Cargando…
Assessment of a livestock GPS collar based on an open‐source datalogger informs best practices for logging intensity
Ecologists have used Global Positioning Systems (GPS) to track animals for 30 years. Issues today include logging frequency and precision in estimating space use and travel distances, as well as battery life and cost. We developed a low‐cost (~US$125), open‐source GPS datalogger based on Arduino. To...
Autores principales: | , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6010917/ https://www.ncbi.nlm.nih.gov/pubmed/29938081 http://dx.doi.org/10.1002/ece3.4094 |
_version_ | 1783333691590705152 |
---|---|
author | McGranahan, Devan Allen Geaumont, Benjamin Spiess, Jonathan W. |
author_facet | McGranahan, Devan Allen Geaumont, Benjamin Spiess, Jonathan W. |
author_sort | McGranahan, Devan Allen |
collection | PubMed |
description | Ecologists have used Global Positioning Systems (GPS) to track animals for 30 years. Issues today include logging frequency and precision in estimating space use and travel distances, as well as battery life and cost. We developed a low‐cost (~US$125), open‐source GPS datalogger based on Arduino. To test the system, we collected positions at 20‐s intervals for several 1‐week durations from cattle and sheep on rangeland in North Dakota. We tested two questions of broad interest to ecologists who use GPS collars to track animal movements: (1) How closely do collared animals cluster in their herd? (2) How well do different logging patterns estimate patch occupancy and total daily distance traveled? Tested logging patterns included regular logging (one position every 5 or 10 min), and burst logging (positions recorded at 20‐s intervals for 5 or 10 min per hour followed by a sleep period). Collared sheep within the same pasture spent 75% of daytime periods within 51 m of each other (mean = 42 m); collared cattle were within 111 m (mean = 76 m). In our comparison of how well different logging patterns estimate space use versus constant logging, the proportion of positions recorded in 1‐ and 16‐ha patches differed by 2%–3% for burst logging and 1% for regular logging. Although all logging patterns underestimated total daily distance traveled, underestimations were corrected by multiplying estimations by regression coefficients estimated by maximum likelihood. Burst logging can extend battery life by a factor of 7. We conclude that a minimum of two collars programmed with burst logging robustly estimate patch use and spatial distribution of grazing livestock herds. Research questions that require accurately estimating travel of individual animals, however, are probably best addressed with regular logging intervals and will thus have greater battery demands than spatial occupancy questions across all GPS datalogger systems. |
format | Online Article Text |
id | pubmed-6010917 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-60109172018-06-22 Assessment of a livestock GPS collar based on an open‐source datalogger informs best practices for logging intensity McGranahan, Devan Allen Geaumont, Benjamin Spiess, Jonathan W. Ecol Evol Original Research Ecologists have used Global Positioning Systems (GPS) to track animals for 30 years. Issues today include logging frequency and precision in estimating space use and travel distances, as well as battery life and cost. We developed a low‐cost (~US$125), open‐source GPS datalogger based on Arduino. To test the system, we collected positions at 20‐s intervals for several 1‐week durations from cattle and sheep on rangeland in North Dakota. We tested two questions of broad interest to ecologists who use GPS collars to track animal movements: (1) How closely do collared animals cluster in their herd? (2) How well do different logging patterns estimate patch occupancy and total daily distance traveled? Tested logging patterns included regular logging (one position every 5 or 10 min), and burst logging (positions recorded at 20‐s intervals for 5 or 10 min per hour followed by a sleep period). Collared sheep within the same pasture spent 75% of daytime periods within 51 m of each other (mean = 42 m); collared cattle were within 111 m (mean = 76 m). In our comparison of how well different logging patterns estimate space use versus constant logging, the proportion of positions recorded in 1‐ and 16‐ha patches differed by 2%–3% for burst logging and 1% for regular logging. Although all logging patterns underestimated total daily distance traveled, underestimations were corrected by multiplying estimations by regression coefficients estimated by maximum likelihood. Burst logging can extend battery life by a factor of 7. We conclude that a minimum of two collars programmed with burst logging robustly estimate patch use and spatial distribution of grazing livestock herds. Research questions that require accurately estimating travel of individual animals, however, are probably best addressed with regular logging intervals and will thus have greater battery demands than spatial occupancy questions across all GPS datalogger systems. John Wiley and Sons Inc. 2018-05-07 /pmc/articles/PMC6010917/ /pubmed/29938081 http://dx.doi.org/10.1002/ece3.4094 Text en © 2018 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Research McGranahan, Devan Allen Geaumont, Benjamin Spiess, Jonathan W. Assessment of a livestock GPS collar based on an open‐source datalogger informs best practices for logging intensity |
title | Assessment of a livestock GPS collar based on an open‐source datalogger informs best practices for logging intensity |
title_full | Assessment of a livestock GPS collar based on an open‐source datalogger informs best practices for logging intensity |
title_fullStr | Assessment of a livestock GPS collar based on an open‐source datalogger informs best practices for logging intensity |
title_full_unstemmed | Assessment of a livestock GPS collar based on an open‐source datalogger informs best practices for logging intensity |
title_short | Assessment of a livestock GPS collar based on an open‐source datalogger informs best practices for logging intensity |
title_sort | assessment of a livestock gps collar based on an open‐source datalogger informs best practices for logging intensity |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6010917/ https://www.ncbi.nlm.nih.gov/pubmed/29938081 http://dx.doi.org/10.1002/ece3.4094 |
work_keys_str_mv | AT mcgranahandevanallen assessmentofalivestockgpscollarbasedonanopensourcedataloggerinformsbestpracticesforloggingintensity AT geaumontbenjamin assessmentofalivestockgpscollarbasedonanopensourcedataloggerinformsbestpracticesforloggingintensity AT spiessjonathanw assessmentofalivestockgpscollarbasedonanopensourcedataloggerinformsbestpracticesforloggingintensity |