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Species distribution/occupancy modelling using PRESENCE and R


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Species distribution/occupancy modelling using PRESENCE and R (OCCU01)

Full details can be found here;

http://bit.ly/2EwtvlpSPECIES_DIST_MOD

This course will run form 25th - 29th June 2018 in Glasgow City Centre and 
will be delivered by Darryl MacKenzie

 

Course Overview:
The presence or absence of a species across a set of landscape units is a 
fundamental concept widely used in ecology (e.g., species range or 
distribution, epidemiology, habitat modeling, resource selection 
probability functions, as a monitoring metric, metapopulation studies, 
biodiversity and species co-occurrence). An important sampling issue, 
however, is that a species may not always be detected when present at a 
landscape unit. This will result in “false absences” causing parameter 
estimates to be biased if unaccounted for, possibly leading to misleading 
results and conclusions, even with moderate levels of imperfect detection.
This workshop will cover many of the latest methods for modeling patterns 
and dynamics of species occurrence in a landscape while accounting for the 
imperfect detection of the species.

Including:
• estimating level of occurrence at single point in time
• identifying factors that influence species occurrence
• creating species distribution maps
• modelling changes in distribution over time
• study design

Participants will be introduced to available software through worked 
examples, and there will be special emphasis on aspects of study design. 
While primarily aimed at the beginner and intermediate level, more 
experienced researchers will also benefit from attending.
The first four days will comprise of formal lectures and exercises, and the 
final morning will be an informal discussion/consulting session where 
participants can work on their own data, talk one-on-one with the 
instructor, etc.

Email oliverhooker@prstatistics.com with any questions

Check out our sister sites,
www.PRstatistics.com (Ecology and Life Sciences)
www.PRinformatics.com (Bioinformatics and data science)
www.PSstatsistics.com (Behaviour and cognition) 
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From PRstatistics

 

We still have a few places left on the course "Species distribution/occupancy modelling using PRESENCE and R (OCCU01)" with the registration deadline soon approaching (15.06.18) https://www.prstatistics.com/course/species-distributionoccupancy-modelling- using-r-occu01/ This course will be held in Glasgow from the 25th - 29th June 2018 This course is being provided through a collaboration of PR statistics and Proteus and will be delivered by Dr. Darryl MacKenzie Course Overview: The presence or absence of a species across a set of landscape units is a fundamental concept widely used in ecology (e.g., species range or distribution, epidemiology, habitat modeling, resource selection probability functions, as a monitoring metric, metapopulation studies, biodiversity and species co-occurrence). An important sampling issue, however, is that a species may not always be detected when present at a landscape unit. This will result in “false absences” causing parameter estimates to be biased if unaccounted for, possibly leading to misleading results and conclusions, even with moderate levels of imperfect detection. This workshop will cover many of the latest methods for modeling patterns and dynamics of species occurrence in a landscape while accounting for the imperfect detection of the species. Including: • estimating level of occurrence at single point in time • identifying factors that influence species occurrence • creating species distribution maps • modelling changes in distribution over time • study design Participants will be introduced to available software through worked examples, and there will be special emphasis on aspects of study design. While primarily aimed at the beginner and intermediate level, more experienced researchers will also benefit from attending. The first four days will comprise of formal lectures and exercises, and the final morning will be an informal discussion/consulting session where participants can work on their own data, talk one-on-one with the instructor, etc.

 

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