Dear list,
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I am intersted in estimating movement based kernel densities for fish that were
relocated at fixed receivers positioned along the coast. These data tend to
display both a drift movment between receivers and a random movement component
that can be estimated from the mean and the variance of the transit time between
receivers. ?If I obtain an estimate of the diffusion coefficient from multiple
observations how can I use it to predict the movement based kernel distribution
between two receivers ? So rather than estimating the diffusion coeffiient from
the data as demonstrated in the documentation for adehabitatLT I would like to
use BRB.D() to visualize the kernel distribution between two locations based on
known movement parameters, or at least explore the idea. However, I am not sure
how to proceed. Below is an example of the type of data I am working with.
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I would be grateful for some thoughts or suggstions.
?
Regards,
?
Juliane
?
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?????? X?????? Y????????? ID VR2 ????Fish_ID??????????????? Date VR2????Number
Habitat
2 345481 3020908? 21 BPN??? 1646 2006-08-18 08:51:27??????? 31??? pass??
3 345481 3020908? 22 BPN??? 1646 2006-08-18 08:52:05??????? 31??? pass??
4 345481 3020908? 24 BPN??? 1646 2006-08-18 08:53:20??????? 31??? pass??
5 345481 3020908? 43 BPN??? 1646 2006-08-18 09:09:05??????? 31??? pass??
6 345580 3020891 206 BPS??? 1646 2006-08-18 09:53:20??????? 30??? pass??
7 345580 3020891 215 BPS??? 1646 2006-08-18 09:59:07??????? 30??? pass???
