Christen H. Fleming

This paper develops a workflow and tool to optimize sample sizes in animal tracking projects for robust population-level inferences.

The paper introduces local corrections to kernel density estimation to reduce spillover bias in home range estimation and demonstrates their effectiveness through simulations and a case study.

This paper introduces a new population kernel density estimator (PKDE) to improve space use estimation for animal populations by accounting for temporal autocorrelation and inter-individual variation, showing it outperforms traditional methods.

The paper compares diffusion rate and mean speed as measures of animal movement, finding diffusion rate more accurate and reliable, especially with low-quality data.