Could anyone direct me towards papers or statistical methods used for analysing the visitation sequence by a large mammal? I am studying Arabian tahr at numerous pits (natural and made by myself) using video camera traps. The tahr frequently scrape and dust in the pits, and I am looking to test hypotheses relating to why Arabian tahr scrape and use the pits. I need to understand if the pattern of visitation to pits is non-random, and if the visitation sequence follows a particular pattern, e.g. Male-fem-male-fem, patterns indicating over-marking. I have not conducted analyses such as this before. Thanks...
Hi Steve. I saw your question, thought "that's just the sort of thing I look into" then noticed I used to be in the same lab as the asker! So I hope you are well have had a good last couple of years or so.
On to the question... for determining when an animal is moving towards a patch, I'd use some sort of step-selection analysis (SSA). This has been very recently used by some people I've collaborated with regarding site fidelity: http://www.esajournals.org/doi/abs/10.1890/14-0805.1 though I haven't read that paper in detail. I'm sure SSA could be used for your analysis. I've written a few papers that use it so know the techniques quite well, if you want to discuss.
This analysis would give a time series of visitations, which you could then analyse using standard techniques such as autocorrelation/variograms and looking at the frequency histogram of "time between visits" for patterns. You could probably find a lot of ideas in any text-book on time series analysis at this point. If you want to discuss this further off-line, give me an email.
Hello Steven,
My experience on the topic you've raised is very limited and only related with the use of scent stations for carnivores. I am sure that advances in patch use & visitation analysis techniches, such as those pointed out above by Jonathan would be very useful to you. I just would like to point out to a useful reference, that although a bit outdated, it has some still very usefull points to start exploring your data (paper adjunt). I hope it helps.
All the best,
Hi Steven,
Not sure if this gets at your question, but if you're interested in modeling time of day that activities occur, the following publications by Ridout and Linkie have a nice method using a kernel density estimator. You can also use this method to measure overlap between activity (males vs. females, for example) to investigate avoidance behavior. If you're comfortable working in R, the papers provide a link to some code that I have found very useful in the past.
Cheers,
Casey Day
http://link.springer.com/article/10.1198/jabes.2009.08038
http://onlinelibrary.wiley.com/doi/10.1111/j.1469-7998.2011.00801.x/full
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