Virtual fencing in remote boreal forests: performance of commercially available GPS collars for free-ranging cattle

Abstract Background The use of virtual fencing in cattle farming is beneficial due to its flexibility, not fragmenting the landscape or restricting access like physical fences. Using GPS (Global Positioning System) technology, virtual fence units emit an audible signal and a low-energy electric shock when crossing a predefined border. In large remote grazing areas and complex terrains, where the performance of the GPS units can be affected by landscape structure, increased positioning errors can lead to unnecessary shocks to the animals leading to animal welfare concerns. This study aimed to explore factors affecting the GPS performance of commercially available virtual fence collars for cattle (NoFence©), both using static tests and mobile tests, i.e., when deployed on free-ranging cattle. Results The static tests revealed generally high fix success rates (% successful positioning attempts), and a lower success rate at four of 30 test locations was most likely due to a lack in GSM (Global System for Mobile communications) coverage. On average the GPS precision and accuracy errors were 3.3 m ± 2.5 SD and 4.6 m ± 3.2 SD, respectively. We found strong evidence that the GPS precision and accuracy errors increased errors under closed canopies. We also found evidence for an effect of the sky-view on the GPS performance, although at a lesser extent than canopy. The direction of the accuracy error in the Cartesian plane was not uniform, but biased, depending on the aspect of the test locations. With an average of 10.8 m ± 6.8 SD, the accuracy error of the mobile tests was more than double that of the static tests. Furthermore, we found evidence that more rugged landscapes resulted in higher GPS accuracy errors. However, the error from mobile tests was not affected by canopy cover, sky-view, or cattle behaviors. Conclusions This study showed that GPS performance can be negatively affected by landscape complexity, such as increased ruggedness and covered habitats, resulting in reduced virtual fence effectiveness and potential welfare concerns for cattle. These issues can be mitigated through proper pasture planning, such as avoiding rugged areas for the virtual fence border.

Authors

Institutions

Publication Details

Journal
Animal Biotelemetry
Published
2024-11-21
DOI
https://doi.org/10.1186/s40317-024-00389-8
Citations
2
Primary Topic
Wildlife Ecology and Conservation
Type
article
Field-Weighted Citation Impact
0.92

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Virtual fencing in remote boreal forests: performance of commercially available GPS collars for free-ranging cattle

Robert Serrouya, Anna Hessle, Derek Scasta, Barbara Zimmermann et al.
2 citations
Animal Biotelemetry
Wildlife Ecology and Conservation
0.92
article

Virtual fencing in remote boreal forests: performance of commercially available GPS collars for free-ranging cattle

Robert Serrouya, Anna Hessle, Derek Scasta, Barbara Zimmermann, Petter Wabakken, Erik Versluijs, Morten Tofastrud
article en
2 citations

Abstract

Abstract Background The use of virtual fencing in cattle farming is beneficial due to its flexibility, not fragmenting the landscape or restricting access like physical fences. Using GPS (Global Positioning System) technology, virtual fence units emit an audible signal and a low-energy electric shock when crossing a predefined border. In large remote grazing areas and complex terrains, where the performance of the GPS units can be affected by landscape structure, increased positioning errors can lead to unnecessary shocks to the animals leading to animal welfare concerns. This study aimed to explore factors affecting the GPS performance of commercially available virtual fence collars for cattle (NoFence©), both using static tests and mobile tests, i.e., when deployed on free-ranging cattle. Results The static tests revealed generally high fix success rates (% successful positioning attempts), and a lower success rate at four of 30 test locations was most likely due to a lack in GSM (Global System for Mobile communications) coverage. On average the GPS precision and accuracy errors were 3.3 m ± 2.5 SD and 4.6 m ± 3.2 SD, respectively. We found strong evidence that the GPS precision and accuracy errors increased errors under closed canopies. We also found evidence for an effect of the sky-view on the GPS performance, although at a lesser extent than canopy. The direction of the accuracy error in the Cartesian plane was not uniform, but biased, depending on the aspect of the test locations. With an average of 10.8 m ± 6.8 SD, the accuracy error of the mobile tests was more than double that of the static tests. Furthermore, we found evidence that more rugged landscapes resulted in higher GPS accuracy errors. However, the error from mobile tests was not affected by canopy cover, sky-view, or cattle behaviors. Conclusions This study showed that GPS performance can be negatively affected by landscape complexity, such as increased ruggedness and covered habitats, resulting in reduced virtual fence effectiveness and potential welfare concerns for cattle. These issues can be mitigated through proper pasture planning, such as avoiding rugged areas for the virtual fence border.

Animal BiotelemetryVol. 12(1)
University of Wyoming (US), University of British Columbia (CA), Swedish University of Agricultural Sciences (SE), University of Inland Norway (NO), Okanagan University College (CA)
Norges Forskningsråd, Høgskolen i Innlandet
Life in Land
Openalex Percentile: Top 22%
Wildlife Ecology and Conservation
0.92
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.