed what to do when the basic assumptions of conventional distance sampling methods cannot be met, there is the five day ‘Advanced Distance Sampling’ workshop.
There is the option for a small number of participants to join in the Advanced Distance Sampling workshop remotely – see registration information for the requirements.
Lecture materials, data and exercises will be available for participants to download prior to the workshops. The workshops start at 9am and finish at 5pm each day. A light lunch and refreshments are provided.
Introduction to R (for Distance Sampling), 19th – 20th August 2019
Many of the options available in the Distance for Windows (Thomas et al. 2010) are now available in R packages (e.g. Distance, Miller 2017 and Miller et al. 2013; mrds, Laake et al 2018), but learning a new computing language can be daunting. The goal of this two-day workshop is to introduce participants to R. It is aimed at people who will attend the following distance sampling workshops, but have not used R before or are not comfortable using R.
We will start with the basics of the R language and the RStudio interface and move to data import and manipulation, creating plots and performing statistical tests. The focus of the course will be on using R rather than on methodological details of distance sampling (these will be covered in the Introduction to Distance Sampling (using R) workshop). The majority of the time will be spent in practical sessions.
Introduction to Distance Sampling (using R), 21st – 23rd August 2019,
The objective of this 3-day workshop is to give participants a solid grounding in the basic methods for design and analysis of distance sampling surveys. The course is intended for scientists conducting and/or analysing data for wildlife population assessments. To gain maximum benefit from the workshop, participants should have some quantitative training on basic statistical methods (e.g. data summary and interval estimation). Learning will involve a combination of lectures, computer sessions and discussion groups. The statistical programming language R will be used for all computer sessions and therefore will be invaluable for those wishing to make the switch from Distance for Windows to R. Participants unfamiliar with R should consider attending the ‘Introduction to R’ course immediately prior to this course or work through instructional materials in R available at www.datacamp.com.
Advanced Distance Sampling, 26th – 30th August 2019
The first part of the workshop will review fundamental principles of distance sampling, analyses involving conventional distance sampling, and survey design. Attention will turn to simulation of distance sampling surveys for design purposes, and to survey and analysis methods for dealing with imperfect detection on the trackline (double-observer methods). Roughly two days will be devoted to spatial modelling of distance sampling data (as described in Miller et al. 2013). R will be used in all practical sessions. Throughout the workshop, there will be time for participants to work on problems specific to their data with instructors.
We recommend owning a copy of Buckland et al. (2015). A soft-cover copy of this book is available via Springer MyCopy at a very reasonable price to researchers from participating institutions, follow this link to the site.
There are two pre-requisites for the advanced-level workshop: a) understanding of conventional distance sampling and b) basic competence with the R programming language.
Pre-requisite (a) can be fulfilled by taking the ‘Introduction distance sampling’ workshop or working through the online course made available by CREEM. This online course consists of video lectures and exercises (with solutions). The course can be viewed at the link: https://workshops.distancesampling.org/online-course/. Alternatively, the material is 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).
Pre-requisite (b) can be achieved by either working through instructional materials in R available at www.datacamp.com, or by attending the “Introduction to R (for Distance Sampling)” workshop.
The number of participants on the workshop will be restricted to 35. Places will be filled on a first-come, first-served basis on receipt of a completed a registration form and payment in full. Registration and payment will be available shortly.
For those unable to travel to St Andrews, a limited number of spaces are available to attend the Advanced Distance Sampling Workshop via videoconference link. Online participants will have reduced one-on-one interaction with instructors and consequently, videoconference participants will receive a 10% discount to their registration fees. The videoconference will be conducted in real time: if you are in time zones distant from Scotland, your sleep patterns will need to adjust. Online participation will not be available for the introductory courses.
Before registering as an online participant, please check that your broadband internet connection at the location where you will take the course is both fast and reliable enough to allow audio and video to be transferred in real time. To determine whether this will be feasible, please contact the CREEM IT Officer, email: Philip.LeFeuvre@st-andrews.ac.uk who will send instructions of how to test your system.
The number of places available for the online videoconference link registration is very limited: places will be filled on a first-come, first-served basis on receipt of a completed a registration form, payment in full and a successful test of the internet connection. Please start this process at least four weeks before the start of the workshop to allow sufficient time for testing and the payment to be processed.
Fees cover tuition, course materials, a light lunch and morning and afternoon refreshments. Students and participants from developing countries receive a 25% discount on the full fee. There is a fee increase for workshops paid for after 22nd July 2019.
Introduction to R (for Distance sampling) 300.00 GBP
Introduction to Distance Sampling (using R) 450.00 GBP
Advanced Distance Sampling 750.00 GBP
Advanced Distance Sampling (online) 675.00 GBP
Introduction to R (for Distance sampling) £225
Introduction to Distance Sampling (using R) £335
Advanced Distance Sampling 560.00 GBP
Advanced Distance Sampling (online) 505.00 GBP
Please complete the registration form below. Payment information will be forwarded to you on receipt of your registration form. Confirmation of a place on any workshop will follow once payment has been received.
Buckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL and Thomas L (2001) Introduction to Distance Sampling. Oxford University Press. https://global.oup.com/academic/product/introduction-to-distance-sampling-9780198509271.
Buckland ST, Rexstad EA, Marques TA and Oedekoven CS (2015) Distance Sampling: Methods and Applications. Methods in Statistical Ecology. Springer International Publishing. https://doi.org/10.1007/978-3-319-19219-2.
Laake JL, Borchers DL, Thomas L, Miller DL and Bishop JRB (2018) mrds: Mark-Recapture Distance Sampling. R package version 2.2.0. https://CRAN.R-project.org/package=mrds
Miller DL (2017) Distance: Distance Sampling Detection Function and Abundance Estimation. R package version 0.9.7. https://CRAN.R-project.org/package=Distance
Miller DL, Rexstad E, Thomas L, Marshall L and Laake JL (In press) Distance Sampling in R. Journal of Statistical Software. https://doi.org/10.1101/063891
Miller DL, Burt ML, Rexstad EA and Thomas L (2013) Spatial models for distance sampling data: recent developments and future directions. Methods in Ecology and Evolution 4 (11):1001–1010. https://doi.org/10.1111/2041-210X.12105.
R Core Team (2018) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/
Thomas L, Buckland ST, Rexstad EA, Laake JL, Strindberg S, Hedley SL, Bishop JRB, Marques TA & Burnham KP (2010) Distance software: design and analysis of distance sampling surveys for estimating population size. Journal of Applied Ecology 47: 5-14. DOI: 10.1111/j.1365-2664.2009.01737.x
For information about accommodation in St Andrews follow this link.
Location and Travel Information
For location and travel information follow this link.
Rhona Rodger, Workshop Administrator
Centre for Research into Ecological and Environmental Modelling
University of St Andrews
The Observatory, Buchanan Gardens
Scotland KY16 9LZ
Tel:+44 (0) 1334 461842