PKDE area outputs vs traditional KDE methods

[Gary C]

Hi all, 

I was hoping if anyone could advise or sense check suitability of methods for a dataset. 

I have 30 min GPS data from a central place forager seabird species. Tracking is short term (up to a week with discrete trips of 1-2 days typically). 

As expected, variograms showing autocorrelation within trips and cyclical non-rage resident behaviour and low DOF. 

I have been exploring AKDE and PKDEs based on individual trips as the unit instead of the individual animal. 

When comparing outputs with more traditional seabird KDE methods (e.g. apply CRAWL then adehabitat package using href bandwidth) the PKDE outputs were broadly similar but often smaller and more restricted (in contrast to Noonan et al 2019 typically showing larger areas for AKDE). 

From what I have read (including new Alston et al paper) this is perhaps expected given the type of data (not collected over long range resident time period) and some of the furthest trips from the colony are not included in PKDE if apparently 'exploratory'. 

- Are there then any recommendations of sensible ways to filter/format short term central place forager data for use with AKDEs or is it best to focus on occurrence distributions (if question is overlap with areas of interest offshore)?

Happy to provide examples if helpful. 

Many thanks, 

Gary