I was wondering if there are any spatial ecologists out there who can provide some insight on the trouble I'm having with my Masters research.
I am looking at the association a bat species to high density aggregations of a flowering plant. The bats were tracked throughout the night with a point taken at approximately 10 minute intervals. The bats were tracked over consecutive nights until an asymptote in their space use was reached. So now I have point patterns for each bat that pretty much covers the entirety of their space use at that period.
When the data is displayed visually there is a clear pattern of the bats that were tracked during the flowering period moving into the aggregations of the plant however they also spend a lot of time foraging around their roost sites.
I have simulated the point pattern of each bat 999 times by randomly shifting and rotating the points within the study window (the internal structure of the observed pattern was maintained in the simulations to account for autocorrelation). I then did randomisation tests to see if the average distance to the nearest plant aggregation for the observed data is within the lower 5% of the distribution of the averages for the simulated point patterns. However because the majority of the points collected are highly associated with the roosts the average distance is primarily effected by the position of the roost in relation to any of the plant aggregations.
I've been thinking of ways to disentangle the association with roosts and the association with the plant.
First I was thought about putting a buffer around the roosts and removing the points falling within these buffers from the analysis. The problem is deciding on a buffer. In the other areas I have been using a buffer equal to the circular error probable of the radio tracking error but placing this around the roost will only incorporate the points where the bat was actually inside the roost not foraging around it. All the bats have different foraging patterns around their roosts and I can't see how to assign a buffer distance that is not completely arbitrary.
The second method we have been looking into is taking out the points that are more closely associated (closer in distance) with the roost than the nearest plant aggregation and then running the randomisation to look at the association of the remaining points to the plant. I want to get an idea of whether or not removing the association with the roosts in this way will potentially bias the analysis.
Any thoughts or further suggestions?!
Thanks in advance!