🚨Preprint alert! 🚨What if your study animal doesn't know the landscape yet? Standard movement models such as SSA assume it does. In our new study we let it learn instead, and put "learner" against "omniscient" head to head (1/4) doi.org/10.64898/202...
Dongmin (Dennis) Kim
@dongminkim.bsky.social
quantative ecologist studying animal movement & disease ecology | George E Burch Fellow @Smithsonian, previously @UMN and @Harvard | PhD @UMN
🦠🐾MoveDisease Archive – call for contributors We’re compiling animal movement data with diagnostic and health information across wildlife systems. Interested in taking part? Quick registry below 👇 kimx3725.github.io/move-disease... Feel free to pass it on to your colleagues! 😀
I'm joining Rutgers DEENR in a tenure-track faculty position this fall! I'll be recruiting a quantitative postdoc in climate change wildlife ecology (start fall 26 or jan 27) and PhD student doing bioacoustics to study avian responses to extreme weather (start fall 27). More- www.gcmelab.com/join-us
Removing outliers is one of the first things to do when analysing movement data. With porting the remaining move functions to move2 in move2utils package, I also wrote some functions to address the GPS outlier problem. The preprint is out and you can find it here: www.biorxiv.org/content/10.6...
Self-thresholding hierarchical outlier-detection for animal movement tracks
1). Erroneous locations are ubiquitous in animal tracking data and prove notoriously difficult to remove, particularly so in an unsupervised manner. Whether caused by poor satellite geometry, atmosphe...
biorxiv.org