Distance sampling training workshops, Scotland, 2019
Posted: Mon Mar 18, 2019 10:08 amDistance Sampling Training Workshops 2019
In August 2019, the Centre for Research into Ecological and Environmental Modelling (CREEM) at the University of St Andrews, Scotland, is hosting a series of linked, training workshops on distance sampling survey methods and analysis. Distance sampling is a widely used method of estimating animal density and abundance (Buckland et al. 2001).
Introduction to R (for distance sampling): 19-20 August 2019
Many of the options available in the Distance for Windows program (Thomas et al. 2013) are now available in R (R Core Team, 2018) packages. The goal of this two-day workshop is to introduce participants to the R language and software for statistics, in the context of analysis of distance sampling data.
Introduction to Distance Sampling (using R): 21-23 August 2019
This workshop will give participants a solid grounding in the basic methods for design and analysis of distance sampling surveys. The statistical programming language R will be used for all computer sessions and therefore this workshop will be invaluable for those wishing to make the switch from the Distance for Windows program to R.
Advanced-level Distance Sampling: 26-30 August 2019
This workshop will cover simulation of distance sampling surveys for design purposes, survey and analysis methods for dealing with imperfect detection on the track line (double-observer methods) and spatial modelling of distance sampling data (as described in Miller et al. (2013)). The statistical programming language R will be used for all computer sessions.
For more information see https://www.creem.st-andrews.ac.uk/dist ... rews-2019/ or contact Louise Burt (lb9@st-andrews.ac.uk) or Rhona Rodger (rmr5@st-andrews.ac.uk).
References
Buckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL and Thomas L (2001) Introduction to distance sampling: Estimating abundance of biological populations. Oxford University Press, Oxford, UK
Miller DL, Burt ML, Rexstad EA & 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
In August 2019, the Centre for Research into Ecological and Environmental Modelling (CREEM) at the University of St Andrews, Scotland, is hosting a series of linked, training workshops on distance sampling survey methods and analysis. Distance sampling is a widely used method of estimating animal density and abundance (Buckland et al. 2001).
Introduction to R (for distance sampling): 19-20 August 2019
Many of the options available in the Distance for Windows program (Thomas et al. 2013) are now available in R (R Core Team, 2018) packages. The goal of this two-day workshop is to introduce participants to the R language and software for statistics, in the context of analysis of distance sampling data.
Introduction to Distance Sampling (using R): 21-23 August 2019
This workshop will give participants a solid grounding in the basic methods for design and analysis of distance sampling surveys. The statistical programming language R will be used for all computer sessions and therefore this workshop will be invaluable for those wishing to make the switch from the Distance for Windows program to R.
Advanced-level Distance Sampling: 26-30 August 2019
This workshop will cover simulation of distance sampling surveys for design purposes, survey and analysis methods for dealing with imperfect detection on the track line (double-observer methods) and spatial modelling of distance sampling data (as described in Miller et al. (2013)). The statistical programming language R will be used for all computer sessions.
For more information see https://www.creem.st-andrews.ac.uk/dist ... rews-2019/ or contact Louise Burt (lb9@st-andrews.ac.uk) or Rhona Rodger (rmr5@st-andrews.ac.uk).
References
Buckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL and Thomas L (2001) Introduction to distance sampling: Estimating abundance of biological populations. Oxford University Press, Oxford, UK
Miller DL, Burt ML, Rexstad EA & 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