Course outline
This outline helps you navigate through the topics covered in the course. We recommend following the videos in the order given below as the individual lectures build upon each other and we assume that materials from previous chapters are known.
Chapter
Topic
Description
1.1: Distance dependent detection
Learn how your ability to detect animals depends on how far the animals are from you.
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Using mark-recapture (or capture-recapture) concepts, we estimate how detection probabilities decline with increasing distance.
2.1: Introduction to abundance estimation
We use the estimated detection probabilities and the observed animals to estimate total abundance of the population.
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We learn how to build capture histories by hand from detection data.
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We describe the three objects required at minimum to fit an SCR model (the detectors, the capture history and the mask), how to create these in R and use them to fit an SCR model.
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3.3 Some technical jargon explained
We explain some of the technical terms related to SCR in plain English.
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We build a capture history for call detections and estimate call density.
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We learn about the components required for fitting an SCR model with the function fit.ascr, use this function to fit the model and interpret the output.
We describe the options for detection unit available for gibbons and introduce the complexities arising from these options.
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We describe how we can localise the location of the calling animals of a group using triangulation of the call angles from the different detectors.
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5.3: Estimate the proportion of occasions that groups call
One example for estimating this parameter is given which involves focal follows of groups.
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5.4 Track groups across multiple occasions
We describe how tracking groups across occasions alleviates the issue that not all groups call during a day.
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5.5 Using calls as the detection unit
We build a capture history for call detections and estimate call density.
