1Biological Sciences, University of Notre Dame, 2Anthropology, University of Notre Dame
Saturday All day, Park Concourse
Recent reviews home range measurement methodology has highlighted a need for a standard currency of measurement and reporting. Across methods including, but not limited to minimum convex polygon, kernel density estimation, linear home range, and harmonic mean, researchers struggle with reproducibility in home range determination.
In an effort to aid standardization of home range estimation methodology we have sub-sampled data and calculated home ranges over a variety of methods from 3 GPS satellite collars. Collars recorded the locations of long-tailed macaques (Macaca fascicularis) over 1-4 week long periods in mixed, rainforest canopy and manicured park space in Singapore. The collars fixed a position in >98% of positioning attempts for collars deployed at Bukit Timah but only ~63% of the time for a collar deployed at Upper Seletar (1: 1786/1810; 2: 1704/1705; 3: 386/609 programmed positions). The dense amount of data taken across intervals varying from every 5 minutes to hourly across 1-4 week long time periods enable us to sub-sample data to determine the most efficient collar program settings. Furthermore, we will include data from other studies utilizing both VHF and GPS tracked individuals to compare the relative methodological efficiency to help researchers evaluate whether the man-hour costs or monetary investment associated with VHF telemetry and GPS collars respectively are most worth investing in. The meta-analysis will also examine the importance of sampling interval. Finally, we will report on the functionality of a remote-trigger drop-off mechanism and report on the impact of study site location and collar programming add/drop times.
This work was supported by GLOBES, an interdisciplinary training program funded by National Science Foundation IGERT grant #0504495, the University of Notre Dame's Center for Aquatic Conservation, the National Science Foundation East Asia Pacific Summer Institute program, National Science Foundation #BCS-0639787, and funds from the University of Notre Dame Office of Research.