Dear list, ? 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. ? I would be grateful for some thoughts or suggstions. ? Regards, ? Juliane ? ? ?????? 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???
adehabitatLT -- movement based kernel density
1 message · Juliane Struve