Understanding the spatiotemporal pattern of grazing cattle movement
Understanding the drivers of animal movement is significant for ecology and biology. Yet researchers have so far been unable to fully understand these drivers, largely due to low data resolution. In this study, we analyse a high-frequency movement dataset for a group of grazing cattle and investigat...
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| Format: | Online |
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Nature Publishing Group
2016
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4995401/ |
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pubmed-49954012016-08-30 Understanding the spatiotemporal pattern of grazing cattle movement Zhao, Kun Jurdak, Raja Article Understanding the drivers of animal movement is significant for ecology and biology. Yet researchers have so far been unable to fully understand these drivers, largely due to low data resolution. In this study, we analyse a high-frequency movement dataset for a group of grazing cattle and investigate their spatiotemporal patterns using a simple two-state ‘stop-and-move’ mobility model. We find that the dispersal kernel in the moving state is best described by a mixture exponential distribution, indicating the hierarchical nature of the movement. On the other hand, the waiting time appears to be scale-invariant below a certain cut-off and is best described by a truncated power-law distribution, suggesting that the non-moving state is governed by time-varying dynamics. We explore possible explanations for the observed phenomena, covering factors that can play a role in the generation of mobility patterns, such as the context of grazing environment, the intrinsic decision-making mechanism or the energy status of different activities. In particular, we propose a new hypothesis that the underlying movement pattern can be attributed to the most probable observable energy status under the maximum entropy configuration. These results are not only valuable for modelling cattle movement but also provide new insights for understanding the underlying biological basis of grazing behaviour. Nature Publishing Group 2016-08-24 /pmc/articles/PMC4995401/ /pubmed/27555220 http://dx.doi.org/10.1038/srep31967 Text en Copyright © 2016, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
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Open Access Journal |
| institution_category |
Foreign Institution |
| institution |
US National Center for Biotechnology Information |
| building |
NCBI PubMed |
| collection |
Online Access |
| language |
English |
| format |
Online |
| author |
Zhao, Kun Jurdak, Raja |
| spellingShingle |
Zhao, Kun Jurdak, Raja Understanding the spatiotemporal pattern of grazing cattle movement |
| author_facet |
Zhao, Kun Jurdak, Raja |
| author_sort |
Zhao, Kun |
| title |
Understanding the spatiotemporal pattern of grazing cattle movement |
| title_short |
Understanding the spatiotemporal pattern of grazing cattle movement |
| title_full |
Understanding the spatiotemporal pattern of grazing cattle movement |
| title_fullStr |
Understanding the spatiotemporal pattern of grazing cattle movement |
| title_full_unstemmed |
Understanding the spatiotemporal pattern of grazing cattle movement |
| title_sort |
understanding the spatiotemporal pattern of grazing cattle movement |
| description |
Understanding the drivers of animal movement is significant for ecology and biology. Yet researchers have so far been unable to fully understand these drivers, largely due to low data resolution. In this study, we analyse a high-frequency movement dataset for a group of grazing cattle and investigate their spatiotemporal patterns using a simple two-state ‘stop-and-move’ mobility model. We find that the dispersal kernel in the moving state is best described by a mixture exponential distribution, indicating the hierarchical nature of the movement. On the other hand, the waiting time appears to be scale-invariant below a certain cut-off and is best described by a truncated power-law distribution, suggesting that the non-moving state is governed by time-varying dynamics. We explore possible explanations for the observed phenomena, covering factors that can play a role in the generation of mobility patterns, such as the context of grazing environment, the intrinsic decision-making mechanism or the energy status of different activities. In particular, we propose a new hypothesis that the underlying movement pattern can be attributed to the most probable observable energy status under the maximum entropy configuration. These results are not only valuable for modelling cattle movement but also provide new insights for understanding the underlying biological basis of grazing behaviour. |
| publisher |
Nature Publishing Group |
| publishDate |
2016 |
| url |
https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4995401/ |
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1613633306065108992 |